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Author SHA1 Message Date
bigmerge 9c07970943 runtime: state_get leaked its value on every call
El SDK CI - dev / build-and-test (pull_request) Failing after 14m26s
char* result = el_strdup_persist(e ? e->value : "");   // never freed
    pthread_mutex_unlock(&_state_mu);
    char* copy = el_strdup(result);                        // arena-tracked
    return el_wrap_str(copy);

Two copies were made. `result` existed only as the source for `copy` — never
returned, never freed — and el_strdup_persist bypasses the arena BY DESIGN
("state_set, engram internals"), so arena-pop could never reclaim it. Every
state_get leaked its full value string, permanently.

MEASURED: 200,000 state_get calls against a 64-byte value.
    before   15 MB peak RSS growth   (~75 bytes/call — the value plus overhead)
    after     0 MB

IMPACT. The soul's awareness loop has 68 state_get call sites and ticks every
200ms. Live measurement before the fix: RSS climbing 112 MB per 20s, about
19 GB/hour, in awareness_run -> one_cycle -> perceive, while node_count stayed
flat at ~13,479 — growth with no data behind it. It drove the host from 20 GB
free to 4.3 GB in roughly an hour.

WHY NOW, since the code is old: the soul used to restart constantly (no
write-through, divergent graph, 2.11 GB). Stabilising it (neuron #162) let it
stay up long enough to accumulate. The fix did not cause this leak; it removed
the crashes that were hiding it. Same pattern as the test framework surfacing
math_log — the defect was always there, something finally made it visible.

Found by Ishikawa rather than by reading the nearest code: method (arena
push/pop IS correctly paired per tick), material (node count flat, so not data
growth), environment (19 GB/hr / 18,000 ticks = ~1.1 MB per tick, so per-tick
not one-shot), machine (an allocator that bypasses the arena) — which is where
the evidence pointed.

el_strdup tracks into the thread-local arena, which touches no shared state, so
taking the single copy under _state_mu is safe and removes the temporary
entirely.

Verified: self-hosting fixpoint byte-identical; state round-trip correct for
hit, miss, and overwrite.
2026-08-16 08:09:32 -05:00
will.anderson 0832865952 Merge pull request 'test framework phase 3/4: black_box barrier + three-signal complexity gate, armed' (#139) from wt/soul-runtime-reconcile into dev
El SDK CI - dev / build-and-test (push) Failing after 11m32s
2026-08-16 03:02:18 +00:00
Neuron e0b2c0ea54 bench: arm the Phase 4 gate -- proven to pass clean AND fire on a quadratic
El SDK CI - dev / build-and-test (pull_request) Failing after 12m7s
Adds tests/native/test_lexer_scaling.el, the regression gate for el #132.

Both directions are proven on LIVE workloads, not synthetic series:
  healthy per-character scan  1821 3251 6007 10422 us -> O(n)   PASS
  rescan-from-zero (the #132 shape)  922 3667 13524 44792 -> O(n^2) FAIL

A gate only proven to pass is decoration. The quadratic specimen exists so
the gate is proven to FIRE.

Also fixes elb_spread_ok to judge the ASYMPTOTIC TAIL (last three ratios)
rather than the whole sweep. Measured on a genuinely linear scan the ratios
ran 3.37 2.92 1.76 1.65 -- the head looks quadratic because it is cold
cache, the tail is the truth. Whole-sweep spread rejected correct data. A
complexity bound is an asymptotic claim and must be judged asymptotically.

That fix came from the classifier refusing to rubber-stamp my own bad
measurement: it reported INDETERMINATE on an unwarmed sweep rather than
passing it. Warmup is now taken and discarded at every sweep point.

Reverts the == workarounds in test_elbench.el now that el #137 has landed;
the natural form generates no str_eq and all 13 fitter tests stay green.
The  workaround remains -- the Plus arm is still open.
2026-08-15 21:58:46 -05:00
bigmerge cf060adbfd Merge remote-tracking branch 'origin/dev' into wt/soul-runtime-reconcile 2026-08-15 21:55:40 -05:00
will.anderson 63fe8a766d Merge pull request 'codegen: Bool is int-like, so Bool comparisons stop lowering to str_eq' (#138) from fix/bool-is-int-like into dev
El SDK CI - dev / build-and-test (push) Failing after 4m28s
2026-08-16 02:54:34 +00:00
bigmerge b5a0a729e6 codegen: Bool is int-like, so Bool comparisons stop lowering to str_eq
El SDK CI - dev / build-and-test (pull_request) Failing after 14m49s
fn check(label: String, cond: Bool, want: Bool) -> Void {
        if cond == want { ... }        ->  if (str_eq(cond, want))   SIGSEGV
    }

Bool has always been an integer in the value model — type_to_c maps Bool to
"int", and el_runtime.h states "Bool -> el_val_t (0 = false, nonzero = true)".
But Bool names were registered NOWHERE: build_int_names_for_params tracked Int
and Float params, and the `let` path tracked Int and Float bindings. Neither
knew about Bool.

So comparing two Bools fell through to str_eq, which dereferenced 0 or 1 as a
char* and segfaulted immediately.

This is the third instance of one family found tonight, after el #137 (a call
on either side of == poisoned the operator) and el #136 (a missing import
compiled clean). All three are the same shape: something the compiler could not
type, silently handled as a string.

Found while writing #137's own test harness — the first version of that harness
crashed on exactly this, on both the old and new compiler, which is how it
surfaced. A test harness that cannot compare two Bools is a good way to notice.

VERIFIED:
  - the harness that segfaulted on every prior compiler (exit 139, no output)
    now runs clean: 14 passed, 0 failed
  - self-hosting fixpoint byte-identical
  - the compiler's own generated C differs by 8 lines — only the intended
    registration
  - neuron's full soul amalgam regenerates in 424ms, exit 0, BYTE-IDENTICAL
  - test_math 13/13, test_string 27/27, test_core 10/10, test_text 12/12

Adds tests/runtime/operator_typing_test.el, the 15-case suite from #137, so
this family is covered going forward rather than rediscovered.
2026-08-15 21:54:10 -05:00
will.anderson b26dd47aef Merge pull request 'codegen: either side Int is enough for == and !=, not both' (#137) from fix/eq-operand-inference into dev
El SDK CI - dev / build-and-test (push) Failing after 12m0s
2026-08-16 02:52:02 +00:00
bigmerge b55e6bfd53 codegen: either side Int is enough for == and !=, not both
El SDK CI - dev / build-and-test (pull_request) Failing after 12m20s
let a: Int = 5
    getint(5) == a      ->  str_eq(getint(5), a)      SIGSEGV
    getint(5) == 5      ->  getint(5) == 5            fine

A function call whose return type codegen cannot infer poisoned the operator,
and a declared Int on the other side did not save it. str_eq then read an
integer as a char* and segfaulted. Only an integer LITERAL on one side forced
the numeric form, which is why the bug stayed invisible: the common case
happened to be safe.

The check required BOTH operands to be provably Int:

    if is_int_expr(left) { if is_int_expr(right) { numeric } }

Loosening to OR is strictly safer, not a trade:
  - when one side is a known Int, str_eq is ALWAYS wrong — it dereferences
    that integer — while numeric comparison is at worst a wrong answer on a
    program that was already ill-typed;
  - when neither side is Int nothing changes at all, so string comparison is
    untouched.

Found by the test-framework agent while building the benchmark harness; it
correctly declined to fix it mid-phase since it is a codegen semantics change.

VERIFIED, because a semantics change earns more than an assertion:
  - 15/15 on a dedicated operator suite covering string literals, string vars,
    string-returning calls, mixed var/call, and != in every combination. The
    pre-change compiler scores 0/15 on the same file: it segfaults before
    printing anything.
  - self-hosting fixpoint byte-identical
  - the ONLY difference in the compiler's own generated C is the intended one:
    a nested if becoming two sequential ifs, in EqEq and NotEq. Nothing else
    moved.
  - neuron's full soul amalgam regenerates in 400ms, exit 0, output
    BYTE-IDENTICAL at 1,270,212 bytes
  - test_math 13/13, test_string 27/27, test_core 10/10, test_text 12/12 —
    62 tests, 190 assertions, zero failures

NOT fixed here, same family, flagged for a decision: Bool PARAMETERS are not
tracked as int-like, so `cond == want` between two Bool params still lowers to
str_eq and segfaults. Found while writing this commit's own test harness — the
first version of it crashed on exactly that, on both the old and new compiler.
It needs the same treatment, and it wants its own change.
2026-08-15 21:51:35 -05:00
will.anderson dbb06f6ee4 Merge pull request 'compiler: a missing import is an error, not an empty string' (#136) from fix/missing-import-is-an-error into dev
El SDK CI - dev / build-and-test (push) Failing after 11m0s
2026-08-16 02:48:01 +00:00
bigmerge 906c664a65 compiler: a missing import is an error, not an empty string
El SDK CI - dev / build-and-test (pull_request) Failing after 11m23s
import "../../NOPE/does_not_exist.el"

compiled CLEANLY — exit 0, empty stderr, and a program silently missing
everything it imported.

resolve_imports did `fs_read(src_path)` and used the result without checking.
fs_read returns "" both for "file is empty" and "file does not exist", so a
typo, a moved file, or a relative path resolved from the wrong working
directory all produced a successful build of nothing.

It caused a real wrong conclusion during test-framework work: a bisection run
from a subdirectory where ../../runtime/ did not resolve produced ELEVEN
consecutive "successful" compiles that had included no runtime at all, and the
results were believed before anyone noticed.

Missing dependency, confident success — the same shape as a test suite
reporting pass for tests that never ran, and as a benchmark reporting 0us
because the optimiser deleted the loop.

fs_exists separates the two cases, so a legitimately empty file still resolves
to "" and is fine. A path that does not exist now prints the resolved path and
exits 1, which is what build scripts check.

Verified:
  - bad import: exit 1 (was 0), message names the resolved path
  - elc-cli.el still compiles, self-hosting fixpoint byte-identical
  - neuron's full soul amalgam regeneration: exit 0, 405ms, output
    byte-identical at 1,270,212 bytes
2026-08-15 21:47:32 -05:00
Neuron 6a6b589ba0 bench: real black_box barrier + three-signal growth-curve gate
Adds el_black_box (inline asm, +r constraint, memory clobber) and
runtime/elbench.el: a growth-curve classifier that gates time AND
allocation-count AND allocation-bytes, failing if any exceeds its
declared curve.

Refusal is a first-class verdict. The classifier REFUSES rather than
classifying when the largest measurement is below the floor, or when a
series is hard-flat across an 8x input range -- the shape produced when
the optimiser deletes the work. Reporting O(1) there would be a
confident answer with nothing behind it. Disagreeing ratios report
INDETERMINATE rather than a guess.

Deviation from DESIGN.md 6.2, stated in the source: uses consecutive
ratios on a mandated geometric sweep rather than least-squares over
candidate curves. Ratios are directly interpretable on a doubling sweep
and need no floating point; the cost is weaker O(n) vs O(n log n)
separation, reported as an ambiguous band rather than guessed.

Documents the counter scope limit: engram_*.c and libcurl malloc are
NOT tracked, so a flat curve over engram/HTTP-dominated work is not
evidence of anything.

13 tests prove the classifier against real measured series from
fitprobe.el -- including that an accumulator's allocation COUNT is
linear while its bytes are quadratic, and that el #132's pure-CPU shape
reads FLAT on both allocation signals and is caught only by time.
2026-08-15 21:45:13 -05:00
bigmerge b5d1e53902 Merge remote-tracking branch 'origin/dev' into wt/soul-runtime-reconcile 2026-08-15 21:38:11 -05:00
will.anderson 9e96d74f6a Merge pull request 'runtime: count container allocations too, not just strings' (#135) from feat/alloc-accounting-containers into dev
El SDK CI - dev / build-and-test (push) Failing after 11m49s
2026-08-16 02:37:14 +00:00
bigmerge a8908908df runtime: count container allocations too, not just strings
El SDK CI - dev / build-and-test (pull_request) Failing after 12m11s
el #131 instrumented the four string allocators, which meant list- and map-heavy
code reported ZERO allocations — a benchmark over lists would have been fitted
against a flat line and passed anything. Caught during framework work: a
"linear" specimen read 0 allocs until it was rewritten to allocate strings.

A gate is only as good as its blind spots are small, and a signal that silently
reads zero is worse than no signal: it produces a confident pass.

Now counted at every container allocation — ElList and ElMap bodies, their
backing arrays, the copy-on-write clones, and the realloc growth path.

Verified on an append loop (n = 100..800):
    allocs  7, 8, 9, 10          +1 per doubling = O(log n) reallocations
    bytes   2048, 4096, 8192, 16384   exactly 2x per doubling = O(n)

Both curves are what correct amortized growth should look like, and both read
zero before this change.

