clojure-code-snippet

Introduction

This piece of code is a curated collection of commonly used algorithms, aimed at reinforcing a software engineer's general algorithmic knowledge. Each snippet is implemented in a minimal and accessible manner, focusing on clarity of logic rather than production-readiness.

This repository is the Clojure port of the collection (see cpp-code-snippets). Solutions mirror the other snippet repos: one script per problem at src/<topic>/<problem>.clj, executed as java -cp <clojure.jar> clojure.main <script> (stdin in, stdout out).

Scope

The repository intentionally excludes production-level concerns such as:

• Memory management
• Error handling
• Vulnerability mitigation

These aspects, while important in real-world applications, are intentionally left out to keep the focus on core algorithmic logic. The assumption is that the intended viewers are primarily interested in the conceptual content itself, rather than scrutinizing the code for potential attack surfaces or production-level robustness.

Privacy & Exposure

Some code examples have been moved to a private repository as a precautionary measure to limit exposure and reduce potential risk, especially when the repository is accessed in contexts where the intent of the viewer is uncertain.

Test Cases

To respect the rights of original content creators, test cases are not included in this repository in plain form. Instead, they can be found on the websites where the referenced problems originate.

For automated validation, the shared test cases from the recipes superproject (resource/shared) ship as an encrypted bundle, tests/resources.tar.xz.asc (tar.xz, AES-256, ASCII-armored). snip test runs every src/**/*.clj script against the decrypted cases and diff-compares stdout against the expected output (trailing whitespace per line ignored).

CI/CD Pipeline

.github/workflows/test.yml validates the snippets on push to master, pull requests, and manual dispatch. It downloads the Clojure jars, decrypts the bundle with the RESOURCES_PASSPHRASE organization secret (shared with the python/ocaml snippet repos), builds the snip tool once (cached per source hash), and runs:

snip test --resources tests/resources --jobs 4 --timeout 300

To test locally, build snip (go build -o snip ./cmd/snip in scripts/ci/go; stdlib-only, no dependencies), decrypt the bundle into tests/resources/ (passphrase holders only) and run the same command. The Clojure classpath comes from --cp or $CLOJURE_CP; when neither is set, sibling spec.alpha / core.specs.alpha jars next to a jar named by $CLOJURE_JAR (or .ci/jars/*.jar) are picked up automatically.

Rebuild the bundle after resource changes with:

snip bundle <resource/shared dir> <passphrase-file>

See snip bundle --help for the rotation instructions when using a fresh passphrase.

Performance tracking

snip measure runs the same scripts and cases but records load-independent metrics per case (Linux-only, needs GNU time, optionally perf):

• cpu_s (user+sys CPU time) — primary time signal; min-of-repeats
• maxrss_kb (peak RSS) — primary memory signal; max-of-repeats
• allocated_bytes (heap-used-at-exit under EpsilonGC, min of 3) — total allocation; load-independent gauge of algorithmic work
• instructions/cycles (perf stat, user-space) — most stable signal
• callgrind_instructions (--callgrind only, needs Valgrind) — deterministic whole-process Ir count (JVM: under -Xint + EpsilonGC; native: plain callgrind, no JVM flags)
• callgrind_allocated_bytes (--callgrind only) — total allocation of that same deterministic run: EpsilonGC total from the JVM's GC log on JVM legs (valgrind-side heap profilers cannot see Java objects), or the LD_PRELOAD counting shim's malloc-request total on native legs
• wall_s — secondary; not load-independent

Each case runs --repeat times (default 5) plus dedicated EpsilonGC allocation runs unless --no-alloc; summaries keep min/median/max. Compare same-machine ratios only (e.g. Clojure vs native back-to-back), never absolutes across machines. JVM allocated bytes are comparable within one JDK build only (absolutes shift between JDK versions); native-leg bytes are malloc-request totals — ratio-meaningful against the JVM number per benchmark, not bit-comparable absolutes. --aot measures the AOT-compiled classes instead of clojure.main interpretation (gen-class transform, cached per source hash under .ci/aot-cache/); --callgrind adds the one-shot deterministic instrumentation (~21s per case all-in on CI hardware, measured for all snippets by the sweep job). Cases exceeding the callgrind budget, EpsilonGC-exempt workloads (JVM leg only), and native-leg counter problems degrade to callgrind_skipped with a warning instead of failing (the timed data stays valid); crashes and output mismatches still fail.

snip measure --resources tests/resources --repeat 5 \
  --output perf.json --bmf-output bencher.json
snip measure --self-test  # parser checks, no JVM needed

CI runs correctness in the test job, then measures every snippet with --callgrind in a sharded matrix perf-callgrind sweep job (needs: test, 8 shards x 2 runtimes via snip measure --shard K/N, lean --repeat 1 --no-alloc recipe, ~40min per shard). Each shard reports its own BMF subset to Bencher (bencher run --adapter json --file sweep-bench.json, carrying only the two gungraun-run measures: callgrind_instructions thresholded at 1% plus unthresholded callgrind_allocated_bytes) — per-shard reports keep every check under GitHub's check-summary limit, where one merged report would re-truncate it — and uploads per-shard artifacts; a fan-in report-callgrind job merges the full reports per runtime (snip measure --merge), uploads the merged bundles, and appends a combined results table to its step summary. A non-blocking perf-pilot job keeps one --aot measurement per push as a stdout-gate canary. Bencher plots each snippet's callgrind_instructions/callgrind_allocated_bytes per commit for both runtimes and posts a check per shard on the head commit (full metrics stay in the uploaded sweep-results.json artifacts). The Bencher project API key lives in the BENCHER_API_KEY repository secret. Clojure jars, apt packages, and the cargo build are cached between runs.

Comparing compilers

Each compiler is a Bencher testbed (ubuntu-latest-jvm for JVM Clojure, ubuntu-latest-clojure-rs for the Rust port); benchmark names stay identical across compilers, so overlay the testbeds on Bencher's perf page to compare them visually. The native leg always builds clojure-rs master HEAD (resolved once per run so all 16 legs share one revision; interpreter-only cargo build --release --locked --no-default-features — run needs no LLVM), since the sweep diff-gates every case and Bencher shows the delta; a manual dispatch may pin clojure_rs_sha to bisect or repro. To add a compiler:

1. Add a runtime entry in .github/workflows/test.yml (perf-callgrind + report-callgrind matrices, testbed ubuntu-latest-<runtime>) with whatever build steps it needs.
2. Point snip measure at its invocation via --runtime <label> --command-template '...' ({cp}, {script}, {stem} holes); the same GNU time + perf harness measures every runtime, and non-java commands automatically take the native callgrind recipe (plain callgrind