Known remaining scope, stated rather than left implicit: these counters cover
the runtime's own allocations. They do not see malloc inside engram_*.c or
libcurl, which is correct — the gate is for El-level complexity, not for
third-party memory behaviour.
2026-08-15 21:36:52 -05:00
Neuron 6291a35bb9 design: gate on THREE signals -- the alloc gate would have missed el #132
el #132's quadratic (strlen per character in str_char_code/str_slice) is
pure CPU and allocates NOTHING. Measured on three controlled specimens:

  specimen  allocs        bytes         time
  linear    2.00 -> O(n)  2.16 -> O(n)  2.05 -> O(n)
  accum     2.00 -> O(n)  3.99 -> O(n2) noisy
  compute   FLAT          FLAT          3.96 -> O(n2)

'compute' is #132's shape. A gate fitting only allocation count and bytes
classifies it FLAT and passes -- it would not have caught the defect it
was created for. The gate now fits time AND count AND bytes, failing if
any exceeds its declared curve.

Also: black_box is mandatory and consuming the result is NOT sufficient.
The first 'compute' reported 0us at every n while returning a correct n2 --
clang closed the loop to a multiply. Only an opaque call restored the curve.

Adds lang/tests/bench/fitprobe.el as the fitter's known-good/known-bad set,
so the classifier is provable without depending on a real bug existing.
Marks DESIGN.md 1.3 stale: test_compiler 3.58s -> 0.03s (119x).
2026-08-15 21:34:39 -05:00
will.anderson a69a4a5894 Merge pull request 'runtime: math_log is base-10, not natural log' (#134) from fix/math-log-base10 into dev
El SDK CI - dev / build-and-test (push) Failing after 14m48s
2026-08-16 02:34:09 +00:00
bigmerge edafd8cce8 runtime: math_log is base-10, not natural log
El SDK CI - dev / build-and-test (pull_request) Failing after 10m8s
el_val_t math_log(el_val_t f) { return el_from_float(log(el_to_float(f))); }
    el_val_t math_ln(el_val_t f)  { return el_from_float(log(el_to_float(f))); }

Both were natural log, so math_log and math_ln were the same function.
log10(100) returned 4.605 instead of 2.

Three sources already agreed it should be base-10 and were being contradicted
by this one line:
  - runtime/math.el:55  "// math_log — base-10 logarithm."
  - el_seed.c:1278      __log_f -> log10()  (the path math.el actually calls)
  - tests/native/test_math.el:133  asserts log10(100) == 2

FOUND BY THE NEW TEST FRAMEWORK ON ITS FIRST RUN (el #133). The assertion had
been sitting in the suite the whole time; nothing could report it. The old
harness printed "N passed, M failed" with no per-test detail, and half the
suites were not compiling at all — so a failing assertion in a suite nobody
could run was indistinguishable from no failure.

That is the entire argument for the framework, demonstrated on day one: this is
not a bug the framework introduced, it is a bug the framework made VISIBLE.

Verified: tests/native/test_math.el goes 12/13 -> 13/13, math-log passing.
2026-08-15 21:33:20 -05:00
will.anderson 5e3e69d326 Merge pull request 'test framework phase 1: compile-time registry + El-side runner with per-test timing' (#133) from wt/soul-runtime-reconcile into dev
El SDK CI - dev / build-and-test (push) Failing after 10m17s
2026-08-16 02:31:08 +00:00
bigmerge 4c3414072b Merge remote-tracking branch 'origin/dev' into wt/soul-runtime-reconcile 2026-08-15 21:30:52 -05:00
will.anderson 0288024396 Merge pull request 'compiler: fix the quadratic — strlen() on every character access' (#132) from fix/compiler-quadratic-strlen into dev
El SDK CI - dev / build-and-test (push) Failing after 4m2s
2026-08-16 02:29:02 +00:00
Neuron 3e7ab07e82 test framework phase 1: forward decls, void-return fix, suite migration
El SDK CI - dev / build-and-test (pull_request) Failing after 10m4s
Completes the Phase 1 runner and migrates the 11 test files onto it.

- forward-declare the registry accessors in the test preamble; they are
  defined at the end of the unit but the El runner is compiled in between
- eltest.el: explicit trailing return in the void emit_* helpers, which
  otherwise lower to 'return println(...)' and fail to compile
- test files import runtime/eltest.el explicitly, using the language's own
  textual import mechanism rather than compiler-side auto-injection
- DESIGN.md 6.5: gate on allocation COUNT AND BYTES, not count alone

Verified: self-hosting fixpoint byte-identical (gen2 == gen3). 6 of 11
suites run and report per-test timing. The other 5 fail to COMPILE, and
fail identically under the committed compiler -- pre-existing breakage
this framework makes visible for the first time.
2026-08-15 21:28:30 -05:00
bigmerge a668062e38 Merge remote-tracking branch 'origin/dev' into wt/soul-runtime-reconcile 2026-08-15 21:24:03 -05:00
Neuron 24fac765a6 test framework phase 1: compile-time registry + El-side runner
Replace the hardcoded test harness main() with a generated static registry
and index-based accessors, and move all reporting into runtime/eltest.el.

The old harness inlined direct calls into main() and counted assertions in
two globals. That shape cannot report which test failed, how long any test
took, or whether a test ran at all -- a misspelled registration reported
success for a test that never executed.

- assertions record into per-test state instead of global counters
- registry table emitted at compile time; discovery strictly precedes
  execution, which is what later enables --list, filtering and sharding
- per-test wall timing on CLOCK_MONOTONIC, taken in C around the call
- runner in El: structured NDJSON events as source of truth, human output
  rendered from the same fields
2026-08-15 21:24:03 -05:00
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# El Test Framework — Design
**Status:** draft for review
**Author:** Neuron
**Date:** 2026-08-15
**Worktree:** `/Users/will/Development/neuron-technologies/el-worktrees/elc-memory-investigation`
---
## 0. The forcing requirement
We have a confirmed quadratic in `elc`. Peak memory in the old shipped binary and wall-clock in
the current source both grow as O(input²). We cannot fix it, because we cannot test it.
Everything in this document is downstream of one sentence: **a test framework must be able to fail
a build when an operation's growth curve degrades from linear to quadratic.**
That is not a nice-to-have bolted onto a correctness framework. It is the requirement that
determines the architecture. Correctness testing is the easy half.
Second-order requirement, learned the hard way tonight: **the framework must report per-test timing
by default.** The current framework prints `N passed, M failed` and nothing else. That is why a
3.58-second test file sat in the suite unnoticed. A framework that is structurally blind to time
cannot surface the defect class we most need to catch.
---
## 1. What exists today, measured
### 1.1 Two competing systems, neither complete
**System A — `lang/runtime/test.el`.** Manual registration, El-level.
**System B — the compiler's `test { }` block + `elc --test`.** Emits its own harness `main()`
with `__el_pass` / `__el_fail` globals (`codegen.el:3777-3796`).
They do not share a result model. Neither has timing. Both are in the tree.
### 1.2 Specific defects in System A
| Defect | Location | Consequence |
|---|---|---|
| All state as JSON strings in a global string-keyed map | `test.el` throughout | every assertion is `state_get``str_to_int``int_to_str``state_set` |
| Failure list appended by string slice + concat | `_test_json_append` | O(n²) in failure count |
| One OS thread spawned per test | `_test_run_one` via `__thread_create`/`__thread_join` | thread spawn per test, purely to get dispatch-by-name through dlsym |
| Manual registration pairing a string to a function name | `test_case(name, fn_name)` | typo ⇒ test silently never runs, suite still reports pass |
| Counters are assertion-level, global | `_test_pass_count` etc. | no per-test record exists at all |
| No timing, no structured output, no fixtures, no tags, no filtering, no parameterization, no benchmarks | — | — |
The registration defect is the serious one. It is not a slow framework, it is a framework that can
report success for tests that did not execute.
### 1.3 Measured cost structure
Per test file, current build model:
| Step | Time |
|---|---|
| `elc` compile `.el``.c` | 0.00s (small files) |
| **`cc` el_runtime.c → .o** | **0.14s** |
| `cc` test .c → .o | 0.02s |
| link | 0.02s |
> **STALE as of el #132 — re-measured 2026-08-16.** The `test_compiler` figure below was
> *entirely* the `strlen`-per-character quadratic, now fixed. Re-measured on the same host:
> **3.58s → 0.03s (119x)**, and the 422 KB compiler concatenation likewise compiles in 0.03s.
> The table is retained only as the historical record that motivated the gate. The remaining
> per-file cost is the redundant `el_runtime.c` rebuild, which §9's compile-once architecture
> addresses.
Per-file `elc` time across the existing suite:
| File | Bytes | elc time |
|---|---|---|
| `test_compiler` | 29,685 (+394 KB of imports) | **3.58s** |
| `string_test` | 18,545 | 0.01s |
| all other 9 files | 2.210 KB | 0.00s |
Two distinct defects in two distinct regimes:
1. **`test_compiler.el` imports all five compiler sources** — 394 KB in one translation unit. Its
3.58s is entirely the quadratic. It is the only file where the quadratic bites.
2. **Every other file's cost is 100% redundant `el_runtime.c` rebuilds** — 480 KB of identical C,
recompiled once per test file.
Neither is fixed by making the compiler faster. Both are fixed by the architecture below, and the
speedup is a by-product of building it correctly, not the goal.
### 1.4 The asset worth keeping
`codegen.el:3651-3652` already collects `test_names` / `test_c_names` — **the compiler already does
compile-time test discovery.** It then discards that registry into a hardcoded `main()`.
That registry is precisely the seam Go's `_testmain.go` and Rust's `test_main_static` are built on.
The mechanism we need is half-built and wired to the wrong thing.
---
## 2. Grounding — the common spine of excellent frameworks
Researched from primary sources: Go `testing`/`go test`, Rust `libtest`/Criterion, JUnit 5 Platform,
NUnit 3, JMH, Google Benchmark. Six invariants hold across all of them.
1. **A registry is built before execution**`(name, metadata, fn-ptr)` triples. Go generates it
from an AST scan; Rust synthesizes it in a compiler pass; JMH emits it as a build-time resource;
JUnit/NUnit build it reflectively. **Reflection is an implementation of the registry on runtimes
where it is cheap. It is never the architecture.**
2. **Discovery strictly precedes execution.** Every good capability — filtering, listing, counting,
sharding, IDE trees, re-run-failed-only, dry runs — is a consequence of this ordering.
3. **A hierarchy with stable, path-shaped unique IDs.** `TestFoo/subcase_2`. Selection is regex over
that path, one pattern per level.
4. **The framework is a prebuilt library; only the entry point is generated.** "Compile once, link
many" is always: framework archive compiled once + a small generated table + one
`MainStart(deps, registry)` call. Nobody recompiles the harness per test file.
5. **Execution emits an event stream; reporters are downstream renderers.** Human text, NDJSON,
JUnit XML, TAP are all transforms of one event stream. Go's one architectural mistake is doing
this backwards — `test2json` parses human output, and has shipped bugs when user output contains
`--- PASS:`.
6. **A dependency-injection seam at the boundary.** Go's `testdeps.TestDeps` exists so `testing`
can avoid importing `regexp`, profilers, and coverage. The execution core knows nothing about
output formats.
---
## 3. Architecture
### 3.1 The seam
```
┌─────────────────────────────────────────────────────────────┐
│ user code: foo.el with test { } / bench { } blocks │
└───────────────────────────┬─────────────────────────────────┘
│ elc --test
┌─────────────────────────────────────────────────────────────┐
│ generated C (per suite, tiny): │
│ __el_test_fn_0 .. _N lowered test/bench bodies │
│ __el_registry[] static table: name/kind/file/ │
│ line/tags/sizes/expected-O │
│ __el_dispatch(i) generated switch → body │
│ main() { return el_test_main(argc, argv); } │
└───────────────────────────┬─────────────────────────────────┘
│ cc + link (registry only)
┌─────────────────────────────────────────────────────────────┐
│ libeltest.a — PREBUILT ONCE │
│ • el_runtime.o (the 480 KB, compiled once, ever) │
│ • eltest.o the runner, WRITTEN IN EL │
│ discovery view · filtering · execution · fixtures · │
│ timing · benchmark harness · curve fitting · reporters │
└─────────────────────────────────────────────────────────────┘
```
The framework is written in El, compiled to C once, archived. Per-suite compilation touches only
the generated registry. This is Go's model, and it is strictly better for us than Go's because we
own the compiler and already have the AST — no separate source-scanning pass is needed.
### 3.2 Why the runner is in El and the registry is in C
El has no closures and no first-class function pointers. The registry must therefore hold C function
pointers, and it is generated C.
The runner stays in El and reaches the registry through a small builtin surface — indices, not
pointers:
```
__el_reg_count() -> Int
__el_reg_name(i) -> String
__el_reg_file(i) -> String
__el_reg_line(i) -> Int
__el_reg_kind(i) -> Int // 0=test 1=bench
__el_reg_tags(i) -> Int
__el_reg_sizes(i) -> String // JSON array, empty for tests
__el_reg_expect(i) -> Int // complexity class enum, 0 = none
__el_reg_invoke(i) -> Int // runs the body via the generated switch
```
Nine builtins. Everything else — filtering, lifecycle, statistics, curve fitting, all reporters —
is El. That satisfies "written in El" without pretending El can do something it cannot.
### 3.3 Result model
The unit is a **result record**, not a counter:
```
TestResult {
id String // slash path: "parser/handles_empty_input/case_3"
file String
line Int
status Status // Pass | Fail | Error | Skip
duration Int // nanoseconds, ALWAYS populated
message String // assertion detail: expected vs actual
output String // captured stdout/stderr for this test
assertions Int
}
```
`Fail` = an assertion failed. `Error` = unexpected crash/abort. This distinction is load-bearing —
every CI consumer depends on it, and the JUnit XML schema encodes it as distinct elements.
---
## 4. Authoring surface
### 4.1 Tests
`test { }` already exists. Keep it. Add subtests and hierarchy:
```el
test "parser/empty input" {
assert_that(parse(""), is_err())
}
test "parser/table" {
for case in [["", 0], ["a", 1], ["a b", 2]] {
subtest(case[0]) {
assert_that(token_count(case[0]), equals(case[1]))
}
}
}
```
Subtest IDs compose as `parser/table/a_b`. Filtering is `--run 'parser/table/.*'`, one regex per
path segment, exactly as Go does.
**We do not build a parameterized-test annotation system.** Table-driven loops plus subtests subsume
`@ParameterizedTest`, `@MethodSource`, `@CsvSource`, and `TestCaseSource` entirely, at zero framework
surface. This is Go's single biggest ergonomic win over JUnit and NUnit.
### 4.2 Fixtures
Per-file and per-test only, plus a LIFO cleanup stack:
```el
setup_all { ... } // once per suite
setup { ... } // before each test
teardown { ... } // after each test
teardown_all { ... }
```
and inside a test, `cleanup { ... }` registering LIFO-ordered teardown.
**We do not build JUnit 5's extension SPI** — seventeen callback interfaces, hierarchical stores,
registration ordering rules. That complexity is the price of retrofitting a plugin ecosystem onto a
twenty-year-old reflective framework. Go's `t.Cleanup` covers roughly 90% of what `@AfterEach` is
used for at a fraction of the surface.
### 4.3 Assertions — constraint model
One entry point, composable constraint values (NUnit's model, which avoids the N² overload
explosion):
```el
assert_that(actual, equals(expected))
assert_that(xs, has_length(3))
assert_that(s, contains("foo").and(starts_with("bar")))
assert_that(f, is_within(0.01).of(3.14))
```
A constraint is a value with `apply_to(actual) -> ConstraintResult`, and the result knows how to
describe its own failure. Custom constraints are ordinary user types.
**Every failure message must name file, line, the expression text, and both values.** We capture
expression source text at compile time — we have the AST, so we can do this better than any
runtime-introspection framework.
Legacy `assert_true` / `assert_eq` / etc. stay as thin wrappers for migration.
---
## 5. Benchmarks
### 5.1 The loop
Adopt `b.Loop()`, not `b.N`. Go spent fifteen years on `b.N` before concluding `b.Loop` was right;
we skip that.
```el
bench "str_concat" {
let s = make_input(bench_n())
for bench_loop() {
black_box(str_concat(s, "x"))
}
}
```
Three properties that make this the correct choice for a C target:
1. **The timer auto-resets on first call**, so setup above the loop is excluded *by construction*
rather than by the author remembering `ResetTimer`.
2. **`N` is hidden**, so it cannot be misused.
3. **The harness owns the loop shape**, which lets us insert an optimization barrier the C compiler
cannot see through. `black_box(v)` lowers to `asm volatile("" :: "r"(&v) : "memory")`. Since we
emit a single translation unit, dead-code elimination of a benchmark body is a live hazard —
this is our version of JMH's `Blackhole` problem, solved in the harness rather than delegated to
the user.
### 5.2 Iteration scaling
Use Go's `predictN` heuristics verbatim. They are battle-tested and cheap:
```
n = goal_ns * prev_iters / prev_ns // multiply before divide — precision on sub-ns ops
n += n / 5 // 20% headroom, overshoot rather than re-loop
n = min(n, 100 * last) // never grow more than 100× per step
n = max(n, last + 1) // guarantee forward progress
n = min(n, 1_000_000_000) // hard ceiling
```
Report `n` rounded to 1/2/3/5 × 10ᵏ so runs are comparable.
### 5.3 Sampling
Criterion's shape, because it is correct near timer resolution:
- **Warmup**: iteration counts 1, 2, 4, 8… until cumulative time exceeds the warmup budget.
- **Measurement**: collect `sample_size` samples at iteration counts `[d, 2d, 3d, …, Nd]`.
- **Estimate**: slope of a linear regression of iteration-count vs elapsed time. The intercept
absorbs fixed overhead.
- **Time whole samples, never individual iterations.** This is the single most important detail —
it defeats timer-resolution error on nanosecond operations.
Outliers classified by modified Tukey (±1.5 IQR mild, ±3 IQR severe), **reported but retained**.
---
## 6. Complexity gating — the centerpiece
This is the part that makes the quadratic fixable, and the part nobody in the mainstream has
finished. Google Benchmark's `Complexity()` fits the curve and *reports* it. We declare it and
**gate** on it.
### 6.1 Surface
```el
bench "elc_compile" over n in [16, 32, 64, 128, 256, 512, 1024] expect O(n) {
let src = synth_source(bench_n())
for bench_loop() { black_box(compile(src)) }
}
```
Alternative with no new syntax, if the parser change is judged too invasive — `bench_sizes([...])`
and `bench_expect("O(n)")` as calls inside the block. **Recommendation: declarative.** Runtime calls
mean `--list` cannot show the invariant without executing, which breaks the discovery-precedes-
execution invariant from §2.
### 6.2 Fitting
Per Google Benchmark `src/complexity.cc`. For candidate curves
`{O(1), O(log n), O(n), O(n log n), O(n²), O(n³)}`, one-parameter least squares, no intercept:
```
coef = Σ(tᵢ · gᵢ) / Σ(gᵢ²)
rms = sqrt( Σ(tᵢ coef·gᵢ)² / k ) / mean(t) // normalized
```
Best fit = lowest normalized RMS. User-supplied lambda curves also supported.
### 6.3 Gate logic
1. **FAIL** if the best-fit curve is strictly worse than declared, ordering
`O(1) < O(log n) < O(n) < O(n log n) < O(n²) < O(n³)`. Print the fitted coefficient and the full
per-size table.
2. **FAIL** if the declared curve's normalized RMS exceeds a threshold (start at 0.10). This catches
the case where *no* candidate fits — noise, a cache cliff, or a phase change. Report
`INDETERMINATE` honestly rather than gating on garbage.
3. **WARN** if the best fit is strictly better than declared — either an optimization landed and the
annotation should tighten, or the sweep is too narrow to expose real behaviour.
4. **REFUSE to gate** on fewer than 5 distinct sizes spanning under 2 decades, geometrically spaced.
Say so loudly rather than producing a meaningless fit.
### 6.4 Why gate on the exponent, not wall-clock
- **Machine-independent.** The fitted exponent is a property of the algorithm; the coefficient is a
property of the machine. Gating on the exponent makes CI hardware heterogeneity, noisy neighbours,
and thermal throttling irrelevant — they scale `coef`, not `g`.
- **No stored baseline.** No artifact storage, no golden-file drift. The invariant lives in the
source next to the code and is reviewed in the same PR.
- **It catches the failure mode that actually ships.** An O(n) lookup inside an O(n) loop is
invisible at n=100 in a unit test and catastrophic at n=100,000 in production. Constant-factor
regressions are annoying. Complexity regressions are outages. Ours was a 27 GB outage.
### 6.5 The deterministic gate — the one that would have caught us
Wall-clock needs statistics. **Allocation counts do not.** They are perfectly deterministic.
> **Correction, 2026-08-16 — count alone is NOT sufficient. Gate on BOTH count and bytes.**
>
> Measured against two El programs, one allocating once per item and one rebuilding its
> accumulator each iteration:
>
> | n | linear allocs / bytes | quadratic allocs / bytes |
> |---|---|---|
> | 100 | 100 / 290 | 100 / 5,150 |
> | 200 | 200 / 690 | 200 / 20,300 |
> | 400 | 400 / 1,490 | 400 / 80,600 |
> | 800 | 800 / 3,090 | 800 / 321,200 |
>
> The quadratic program's allocation **count is exactly linear** — 100/200/400/800, identical to
> the healthy program. A count-only gate passes it clean. **Bytes** catch it: each doubling of n
> quadruples bytes (ratios 3.94, 3.97, 3.99 → 4.0 = O(n²)) where the linear program converges
> on 2.0.
>
> This is precisely elc's own defect shape — a copy-on-write accumulator reallocating once per
> pass (count linear) into a proportionally larger buffer (bytes quadratic).
>
> Therefore `expect allocs O(n)` **fits count and bytes independently and fails if EITHER exceeds
> the declared curve**, reporting which signal broke. "count linear, bytes quadratic" is a precise,
> directly actionable diagnosis.
>
> **`el_peak_rss()` is CONTEXT ONLY — never gate on it.** It is perturbed by the allocator and by
> the page cache. Allocation volume is the invariant; RSS and malloc/free churn are merely the two
> surfaces it shows on. The old shipped compiler paid the same quadratic in RSS that the rebuilt
> one pays in churn.
>
> **Measure rate, not level.** A guard reading swap *level* saw 97% on a thrashing host and 97% on
> a healthy one; only *rate* separated them. A growth exponent is a rate; a single measurement is
> a level. That is why the gate fits a curve across a sweep instead of comparing one number to a
> threshold.
> **Second correction, same day — THE ALLOCATION GATE ALONE WOULD HAVE MISSED THE REAL BUG.**
>
> el #132 found the actual elc quadratic: `strlen()` called inside `str_char_code()` and
> `str_slice()`, so the lexer rescanned the remaining input on every character. Pure CPU.
> **Zero allocation.** `str_char_code` is a bounds check and an index — it allocates nothing.
>
> Measured on three controlled specimens (`lang/.work/fitprobe.el`), growth ratio per doubling of
> n across n = 200/400/800/1600:
>
> | specimen | allocs | bytes | time | what it proves |
> |---|---|---|---|---|
> | `linear` — one alloc per item | 2.00 2.00 2.00 → **O(n)** | 2.16 2.07 2.23 → **O(n)** | 0.83 2.00 2.05 → **O(n)** | clean baseline |
> | `accum` — rebuilds accumulator | 2.00 2.00 2.00 → **O(n)** | 3.97 3.99 3.99 → **O(n²)** | noisy | count misses, **bytes catches** |
> | `compute` — n scans over n chars | 0 → **FLAT** | 0 → **FLAT** | 3.93 4.01 3.96 → **O(n²)** | **both alloc signals blind; only time catches** |
>
> `compute` is el #132's shape exactly. A gate fitting only allocation count and bytes classifies
> it as FLAT and passes it. **The gate as originally specified would not have caught the defect it
> was created for.**
>
> Therefore the gate fits **THREE** signals and fails if ANY exceeds its declared curve:
>
> ```
> bench "elc_compile" over n in [...] expect time O(n) allocs O(n) bytes O(n) { ... }
> ```
>
> - **allocs (count)** — deterministic, zero-noise. Catches per-item allocation growth.
> - **allocs (bytes)** — deterministic, zero-noise. Catches accumulator-rebuild quadratics that
> count cannot see.
> - **time** — noisy, needs the sweep and statistics. The ONLY signal that sees pure-compute
> complexity regressions. Gate on the fitted *exponent*, never on absolute duration, so CI
> hardware variance scales the coefficient and leaves the classification intact.
>
> The deterministic signals remain preferable where they apply — they need no statistics and are
> correct on the first run. They are simply not sufficient.
>
> **`black_box` is mandatory, and consuming the result is NOT enough.** The first version of
> `compute` accumulated `total + 1` in a nested loop and reported **0 µs at every n** while
> returning a numerically correct n². Clang recognised the idiom and closed the loop to a
> multiply. Feeding the result into output did not prevent it. Only making the inner operation an
> opaque external call restored the real curve. A benchmark harness that trusts the user to defeat
> the optimiser will silently measure nothing — and report success while doing it.
Instrument the runtime with allocation counters and fit *those* against n instead of time:
```el
bench "elc_compile" over n in [...] expect O(n) allocs O(n) { ... }
```
Zero noise, zero statistics, always gateable, correct on the first run on any machine. Go reports
`allocs/op` and `B/op`; **nobody fits them against n.** That is an open opportunity and it is exactly
our bug: elc's defect is quadratic *allocation volume*, which the old binary paid in RSS and the
current source pays in malloc/free churn.
An `expect allocs O(n)` assertion on `elc`'s compile path would have failed the build the day the
quadratic was introduced.
Required runtime additions: `__el_alloc_count()`, `__el_alloc_bytes()`, `__el_peak_rss()`.
### 6.6 Constant-factor gate (secondary, opt-in)
Mann-Whitney U at α = 0.05, noise floor 1%, medians with 95% CIs, `~` for not-significant. Requires
`--count >= 9`. Off by default on CI; opt-in per benchmark.
**Exit nonzero on regression.** Both benchstat and Criterion always exit 0, which is why every shop
using them wrote a wrapper. We do not repeat that omission.
---
## 7. Output
**Structured events are the source of truth.** Human text is rendered from them. We do not repeat
Go's parse-the-human-output design.
Event stream, NDJSON, one object per line, streamed live:
```json
{"time":"...","action":"run","test":"parser/empty"}
{"time":"...","action":"output","test":"parser/empty","output":"..."}
{"time":"...","action":"pass","test":"parser/empty","elapsed":0.0031}
{"time":"...","action":"bench","test":"str_concat","n":1024,"ns_op":41.2,"allocs_op":3,"bigo":"N","rms":0.03}
```
Renderers, all downstream and pluggable:
| Format | Flag | Use |
|---|---|---|
| Human | default | terminal, **per-test duration always shown** |
| NDJSON | `--json` | tooling, history, flaky detection |
| JUnit XML | `--junit-xml=PATH` | every CI system on earth |
| TAP | `--tap` | optional |
JUnit XML per the de-facto schema: `testsuites``testsuite``testcase`, with `time` in seconds
as a decimal, `file`/`line` attributes, and `failure` vs `error` vs `skipped` as distinct child
elements. Absence of a child element means pass. Emit `<testsuites>` even for a single suite, and
parse both shapes on input.
---
## 8. CLI
```
--list print the registry, run nothing
--list-json machine-readable registry
--run PATTERN slash-separated regex per path segment
--tag EXPR tag expression: fast & !slow
--shard I/N deterministic sharding for CI parallelism
--count N repetitions, for statistics
--bench PATTERN run benchmarks (off by default in test runs)
--benchtime DUR per-benchmark time budget
--junit-xml PATH
--json
--isolate re-exec per test on crash, so one SIGSEGV doesn't lose the run
--timeout DUR
--fail-fast
```
`--list` / `--list-json` / `--shard` cost roughly thirty lines because the registry already exists
before `main` does anything. That is the dividend of discovery-precedes-execution.
---
## 9. Build model
```
# once, ever (or when the runtime/framework changes):
cc -c el_runtime.c -o el_runtime.o
elc eltest.el > eltest.c && cc -c eltest.c -o eltest.o
ar rcs libeltest.a el_runtime.o eltest.o
# per suite:
elc --test foo_test.el > foo_test.c # registry + bodies only
cc foo_test.c libeltest.a -o foo_test
```
The 0.14s × N of redundant runtime rebuilds disappears — not because we optimized it, but because
one-runner-over-many-suites requires compile-once-link-many as a structural precondition.
---
## 10. Bootstrap and self-hosting
The framework's own tests are `test { }` blocks run by the framework. Same fixpoint discipline the
compiler already applies to itself.
1. Build the framework using the *existing* harness for its first tests (stage 0).
2. Rebuild the framework's tests as `test { }` blocks run by the new runner (stage 1).
3. Verify stage 1 reports identical results to stage 0.
4. From then on, the framework is tested by itself.
A framework that cannot run its own suite is not evidence of anything. This is a correctness proof,
not a claim.
---
## 11. Explicitly not building
| Rejected | Why |
|---|---|
| Naming-convention discovery (`fn test_foo`) | `test { }` is a real declaration. Go's `TestXxx` exists only because Go had no better hook — and it needs a heuristic to avoid matching `TesticularCancer`. |
| Reflection or symbol-table scanning | Slow, fragile under LTO/strip/dead-strip, and unnecessary when we own the compiler. |
| Parsing human output into structure | Go's `test2json` is its one clear architectural mistake. |
| JUnit 5's extension SPI | Seventeen callback interfaces to retrofit plugins onto a reflective framework. Not our problem. |
| `@ParameterizedTest` machinery | Table-driven loops + subtests subsume it at zero surface. |
| NUnit's out-of-process agents | They bridge CLR versions and AppDomains. We emit one native binary. Keep `--isolate` as crash fallback only. |
| JMH-style forking by default | Forks exist because JIT profiles are per-process. AOT C has no such state. Keep `--fork` available, not default. |
| Exit 0 on regression | benchstat and Criterion both do this, and every user writes a wrapper. |
| Dynamic runtime test registration | Breaks `--list`, sharding, and individual selection. Registry stays static. |
---
## 12. Phasing
| Phase | Content | Gate |
|---|---|---|
| **1** | Registry emission in codegen; 9 builtins; `el_test_main` skeleton in El; result records; per-test timing; human + NDJSON output | existing 11 test files pass, with timing |
| **2** | `libeltest.a` build model; subtests; filtering; `--list`; fixtures; constraint assertions; JUnit XML | suite runs in one binary; runtime compiled once |
| **3** | `bench { }`, `bench_loop`, `black_box`, `predictN`, Criterion sampling | benchmarks produce stable ns/op |
| **4** | Allocation counters; complexity fitting; `expect O(...)` gate | **an `expect allocs O(n)` benchmark on `elc` fails on the current quadratic** |
| **5** | Migrate both legacy systems; delete `runtime/test.el`; self-host | framework runs its own suite |
Phase 4 is the deliverable that matters. Phases 13 exist to make it possible.
---
## 13. Open questions for review
1. **Declarative `over n in [...] expect O(...)` syntax vs runtime calls.** I recommend declarative
(§6.1) so `--list` can show invariants without executing. It costs parser work. Your call.
2. **`bench { }` as a new block form** — parallel to `test { }`, or a modifier on it?
3. **Scope of the constraint model.** Full composable constraints, or start with a flat assertion set
and add constraints later? Full model is more surface but avoids a second migration.
4. **Does `runtime/test.el` get deleted or kept as a deprecated shim?** I lean delete — two systems
is how we got here.
5. **Where does `libeltest.a` live** in the tree, and does `epm` need to know about it?
6. **Allocation counters in `el_seed.c` or `el_runtime.c`?** AGENTS.md says `el_seed.c` is the sole
C dependency and hand-maintained; counters are OS-boundary-adjacent but not OS calls.
7. **Is per-test timing enough, or do we want per-*assertion* timing** for finding slow helpers?
---
## 14. What this document is not
This is a design, not a measurement. Every performance claim about the *current* system in §1 is
measured and reproducible in this worktree. Every claim about the *proposed* system is a prediction.
None of it is verified until Phase 1 runs and Phase 4 fails a build on the real quadratic.
+143 -20
View File
@@ -862,10 +862,23 @@ fn cg_expr(expr: Map<String, Any>) -> String {
// arithmetic BinOp (or vice-versa). Without this check the
// fallthrough to str_eq produces str_eq(int_value, int_value)
// which reads the integer as a char* and segfaults.
// EITHER side provably Int is enough. Requiring BOTH meant a call
// whose return type codegen cannot infer poisoned the operator:
// getint(5) == a -> str_eq(getint(5), a)
// even with `a` declared Int. str_eq then reads an integer as a
// char* and segfaults. Only an integer LITERAL on one side forced
// the numeric form, so the bug was invisible in the common case.
//
// Loosening to OR is strictly safer: when one side is a known Int,
// str_eq is always wrong (it dereferences that int), while numeric
// comparison is at worst a wrong answer on an already ill-typed
// program. When neither side is Int nothing changes, so string
// comparison is untouched.
if is_int_expr(left) {
if is_int_expr(right) {
return "(" + left_c + " == " + right_c + ")"
}
return "(" + left_c + " == " + right_c + ")"
}
if is_int_expr(right) {
return "(" + left_c + " == " + right_c + ")"
}
// Float literal or negative float literal: use plain == (bit-equal
// el_val_t comparison). This handles `r0 == 3.0`, `neg == -3.0`, etc.
@@ -921,10 +934,12 @@ fn cg_expr(expr: Map<String, Any>) -> String {
}
// Same mixed Ident/BinOp fix as EqEq: use is_int_expr to detect
// integer-typed operands before falling through to !str_eq.
// Either side Int is enough see the EqEq note above.
if is_int_expr(left) {
if is_int_expr(right) {
return "(" + left_c + " != " + right_c + ")"
}
return "(" + left_c + " != " + right_c + ")"
}
if is_int_expr(right) {
return "(" + left_c + " != " + right_c + ")"
}
// Float-typed operands use plain != (bit-equal comparison).
if is_float_expr(left) {
@@ -1495,6 +1510,11 @@ fn cg_stmt(stmt: Map<String, Any>, indent: String, declared: [String]) -> [Strin
if str_eq(ltype, "Int") {
add_int_name(name)
}
// Same as params: Bool is an int in the value model. Without this a
// `let ok: Bool = ...` compared to another Bool lowered to str_eq.
if str_eq(ltype, "Bool") {
add_int_name(name)
}
if str_eq(ltype, "Float") {
add_float_name(name)
}
@@ -1705,9 +1725,13 @@ fn cg_stmt(stmt: Map<String, Any>, indent: String, declared: [String]) -> [Strin
} else {
let c_msg = "EL_STR_PTR(" + cg_expr(msg_node) + ")"
}
// Assertions record into PER-TEST state, not global counters. The test
// is the unit of result; a global pass/fail tally cannot say which test
// failed or whether a test ran at all. Reporting is the runner's job
// nothing is printed here.
emit_line(indent + "if (!(" + c_cond + ")) {")
emit_line(indent + " __el_test_fail(__el_cur_test, " + c_msg + "); __el_fail++;")
emit_line(indent + "} else { __el_pass++; }")
emit_line(indent + " __el_test_fail(" + c_msg + ");")
emit_line(indent + "} else { __el_cur_asserts++; }")
return declared
}
@@ -2602,6 +2626,17 @@ fn builtin_arity(name: String) -> Int {
// LSP seed primitives
if str_eq(name, "__read_n") { return 1 }
if str_eq(name, "__print_raw") { return 1 }
// Test-registry accessors. These are not runtime builtins they are
// GENERATED into the same translation unit by the --test path below, one
// set per test binary. They are declared here so the El-side runner in
// runtime/eltest.el can call them with a known arity.
if str_eq(name, "__el_reg_count") { return 0 }
if str_eq(name, "__el_reg_name") { return 1 }
if str_eq(name, "__el_reg_invoke") { return 1 }
if str_eq(name, "__el_reg_last_ns") { return 0 }
if str_eq(name, "__el_reg_msg") { return 0 }
if str_eq(name, "__el_reg_asserts") { return 0 }
if str_eq(name, "__el_opt_json") { return 0 }
// String
if str_eq(name, "el_str_concat") { return 2 }
if str_eq(name, "str_eq") { return 2 }
@@ -2872,6 +2907,7 @@ fn builtin_arity(name: String) -> Int {
if str_eq(name, "el_alloc_count") { return 0 }
if str_eq(name, "el_alloc_bytes") { return 0 }
if str_eq(name, "el_peak_rss") { return 0 }
if str_eq(name, "el_black_box") { return 1 }
if str_eq(name, "engram_neighbors_json") { return 3 }
if str_eq(name, "engram_activate_json") { return 2 }
if str_eq(name, "engram_stats_json") { return 0 }
@@ -3097,6 +3133,15 @@ fn build_int_names_for_params(params: [Map<String, Any>]) -> Bool {
if str_eq(ptype, "Int") {
add_int_name(pname)
}
// Bool is an integer in the value model (type_to_c maps Bool -> "int";
// el_runtime.h: "Bool -> el_val_t (0 = false, nonzero = true)"), but
// Bool names were registered nowhere. So `cond == want` between two
// Bool params fell through to str_eq and dereferenced 0 or 1 as a
// char* an immediate segfault. Track them as int-like, which is what
// they are.
if str_eq(ptype, "Bool") {
add_int_name(pname)
}
if str_eq(ptype, "Float") {
add_float_name(pname)
}
@@ -4116,13 +4161,36 @@ fn codegen_streaming(tokens: [Any], sigs: [Map<String, Any>], source: String) ->
// Emit test harness preamble (counters, fail printer) when in test mode.
if test_is_mode {
emit_line("#include <stdio.h>")
emit_line("#include <string.h>")
emit_line("#include <time.h>")
emit_blank()
emit_line("static int __el_pass = 0, __el_fail = 0;")
// Per-test result state. Reset by __el_reg_invoke before each test, so
// every test gets its own record rather than contributing to a global
// tally. The first failure message is retained; later ones only bump
// the count, which keeps the common case allocation-free.
emit_line("static int __el_cur_fails = 0;")
emit_line("static int __el_cur_asserts = 0;")
emit_line("static char __el_cur_msg[512] = \"\";")
emit_line("static const char *__el_cur_test = \"(none)\";")
emit_line("static void __el_test_fail(const char *test, const char *msg) {")
emit_line(" fprintf(stderr, \"FAIL %-40s %s\\n\", test, msg);")
emit_line("static void __el_test_fail(const char *msg) {")
emit_line(" if (__el_cur_fails == 0 && msg) {")
emit_line(" snprintf(__el_cur_msg, sizeof __el_cur_msg, \"%s\", msg);")
emit_line(" }")
emit_line(" __el_cur_fails++; __el_cur_asserts++;")
emit_line("}")
emit_blank()
// Forward declarations for the registry accessors. The definitions are
// emitted at the END of the unit (they reference the test functions,
// which do not exist yet at this point), but the El-side runner is
// compiled in between and calls them so it needs the prototypes here.
emit_line("el_val_t __el_reg_count(void);")
emit_line("el_val_t __el_reg_name(el_val_t i);")
emit_line("el_val_t __el_reg_invoke(el_val_t i);")
emit_line("el_val_t __el_reg_last_ns(void);")
emit_line("el_val_t __el_reg_msg(void);")
emit_line("el_val_t __el_reg_asserts(void);")
emit_line("el_val_t __el_opt_json(void);")
emit_blank()
}
// Streaming parse-emit loop.
@@ -4318,17 +4386,72 @@ fn codegen_streaming(tokens: [Any], sigs: [Map<String, Any>], source: String) ->
el_release(sigs)
let test_arena_mark: Any = el_arena_push()
let tn: Int = native_list_len(test_c_names)
// Generated test registry
// Discovery happens HERE, at compile time. The runner never searches
// for tests; it walks this table. That ordering — discovery strictly
// before execution is what makes --list, filtering, sharding and
// per-test reporting possible later, and it is why the old harness
// (which inlined direct calls into main) could not have any of them.
emit_line("typedef void (*__el_test_fp)(void);")
emit_line("typedef struct { const char *name; __el_test_fp fn; } __el_test_entry;")
emit_line("static const __el_test_entry __el_registry[] = {")
let ri: Int = 0
while ri < tn {
let r_name: String = native_list_get(test_names, ri)
let r_cfn: String = native_list_get(test_c_names, ri)
emit_line(" { \"" + c_escape(r_name) + "\", " + r_cfn + " },")
let ri = ri + 1
}
// Trailing sentinel keeps the array non-empty when a file declares no
// tests (a zero-length array is not valid C).
emit_line(" { 0, 0 }")
emit_line("};")
emit_line("static const int __el_registry_n = " + int_to_str(tn) + ";")
emit_blank()
emit_line("static long long __el_last_ns = 0;")
emit_line("static int __el_opt_json_v = 0;")
emit_blank()
// Index-based accessors
// El has no function pointers, so the runner works purely in indices.
// This is the whole seam between generated C and the El-side runner.
emit_line("el_val_t __el_reg_count(void) { return (el_val_t)(int64_t)__el_registry_n; }")
emit_line("el_val_t __el_reg_name(el_val_t i) {")
emit_line(" int64_t k = (int64_t)i;")
emit_line(" if (k < 0 || k >= __el_registry_n) return EL_STR(\"\");")
emit_line(" return EL_STR(__el_registry[k].name);")
emit_line("}")
// Timing is taken immediately around the call, in C, on the MONOTONIC
// clock never the wall clock, which can step backwards under NTP.
emit_line("el_val_t __el_reg_invoke(el_val_t i) {")
emit_line(" int64_t k = (int64_t)i;")
emit_line(" if (k < 0 || k >= __el_registry_n) return 0;")
emit_line(" __el_cur_fails = 0; __el_cur_asserts = 0; __el_cur_msg[0] = '\\0';")
emit_line(" __el_cur_test = __el_registry[k].name;")
emit_line(" struct timespec _t0, _t1;")
emit_line(" clock_gettime(CLOCK_MONOTONIC, &_t0);")
emit_line(" __el_registry[k].fn();")
emit_line(" clock_gettime(CLOCK_MONOTONIC, &_t1);")
emit_line(" __el_last_ns = (long long)(_t1.tv_sec - _t0.tv_sec) * 1000000000LL")
emit_line(" + (long long)(_t1.tv_nsec - _t0.tv_nsec);")
emit_line(" return (el_val_t)(int64_t)__el_cur_fails;")
emit_line("}")
emit_line("el_val_t __el_reg_last_ns(void) { return (el_val_t)(int64_t)__el_last_ns; }")
emit_line("el_val_t __el_reg_msg(void) { return EL_STR(__el_cur_msg); }")
emit_line("el_val_t __el_reg_asserts(void) { return (el_val_t)(int64_t)__el_cur_asserts; }")
emit_line("el_val_t __el_opt_json(void) { return (el_val_t)(int64_t)__el_opt_json_v; }")
emit_blank()
// main() delegates to the El-side runner. Everything above this line is
// generated glue; all reporting logic lives in runtime/eltest.el.
emit_line("int main(int _argc, char **_argv) {")
emit_line(" el_runtime_init_args(_argc, _argv);")
let ti: Int = 0
let tn: Int = native_list_len(test_c_names)
while ti < tn {
let tc_name: String = native_list_get(test_c_names, ti)
emit_line(" " + tc_name + "();")
let ti = ti + 1
}
emit_line(" printf(\"%d passed, %d failed\\n\", __el_pass, __el_fail);")
emit_line(" return __el_fail;")
emit_line(" for (int _i = 1; _i < _argc; _i++) {")
emit_line(" if (strcmp(_argv[_i], \"--json\") == 0) __el_opt_json_v = 1;")
emit_line(" }")
emit_line(" return (int)(int64_t)el_test_main();")
emit_line("}")
el_arena_pop(test_arena_mark)
el_release(test_names)
+16
View File
@@ -419,6 +419,22 @@ fn resolve_imports(src_path: String) -> String {
if !str_eq(already, "") { return "" }
state_set(seen_key, "1")
// A missing file must be a hard error, never an empty string.
//
// fs_read returns "" both for "file is empty" and "file does not exist", and
// this function used the value without distinguishing them. So a broken
// import path a typo, a moved file, a relative path resolved from the
// wrong working directory compiled CLEANLY: exit 0, empty stderr, and a
// program silently missing everything it imported. Observed 2026-08-15:
// eleven consecutive "successful" compiles that had included no runtime at
// all, and a wrong conclusion drawn from them before anyone noticed.
//
// Missing dependency, confident success. fs_exists separates the two cases,
// so a genuinely empty file still resolves to "" and is fine.
if !fs_exists(src_path) {
println("elc: cannot resolve import: " + src_path)
exit_program(1)
}
let source: String = fs_read(src_path)
let dir: String = dirname_of(src_path)
let lines: [String] = str_split(source, "\n")
+51 -4
View File
@@ -476,12 +476,14 @@ typedef struct {
static ElList* list_alloc(int64_t cap) {
if (cap < 4) cap = 4;
ElList* lst = malloc(sizeof(ElList));
_el_alloc_count++; _el_alloc_bytes += sizeof(ElList);
if (!lst) { fputs("el_runtime: out of memory\n", stderr); exit(1); }
lst->hdr.magic = EL_MAGIC_LIST;
lst->hdr.refcount = 1;
lst->length = 0;
lst->capacity = cap;
lst->elems = malloc((size_t)cap * sizeof(el_val_t));
_el_alloc_count++; _el_alloc_bytes += (size_t)cap * sizeof(el_val_t);
if (!lst->elems) { fputs("el_runtime: out of memory\n", stderr); exit(1); }
return lst;
}
@@ -531,6 +533,7 @@ el_val_t el_list_append(el_val_t listv, el_val_t elem) {
if (old->length >= old->capacity) {
int64_t new_cap = old->capacity > 0 ? old->capacity * 2 : 4;
el_val_t* grown = realloc(old->elems, (size_t)new_cap * sizeof(el_val_t));
_el_alloc_count++; _el_alloc_bytes += (size_t)new_cap * sizeof(el_val_t);
if (!grown) { fputs("el_runtime: out of memory\n", stderr); exit(1); }
old->elems = grown;
old->capacity = new_cap;
@@ -543,12 +546,14 @@ el_val_t el_list_append(el_val_t listv, el_val_t elem) {
int64_t new_cap = old->length + 1;
if (new_cap < 4) new_cap = 4;
ElList* fresh = malloc(sizeof(ElList));
_el_alloc_count++; _el_alloc_bytes += sizeof(ElList);
if (!fresh) { fputs("el_runtime: out of memory\n", stderr); exit(1); }
fresh->hdr.magic = EL_MAGIC_LIST;
fresh->hdr.refcount = 1;
fresh->length = old->length + 1;
fresh->capacity = new_cap;
fresh->elems = malloc((size_t)new_cap * sizeof(el_val_t));
_el_alloc_count++; _el_alloc_bytes += (size_t)new_cap * sizeof(el_val_t);
if (!fresh->elems) { fputs("el_runtime: out of memory\n", stderr); exit(1); }
if (old->length > 0) {
memcpy(fresh->elems, old->elems, (size_t)old->length * sizeof(el_val_t));
@@ -570,12 +575,14 @@ el_val_t el_list_clone(el_val_t listv) {
if (cap < old->length) cap = old->length;
if (cap < 4) cap = 4;
ElList* fresh = malloc(sizeof(ElList));
_el_alloc_count++; _el_alloc_bytes += sizeof(ElList);
if (!fresh) { fputs("el_runtime: out of memory\n", stderr); exit(1); }
fresh->hdr.magic = EL_MAGIC_LIST;
fresh->hdr.refcount = 1;
fresh->length = old->length;
fresh->capacity = cap;
fresh->elems = malloc((size_t)cap * sizeof(el_val_t));
_el_alloc_count++; _el_alloc_bytes += (size_t)cap * sizeof(el_val_t);
if (!fresh->elems) { fputs("el_runtime: out of memory\n", stderr); exit(1); }
if (old->length > 0) {
memcpy(fresh->elems, old->elems, (size_t)old->length * sizeof(el_val_t));
@@ -596,6 +603,7 @@ typedef struct {
static ElMap* map_alloc(int64_t cap) {
if (cap < 4) cap = 4;
ElMap* m = malloc(sizeof(ElMap));
_el_alloc_count++; _el_alloc_bytes += sizeof(ElMap);
if (!m) { fputs("el_runtime: out of memory\n", stderr); exit(1); }
m->hdr.magic = EL_MAGIC_MAP;
m->hdr.refcount = 1;
@@ -671,6 +679,7 @@ el_val_t el_map_set(el_val_t mapv, el_val_t keyv, el_val_t value) {
int64_t new_cap = m->count + 1;
if (new_cap < 4) new_cap = 4;
ElMap* fresh = malloc(sizeof(ElMap));
_el_alloc_count++; _el_alloc_bytes += sizeof(ElMap);
if (!fresh) { fputs("el_runtime: out of memory\n", stderr); exit(1); }
fresh->hdr.magic = EL_MAGIC_MAP;
fresh->hdr.refcount = 1;
@@ -5159,10 +5168,23 @@ el_val_t state_get(el_val_t key) {
if (!k) return el_wrap_str(el_strdup(""));
pthread_mutex_lock(&_state_mu);
StateEntry* e = state_find(k);
char* result = el_strdup_persist(e ? e->value : "");
/* ONE arena-tracked copy, taken under the lock.
*
* This used to make TWO copies: an el_strdup_persist temporary, then an
* arena-tracked copy of that temporary. The persistent one was never
* returned and never freed el_strdup_persist bypasses the arena by
* design ("state_set, engram internals"), so arena-pop could not reclaim
* it. Every state_get therefore leaked its full value string, permanently.
*
* The soul's awareness loop has 68 state_get call sites and ticks every
* 200ms; measured leak was ~1.1 MB per tick, about 19 GB/hour. It went
* unnoticed for as long as the soul restarted often enough to mask it.
*
* el_strdup tracks into the thread-local arena, which touches no shared
* state, so doing it under _state_mu is safe and removes the need for the
* temporary entirely. */
char* copy = el_strdup(e ? e->value : "");
pthread_mutex_unlock(&_state_mu);
/* wrap in arena-tracked copy for the caller's request lifetime */
char* copy = el_strdup(result);
return el_wrap_str(copy);
}
@@ -5240,7 +5262,12 @@ el_val_t str_to_float(el_val_t s) {
/* ── Math (Float-aware) ──────────────────────────────────────────────────── */
el_val_t math_sqrt(el_val_t f) { return el_from_float(sqrt(el_to_float(f))); }
el_val_t math_log(el_val_t f) { return el_from_float(log(el_to_float(f))); }
/* base-10, matching runtime/math.el's documented contract ("math_log — base-10
* logarithm") and el_seed.c's __log_f. This returned NATURAL log, so math_log
* and math_ln were the same function: log10(100) gave 4.605 instead of 2.
* Caught by tests/native/test_math.el on the new framework's first run the
* assertion existed all along, the suite just had no way to report it. */
el_val_t math_log(el_val_t f) { return el_from_float(log10(el_to_float(f))); }
el_val_t math_ln(el_val_t f) { return el_from_float(log(el_to_float(f))); }
el_val_t math_sin(el_val_t f) { return el_from_float(sin(el_to_float(f))); }
el_val_t math_cos(el_val_t f) { return el_from_float(cos(el_to_float(f))); }
@@ -18508,6 +18535,26 @@ el_val_t engram_pool_stats_json(void) {
el_val_t el_alloc_count(void) { return (el_val_t)(int64_t)_el_alloc_count; }
el_val_t el_alloc_bytes(void) { return (el_val_t)(int64_t)_el_alloc_bytes; }
/* el_black_box — optimisation barrier for benchmark bodies.
*
* WHY THIS IS NOT OPTIONAL. A benchmark whose result is unused is dead code,
* and CONSUMING THE RESULT IS NOT SUFFICIENT: clang recognises loop idioms and
* closes them to arithmetic. A nested `total = total + 1` loop measured at
* 0 microseconds for every n while returning a numerically correct n*n --
* the answer was right and the work never happened.
*
* That is the same failure shape as a test that never ran reporting pass. The
* harness must own the barrier rather than trusting the benchmark author to
* defeat the optimiser.
*
* The constraint "+r" forces the value through a register the compiler must
* treat as both read and written by opaque code; the "memory" clobber stops
* loads and stores being reordered across it or elided. Emits no instructions. */
el_val_t el_black_box(el_val_t v) {
__asm__ __volatile__("" : "+r"(v) : : "memory");
return v;
}
el_val_t el_peak_rss(void) {
struct rusage ru;
if (getrusage(RUSAGE_SELF, &ru) != 0) return (el_val_t)0;
+1
View File
@@ -1022,6 +1022,7 @@ el_val_t el_mem_check(void);
el_val_t el_alloc_count(void);
el_val_t el_alloc_bytes(void);
el_val_t el_peak_rss(void);
el_val_t el_black_box(el_val_t v);
/* Semantic retrieval surface. NOT interchangeable with engram_search_json,
* which is lexical by design — see the note at the definition. */
+256
View File
@@ -0,0 +1,256 @@
// runtime/elbench.el growth-curve classifier and complexity gate.
//
// Given a geometric sweep of input sizes and the measurements taken at each,
// classify the growth curve and decide whether it violates a declared bound.
//
// Why this exists
//
// Constant-factor regressions are annoying. Complexity regressions are outages.
// An O(n) lookup inside an O(n) loop is invisible at n=100 in a unit test and
// catastrophic at n=100000 in production. el #132 was exactly that: a strlen()
// inside a per-character accessor, quadratic, shipped for months.
//
// THREE signals, not one
//
// The gate fits time AND allocation-count AND allocation-bytes, and fails if
// ANY of them exceeds its declared curve. This is not belt-and-braces; each
// signal is blind to a real defect class the others catch:
//
// * A copy-on-write accumulator rebuilding its buffer allocates ONCE per
// iteration count is exactly linear while bytes go quadratic.
// Count alone passes it.
// * el #132's strlen-per-character is pure CPU and allocates NOTHING.
// Both allocation signals read FLAT. Only time catches it.
//
// The deterministic signals (count, bytes) are preferable where they apply:
// no statistics, correct on the first run, machine-independent. They are
// simply not sufficient.
//
// SCOPE LIMIT read this before trusting a flat curve
//
// The allocation counters track EL-LEVEL allocation only: strings, ElList and
// ElMap bodies, their backing arrays, copy-on-write clones, and the realloc
// growth path. malloc inside engram_*.c and inside libcurl is NOT counted.
//
// A flat allocation curve over a workload dominated by engram or HTTP calls is
// therefore NOT evidence of anything. It means "no El-level allocation growth",
// not "no allocation growth". Gate El-level complexity with this; do not read
// third-party memory behaviour into it.
//
// Classification method
//
// Sizes must form a geometric sweep (each n double the last). On such a sweep
// the ratio between consecutive measurements IS the growth exponent, directly:
//
// O(1) -> 1.0 O(log n) -> ~1.1 O(n) -> 2.0
// O(n log n) -> ~2.2 O(n^2) -> 4.0 O(n^3) -> 8.0
//
// DEVIATION FROM DESIGN.md 6.2, stated plainly: that section specified Google
// Benchmark's one-parameter least-squares fit over candidate curves. This uses
// consecutive ratios instead. The sweep is mandated geometric either way, and
// on a geometric sweep ratios are directly interpretable and need no floating
// point. The cost is weaker separation between O(n) and O(n log n), which is
// reported honestly as an ambiguous band rather than guessed at. Least-squares
// remains the better answer if that band ever needs to be resolved.
//
// All arithmetic is fixed-point, scaled by 1000 ("milli-ratio"), so a ratio of
// 2.0 is 2000. El values are int64; this avoids float-in-list handling.
// Curve identifiers. Ordered by growth the ordering IS the comparison used
// by the gate, so an index comparison decides "worse than declared".
// 0 = O(1) 1 = O(log n) 2 = O(n) 3 = O(n log n) 4 = O(n^2) 5 = O(n^3)
fn elb_curve_name(c: Int) -> String {
if c == 0 { return "O(1)" }
if c == 1 { return "O(log n)" }
if c == 2 { return "O(n)" }
if c == 3 { return "O(n log n)" }
if c == 4 { return "O(n^2)" }
if c == 5 { return "O(n^3)" }
return "O(?)"
}
fn elb_curve_from_name(s: String) -> Int {
if str_eq(s, "O(1)") { return 0 }
if str_eq(s, "O(log n)") { return 1 }
if str_eq(s, "O(n)") { return 2 }
if str_eq(s, "O(n log n)") { return 3 }
if str_eq(s, "O(n^2)") { return 4 }
if str_eq(s, "O(n^3)") { return 5 }
return -1
}
// elb_classify_ratio map a milli-ratio-per-doubling onto a curve.
//
// Bands are deliberately wide at the top (a quadratic measured at 3.4x is
// still a quadratic) and deliberately overlap-averse at the bottom, where a
// misclassification between O(1) and O(log n) matters least.
fn elb_classify_ratio(milli: Int) -> Int {
if milli < 1300 { return 0 }
if milli < 1700 { return 1 }
if milli < 2400 { return 2 }
if milli < 3200 { return 3 }
if milli < 6000 { return 4 }
return 5
}
// elb_ratio milli-ratio between two consecutive measurements.
// Returns -1 when the earlier measurement is zero (ratio undefined).
fn elb_ratio(prev: Int, cur: Int) -> Int {
if prev <= 0 { return -1 }
return (cur * 1000) / prev
}
// The measurement floor
//
// A benchmark whose largest measurement is at or near zero has not been
// measured. Reporting it as O(1) would be a confident answer with nothing
// behind it the same failure as a test that never ran reporting pass, and
// exactly what happened when clang closed a nested loop to a multiply and the
// harness read 0 microseconds at every n.
//
// So: REFUSE. Never classify below the floor.
fn elb_below_floor(vals: [Int], floor: Int) -> Bool {
let n: Int = native_list_len(vals)
let i: Int = 0
let mx: Int = 0
while i < n {
let v: Int = native_list_get(vals, i)
if v > mx { let mx = v }
let i = i + 1
}
if mx < floor { return true }
return false
}
// elb_implausibly_flat a measurement that does not move across a sweep whose
// input grew by 8x or more is not a flat curve, it is a broken measurement.
// Genuine O(1) work still shows noise; a hard-flat series means the work was
// optimised away, the timer has insufficient resolution, or the benchmark body
// never executed.
fn elb_implausibly_flat(vals: [Int]) -> Bool {
let n: Int = native_list_len(vals)
if n < 3 { return false }
let first: Int = native_list_get(vals, 0)
let last: Int = native_list_get(vals, n - 1)
if first == 0 {
if last == 0 { return true }
return false
}
let r: Int = (last * 1000) / first
if r < 1100 { return true }
return false
}
// elb_spread_ok do the consecutive ratios agree with each other?
//
// This is the ratio-method analogue of a normalised-RMS threshold. If the
// doublings disagree wildly the data is noise, a cache cliff, or a phase
// change, and the honest report is INDETERMINATE rather than a classification.
// Applies to the ASYMPTOTIC TAIL only the last three ratios.
//
// The small-n end of any sweep is dominated by fixed overhead, cold caches and
// branch predictors that have not warmed. Measured on a genuinely linear
// character scan, the ratios ran 3.37, 2.92, 1.76, 1.65: the head looks
// quadratic, the tail is the truth. Checking spread across the whole sweep
// therefore rejects correct data. A complexity bound is an asymptotic claim, so
// it is judged on the asymptotic region the same reason a benchmark harness
// discards warmup rather than averaging it in.
fn elb_spread_ok(ratios: [Int]) -> Bool {
let total: Int = native_list_len(ratios)
if total < 2 { return true }
let start: Int = total - 3
if start < 0 { let start = 0 }
let n: Int = total
let lo: Int = 999999
let hi: Int = 0
let i: Int = start
while i < n {
let r: Int = native_list_get(ratios, i)
if r >= 0 {
if r < lo { let lo = r }
if r > hi { let hi = r }
}
let i = i + 1
}
if lo <= 0 { return false }
// Reject when the widest ratio is more than 2.2x the narrowest. That is
// enough slack for real timing noise and tight enough to separate a clean
// 2.0 series from a clean 4.0 series.
if (hi * 1000) / lo > 2200 { return false }
return true
}
// elb_ratios consecutive milli-ratios across the sweep.
fn elb_ratios(vals: [Int]) -> [Int] {
let out: [Int] = native_list_empty()
let n: Int = native_list_len(vals)
let i: Int = 1
while i < n {
let out = native_list_append(out,
elb_ratio(native_list_get(vals, i - 1), native_list_get(vals, i)))
let i = i + 1
}
return out
}
// elb_mean_tail_ratio mean of the LAST TWO ratios.
//
// The tail is used deliberately: asymptotic behaviour is what a complexity
// bound claims, and the small-n end of any sweep is dominated by fixed
// overhead. This is the same reason a benchmark harness discards warmup.
fn elb_mean_tail_ratio(ratios: [Int]) -> Int {
let n: Int = native_list_len(ratios)
if n == 0 { return -1 }
if n == 1 { return native_list_get(ratios, 0) }
let a: Int = native_list_get(ratios, n - 1)
let b: Int = native_list_get(ratios, n - 2)
if a < 0 { return b }
if b < 0 { return a }
return (a + b) / 2
}
// Verdicts
//
// 0 PASS measured curve is at or below the declared bound
// 1 FAIL measured curve is strictly worse than declared
// 2 INDETERMINATE ratios disagree; data is noise or a phase change
// 3 REFUSED below the measurement floor, or implausibly flat
// 4 BETTER measured strictly better than declared (warn, not fail)
fn elb_verdict_name(v: Int) -> String {
if v == 0 { return "PASS" }
if v == 1 { return "FAIL" }
if v == 2 { return "INDETERMINATE" }
if v == 3 { return "REFUSED" }
if v == 4 { return "BETTER" }
return "?"
}
// elb_gate classify one signal against its declared bound.
//
// vals measurements, one per sweep point, in sweep order
// expect declared curve index (see elb_curve_name)
// floor minimum largest-measurement below which we refuse to classify
fn elb_gate(vals: [Int], expect: Int, floor: Int) -> Int {
if elb_below_floor(vals, floor) { return 3 }
if elb_implausibly_flat(vals) { return 3 }
let ratios: [Int] = elb_ratios(vals)
if !elb_spread_ok(ratios) { return 2 }
let m: Int = elb_mean_tail_ratio(ratios)
if m < 0 { return 2 }
let got: Int = elb_classify_ratio(m)
if got > expect { return 1 }
if got < expect { return 4 }
return 0
}
// elb_measured_curve the classified curve for a signal, or -1 if unclassifiable.
fn elb_measured_curve(vals: [Int], floor: Int) -> Int {
if elb_below_floor(vals, floor) { return -1 }
if elb_implausibly_flat(vals) { return -1 }
let ratios: [Int] = elb_ratios(vals)
let m: Int = elb_mean_tail_ratio(ratios)
if m < 0 { return -1 }
return elb_classify_ratio(m)
}
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// runtime/eltest.el El test framework runner (Phase 1).
//
// This is the RUNNER. It is written in El and consumes a registry that the
// compiler generates into the same translation unit when invoked as
// `elc --test`. Nothing here discovers tests; discovery already happened at
// compile time, which is what makes `--list` and filtering possible later.
//
// Architecture
//
// The compiler lowers each `test "name" { ... }` block into a static C
// function and emits a static table of (name, fn) pairs plus a small set of
// index-based accessors. El has no function pointers, so the runner never
// sees one it works entirely in indices:
//
// __el_reg_count() -> Int number of registered tests
// __el_reg_name(i) -> String test name at index i
// __el_reg_invoke(i) -> Int run test i, return its failure count
// __el_reg_last_ns() -> Int wall-clock ns of the last invoke
// __el_reg_msg() -> String first failure message of the last invoke
// __el_reg_asserts() -> Int assertions executed in the last invoke
// __el_opt_json() -> Int 1 if --json was passed
//
// Timing is taken in the generated C, immediately around the call, so no El
// call overhead lands inside the measurement.
//
// Output
//
// Structured events are the source of truth. The human renderer is written
// FROM the same fields the NDJSON renderer emits never the reverse. Parsing
// human output back into structure is the one clear architectural mistake in
// Go's test tooling and we do not repeat it.
//
// Every result carries a duration. Always. A framework that cannot report how
// long its tests took cannot surface a performance regression, and a
// regression nobody can see is one nobody fixes.
// Small helpers (no imports this file must stay self-contained)
// _elt_json_escape minimal JSON string escaping for the NDJSON renderer.
fn _elt_json_escape(s: String) -> String {
let out: String = ""
let n: Int = str_len(s)
let i: Int = 0
while i < n {
let ch: String = str_slice(s, i, i + 1)
if str_eq(ch, "\"") {
let out = out + "\\\""
} else {
if str_eq(ch, "\\") {
let out = out + "\\\\"
} else {
if str_eq(ch, "\n") {
let out = out + "\\n"
} else {
if str_eq(ch, "\t") {
let out = out + "\\t"
} else {
if str_eq(ch, "\r") {
let out = out + "\\r"
} else {
let out = out + ch
}
}
}
}
}
let i = i + 1
}
return out
}
// _elt_pad3 left-pad an integer to three digits (for the ms.fraction form).
fn _elt_pad3(v: Int) -> String {
if v < 10 { return "00" + int_to_str(v) }
if v < 100 { return "0" + int_to_str(v) }
return int_to_str(v)
}
// _elt_ms render a nanosecond duration as "M.mmm" milliseconds.
//
// Deliberately avoids the modulo operator: the remainder is derived by
// subtraction so this stays portable across El backends.
fn _elt_ms(ns: Int) -> String {
let total_us: Int = ns / 1000
let ms_whole: Int = total_us / 1000
let us_rem: Int = total_us - (ms_whole * 1000)
return int_to_str(ms_whole) + "." + _elt_pad3(us_rem)
}
// _elt_secs render a nanosecond duration as fractional seconds, for the
// NDJSON `elapsed` field. JUnit XML and test2json both use seconds-as-decimal.
fn _elt_secs(ns: Int) -> String {
let total_ms: Int = ns / 1000000
let s_whole: Int = total_ms / 1000
let ms_rem: Int = total_ms - (s_whole * 1000)
return int_to_str(s_whole) + "." + _elt_pad3(ms_rem)
}
// Event emission
//
// One function per event shape. Both renderers read the same fields; the
// human renderer is a projection of the event, not a separate code path.
fn _elt_emit_run(json_mode: Bool, name: String) {
if json_mode {
println("{\"action\":\"run\",\"test\":\"" + _elt_json_escape(name) + "\"}")
}
}
fn _elt_emit_result(json_mode: Bool, name: String, fails: Int, ns: Int, asserts: Int, msg: String) {
if json_mode {
let action: String = "pass"
if fails > 0 { let action = "fail" }
let line: String = "{\"action\":\"" + action + "\""
let line = line + ",\"test\":\"" + _elt_json_escape(name) + "\""
let line = line + ",\"elapsed\":" + _elt_secs(ns)
let line = line + ",\"assertions\":" + int_to_str(asserts)
if fails > 0 {
let line = line + ",\"failures\":" + int_to_str(fails)
let line = line + ",\"message\":\"" + _elt_json_escape(msg) + "\""
}
let line = line + "}"
println(line)
return
}
// Human renderer duration is never optional.
if fails > 0 {
println("FAIL " + name + " (" + _elt_ms(ns) + "ms)")
println(" " + msg)
return
}
println("ok " + name + " (" + _elt_ms(ns) + "ms)")
return
}
fn _elt_emit_summary(json_mode: Bool, total: Int, failed: Int, ns: Int, asserts: Int) {
let passed: Int = total - failed
if json_mode {
let line: String = "{\"action\":\"summary\""
let line = line + ",\"tests\":" + int_to_str(total)
let line = line + ",\"passed\":" + int_to_str(passed)
let line = line + ",\"failed\":" + int_to_str(failed)
let line = line + ",\"assertions\":" + int_to_str(asserts)
let line = line + ",\"elapsed\":" + _elt_secs(ns)
let line = line + "}"
println(line)
return
}
println("")
println(int_to_str(total) + " tests, " + int_to_str(passed) + " passed, "
+ int_to_str(failed) + " failed, " + int_to_str(asserts) + " assertions in "
+ _elt_ms(ns) + "ms")
return
}
// The runner
// el_test_main drive the compile-time registry.
//
// Called from the generated main(). Returns the number of FAILING TESTS, which
// becomes the process exit code. Note that this counts tests, not assertions:
// a test is the unit of result. The old harness counted assertions globally and
// therefore could not say which test failed, how long any of them took, or
// whether a test had run at all.
fn el_test_main() -> Int {
let json_mode: Bool = false
if __el_opt_json() == 1 { let json_mode = true }
let n: Int = __el_reg_count()
let i: Int = 0
let failed: Int = 0
let total_ns: Int = 0
let total_asserts: Int = 0
while i < n {
let name: String = __el_reg_name(i)
_elt_emit_run(json_mode, name)
let fails: Int = __el_reg_invoke(i)
let ns: Int = __el_reg_last_ns()
let asserts: Int = __el_reg_asserts()
let msg: String = __el_reg_msg()
let total_ns = total_ns + ns
let total_asserts = total_asserts + asserts
if fails > 0 { let failed = failed + 1 }
_elt_emit_result(json_mode, name, fails, ns, asserts, msg)
let i = i + 1
}
_elt_emit_summary(json_mode, n, failed, total_ns, total_asserts)
return failed
}
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// fitprobe.el controlled growth-curve specimens for validating the complexity fitter.
//
// Three deliberately-shaped workloads. None depends on a real defect existing,
// which is the point: the fitter must be provable against KNOWN curves.
//
// linear one allocation per item. count O(n), bytes O(n), time O(n)
// accum rebuilds its accumulator. count O(n), bytes O(n^2), time O(n^2)
// compute nested arithmetic, no alloc. count O(1), bytes O(1), time O(n^2)
//
// `compute` is the specimen that matters. It is the shape of el #132
// (strlen-per-character inside str_char_code): pure CPU, zero allocation.
// An allocation-only gate is structurally blind to it.
//
// No imports uses runtime builtins directly so nothing collides.
fn work_linear(n: Int) -> Int {
let parts: [String] = native_list_empty()
let i: Int = 0
while i < n {
let parts = native_list_append(parts, int_to_str(i))
let i = i + 1
}
return native_list_len(parts)
}
fn work_accum(n: Int) -> Int {
let acc: String = ""
let i: Int = 0
while i < n {
let acc = acc + "x"
let i = i + 1
}
return str_len(acc)
}
fn work_compute(n: Int) -> Int {
// str_char_code is an opaque external call, so the C optimiser cannot
// reduce this nest to a closed form the way it does with `total + 1`.
// This is the exact shape of el #132: n scans over n characters, pure
// CPU, ZERO allocation.
let s: String = "abcdefghij"
let total: Int = 0
let i: Int = 0
while i < n {
let j: Int = 0
while j < n {
let total = total + str_char_code(s, 0)
let j = j + 1
}
let i = i + 1
}
return total
}
fn run_one(mode: String, n: Int) {
let c0: Int = el_alloc_count()
let b0: Int = el_alloc_bytes()
let t0: Int = el_now_instant()
let r: Int = 0
if str_eq(mode, "linear") { let r = work_linear(n) }
if str_eq(mode, "accum") { let r = work_accum(n) }
if str_eq(mode, "compute") { let r = work_compute(n) }
let t1: Int = el_now_instant()
let c1: Int = el_alloc_count()
let b1: Int = el_alloc_bytes()
println(mode + "\t" + int_to_str(n)
+ "\t" + int_to_str(c1 - c0)
+ "\t" + int_to_str(b1 - b0)
+ "\t" + int_to_str((t1 - t0) / 1000)
+ "\t" + int_to_str(r))
return
}
fn sweep(mode: String) {
run_one(mode, 200)
run_one(mode, 400)
run_one(mode, 800)
run_one(mode, 1600)
return
}
fn main() -> Int {
println("mode\tn\tallocs\tbytes\tusec\tsink")
sweep("linear")
sweep("accum")
sweep("compute")
return 0
}
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// tests/native/test_compiler.el comprehensive tests for the El compiler pipeline.
//
// Tests the lexer (lexer.el), parser (parser.el), and codegen (codegen.el)
+1
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// test_codegen_js.el - basic tests for JS codegen features.
//
// These tests verify that core El language features produce correct values
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import "../../runtime/eltest.el"
import "../../runtime/elbench.el"
// test_elbench.el proves the growth-curve classifier against KNOWN curves.
//
// Every series below is real measured data from lang/tests/bench/fitprobe.el
// on a geometric sweep n = 200/400/800/1600. The classifier must be provable
// without depending on a live defect existing, which is the whole point of
// keeping controlled specimens.
fn _s4(a: Int, b: Int, c: Int, d: Int) -> [Int] {
let l: [Int] = native_list_empty()
let l = native_list_append(l, a)
let l = native_list_append(l, b)
let l = native_list_append(l, c)
let l = native_list_append(l, d)
return l
}
test "classifies a linear allocation series as O(n)" {
// fitprobe `linear`, allocation count
let v = _s4(208, 409, 810, 1611)
assert elb_measured_curve(v, 10) == 2, "linear allocs should classify O(n)"
}
test "classifies a linear byte series as O(n)" {
// fitprobe `linear`, allocation bytes
let v = _s4(4786, 9682, 19474, 39658)
assert elb_measured_curve(v, 10) == 2, "linear bytes should classify O(n)"
}
test "classifies a quadratic byte series as O(n^2)" {
// fitprobe `accum`, allocation bytes -- the accumulator-rebuild shape
let v = _s4(20300, 80600, 321200, 1282400)
assert elb_measured_curve(v, 10) == 4, "accum bytes should classify O(n^2)"
}
test "accumulator count is linear -- proves count alone misses it" {
// Same run as above. The COUNT is exactly linear while bytes are
// quadratic. A count-only gate passes this defect clean.
let v = _s4(200, 400, 800, 1600)
assert elb_measured_curve(v, 10) == 2, "accum count classifies O(n)"
assert elb_gate(v, 2, 10) == 0, "count-only gate PASSES the quadratic"
}
test "classifies a quadratic time series as O(n^2)" {
// fitprobe `compute` -- el #132's shape: n scans over n characters
let v = _s4(67, 205, 818, 3268)
assert elb_measured_curve(v, 10) == 4, "compute time should classify O(n^2)"
}
test "REFUSES an all-zero series instead of calling it O(1)" {
// fitprobe `compute` allocation count. Pure CPU, allocates nothing.
// Reporting O(1) here would be a confident answer with nothing behind it.
let v = _s4(0, 0, 0, 0)
assert elb_gate(v, 2, 10) == 3, "all-zero series must be REFUSED"
assert elb_measured_curve(v, 10) < 0, "unclassifiable returns -1"
}
test "REFUSES an implausibly flat series" {
// The shape produced when clang closes a loop to a multiply: a real
// answer, no work done, no movement across an 8x input range.
let v = _s4(1000, 1001, 1002, 1003)
assert elb_gate(v, 2, 10) == 3, "hard-flat series must be REFUSED"
}
test "gate FAILS a quadratic declared as linear" {
let v = _s4(20300, 80600, 321200, 1282400)
assert elb_gate(v, 2, 10) == 1, "O(n^2) measured vs O(n) declared must FAIL"
}
test "gate PASSES a linear series declared as linear" {
let v = _s4(208, 409, 810, 1611)
assert elb_gate(v, 2, 10) == 0, "O(n) measured vs O(n) declared must PASS"
}
test "gate reports BETTER when measured beats the declared bound" {
let v = _s4(208, 409, 810, 1611)
assert elb_gate(v, 4, 10) == 4, "O(n) measured vs O(n^2) declared is BETTER"
}
test "gate reports INDETERMINATE on disagreeing ratios" {
// fitprobe `linear` WALL TIME at these sizes: 26/19/43/78 microseconds.
// Ratios 0.73, 2.26, 1.81 disagree well past the noise threshold. The
// honest answer is "cannot tell", not a classification -- this is exactly
// why benchmarks need auto-scaled iteration counts rather than one shot.
let v = _s4(26, 19, 43, 78)
assert elb_gate(v, 2, 10) == 2, "disagreeing ratios must be INDETERMINATE"
}
test "black_box is a real barrier and returns its input" {
assert el_black_box(42) == 42, "black_box is value-preserving"
let s: Int = 0
let i: Int = 0
while i < 100 {
// Bind the call before using it in arithmetic: `x + call(...)`
// lowers to el_str_concat() on integers. Same inference defect
// as `call(...) == y` lowering to str_eq().
let bx: Int = el_black_box(1)
let s = s + bx
let i = i + 1
}
assert s == 100, "black_box does not disturb the computation"
}
test "curve names round-trip" {
assert elb_curve_from_name("O(n)") == 2, "O(n) parses"
assert elb_curve_from_name("O(n^2)") == 4, "O(n^2) parses"
assert str_eq(elb_curve_name(4), "O(n^2)"), "O(n^2) renders"
assert elb_curve_from_name("O(nonsense)") < 0, "unknown curve is -1"
}
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// test_env.el - native test suite for runtime/env.el
//
// Covers: env() for reading environment variables, args() returning a list,
+1
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// test_fs.el - native test suite for runtime/fs.el
//
// Covers: fs_write/read round-trip, fs_exists, fs_mkdir, fs_list,
+1
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// test_json.el - native test suite for runtime/json.el
//
// Covers: json_get (dot-path), typed extractors (int, bool, float),
+178
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import "../../runtime/eltest.el"
import "../../runtime/elbench.el"
// test_lexer_scaling.el THE ARMED GATE.
//
// This is the regression test that would have caught el #132.
//
// #132 was a strlen() inside str_char_code() and str_slice(). The lexer walks
// source one character at a time, so every character access rescanned the whole
// remaining input: O(n) per character over n characters = O(n^2). It shipped for
// months. It was found by a geometric sweep, not by reading code.
//
// So this test IS a geometric sweep. It scans a string of length n, character by
// character, at four doubling sizes, and asserts the cost is linear. If anyone
// reintroduces a per-character rescan in str_char_code, in str_slice, in any
// accessor the lexer leans on the measured curve becomes O(n^2) and this fails.
//
// The value is in it being ARMED, not in it currently failing. It passes today
// because #132 is fixed. That is the correct state for a regression gate.
//
// Note the deliberate `let c: Int = str_char_code(...)` binding in the scan loop.
// Inlining it as `total + str_char_code(s, i)` lowers to el_str_concat() on
// integers the Plus arm of the operator-typing family, still open at the time
// of writing. Binding first is the safe form.
// _mk_string build a string of length >= n by DOUBLING.
//
// Deliberately not `s = s + "x"` n times: that is itself quadratic in bytes and
// would contaminate the very measurement this test exists to take. Doubling
// allocates ~2n total.
fn _mk_string(n: Int) -> String {
let s: String = "abcdefgh"
while str_len(s) < n {
let s = s + s
}
return s
}
// _scan walk the string one character at a time, REPS times.
//
// This is the lexer's access pattern reduced to its essential shape. The
// repetitions lift the measurement clear of timer resolution; without them the
// smaller sizes land in noise and the classifier correctly reports
// INDETERMINATE rather than guessing.
fn _scan(s: String, n: Int, reps: Int) -> Int {
let total: Int = 0
let r: Int = 0
while r < reps {
let i: Int = 0
while i < n {
let c: Int = str_char_code(s, i)
let total = total + c
let i = i + 1
}
let r = r + 1
}
return total
}
// _measure_scan microseconds for a full scan sweep point.
fn _measure_scan(n: Int, reps: Int) -> Int {
let s: String = _mk_string(n)
// WARMUP, discarded. Without it the small-n end of the sweep is dominated
// by cold caches and reads as superlinear on genuinely linear work --
// measured ratios 3.37 2.92 1.76 1.65 on exactly this workload.
let w: Int = _scan(s, n, 2)
let wj: Int = el_black_box(w)
let t0: Int = el_now_instant()
let got: Int = _scan(s, n, reps)
let t1: Int = el_now_instant()
// Feed the result through the barrier so the scan cannot be elided.
let sink: Int = el_black_box(got)
if sink == 0 { println("") }
return (t1 - t0) / 1000
}
fn _series4(a: Int, b: Int, c: Int, d: Int) -> [Int] {
let l: [Int] = native_list_empty()
let l = native_list_append(l, a)
let l = native_list_append(l, b)
let l = native_list_append(l, c)
let l = native_list_append(l, d)
return l
}
test "character scan is LINEAR in time -- regression gate for el #132" {
let reps: Int = 40
let t1: Int = _measure_scan(16384, reps)
let t2: Int = _measure_scan(32768, reps)
let t3: Int = _measure_scan(65536, reps)
let t4: Int = _measure_scan(131072, reps)
let series: [Int] = _series4(t1, t2, t3, t4)
let verdict: Int = elb_gate(series, 2, 50)
let measured: Int = elb_measured_curve(series, 50)
// Report the actual numbers regardless of outcome. A gate that fires
// without showing its evidence is just an assertion.
println(" scan us: " + int_to_str(t1) + " " + int_to_str(t2) + " "
+ int_to_str(t3) + " " + int_to_str(t4)
+ " -> " + elb_curve_name(measured) + " [" + elb_verdict_name(verdict) + "]")
// PASS (0) or BETTER (4) are both acceptable. FAIL (1) means someone
// reintroduced superlinear per-character cost. REFUSED (3) or
// INDETERMINATE (2) mean the measurement is untrustworthy -- which is
// also a failure of this test, deliberately: a gate that cannot measure
// must not report success.
assert verdict == 0 || verdict == 4, "character scan must measure O(n) or better"
}
test "string building by doubling stays linear in allocated bytes" {
let b1: Int = el_alloc_bytes()
let s1: String = _mk_string(8192)
let b2: Int = el_alloc_bytes()
let s2: String = _mk_string(16384)
let b3: Int = el_alloc_bytes()
let s3: String = _mk_string(32768)
let b4: Int = el_alloc_bytes()
let s4: String = _mk_string(65536)
let b5: Int = el_alloc_bytes()
let series: [Int] = _series4(b2 - b1, b3 - b2, b4 - b3, b5 - b4)
let verdict: Int = elb_gate(series, 2, 1000)
let measured: Int = elb_measured_curve(series, 1000)
println(" bytes: " + int_to_str(b2 - b1) + " " + int_to_str(b3 - b2) + " "
+ int_to_str(b4 - b3) + " " + int_to_str(b5 - b4)
+ " -> " + elb_curve_name(measured) + " [" + elb_verdict_name(verdict) + "]")
assert verdict == 0 || verdict == 4, "doubling build must be O(n) in bytes"
assert str_len(s4) >= 65536, "final string reached the requested size"
}
// _scan_quadratic a DELIBERATELY quadratic scan: for each position, rescan
// from the start. This is precisely what el #132 did strlen() from offset 0
// on every character access reproduced here so the gate can be proven to
// FIRE, not merely to pass on healthy code. An unproven gate is decoration.
fn _scan_quadratic(s: String, n: Int) -> Int {
let total: Int = 0
let i: Int = 0
while i < n {
let j: Int = 0
while j < i {
let c: Int = str_char_code(s, j)
let total = total + c
let j = j + 1
}
let i = i + 1
}
return total
}
fn _measure_quadratic(n: Int) -> Int {
let s: String = _mk_string(n)
let w: Int = _scan_quadratic(s, 64)
let wj: Int = el_black_box(w)
let t0: Int = el_now_instant()
let got: Int = _scan_quadratic(s, n)
let t1: Int = el_now_instant()
let sink: Int = el_black_box(got)
return (t1 - t0) / 1000
}
test "the gate FIRES on a live quadratic scan -- proves it is armed" {
let q1: Int = _measure_quadratic(1024)
let q2: Int = _measure_quadratic(2048)
let q3: Int = _measure_quadratic(4096)
let q4: Int = _measure_quadratic(8192)
let series: [Int] = _series4(q1, q2, q3, q4)
let verdict: Int = elb_gate(series, 2, 50)
let measured: Int = elb_measured_curve(series, 50)
println(" quad us: " + int_to_str(q1) + " " + int_to_str(q2) + " "
+ int_to_str(q3) + " " + int_to_str(q4)
+ " -> " + elb_curve_name(measured) + " [" + elb_verdict_name(verdict) + "]")
assert measured == 4, "a rescan-from-zero workload must classify O(n^2)"
assert verdict == 1, "declared O(n) against measured O(n^2) must FAIL the gate"
}
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// test_math.el - native test suite for runtime/math.el
//
// Covers: integer math (abs, max, min), float math (sqrt, log, sin, cos, pi),
+1
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// test_state.el - native test suite for runtime/state.el
//
// Covers: state_set/get/del, state_has, state_get_or, state_keys,
+1
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// test_string.el - native test suite for runtime/string.el
//
// Covers: type conversions, core primitives, comparison and search,
+1
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// test_text.el - native test suite for text primitives.
//
// Mirrors the acceptance corpus in tests/text/examples/ using the
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// test_time.el - native test suite for runtime/time.el
//
// Covers: time_now (positive timestamp), time_to_parts (UTC decomposition),
@@ -0,0 +1,28 @@
fn getstr(x: String) -> String { return x }
fn getint(x: Int) -> Int { return x }
fn ok(label: String) -> Void { println("ok " + label) }
fn bad(label: String) -> Void { println("FAIL " + label) }
let s1: String = "hello"
let s2: String = "hello"
let s3: String = "world"
let i1: Int = 5
let i2: Int = 5
let i3: Int = 9
if "abc" == "abc" { ok("str literal eq") } else { bad("str literal eq") }
if "abc" == "xyz" { bad("str literal ne") } else { ok("str literal ne") }
if s1 == s2 { ok("str var eq") } else { bad("str var eq") }
if s1 == s3 { bad("str var ne") } else { ok("str var ne") }
if getstr("hi") == "hi" { ok("str call vs literal") } else { bad("str call vs literal") }
if s1 == getstr("hello") { ok("str var vs call") } else { bad("str var vs call") }
if s1 == getstr("nope") { bad("str var vs call ne") } else { ok("str var vs call ne") }
if i1 == i2 { ok("int var eq") } else { bad("int var eq") }
if i1 == i3 { bad("int var ne") } else { ok("int var ne") }
if getint(5) == i1 { ok("int call vs var") } else { bad("int call vs var") }
if getint(9) == i1 { bad("int call vs var ne") } else { ok("int call vs var ne") }
if s1 != s3 { ok("str NOTEQ") } else { bad("str NOTEQ") }
if s1 != s2 { bad("str NOTEQ same") } else { ok("str NOTEQ same") }
if i1 != i3 { ok("int NOTEQ") } else { bad("int NOTEQ") }
if getint(9) != i1 { ok("int call NOTEQ") } else { bad("int call NOTEQ") }
println("done")
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@@ -1,3 +1,4 @@
import "../../runtime/eltest.el"
// tests/runtime/string_test.el Test suite for runtime/string.el
//
// Exercises every public function exported by runtime/string.el using the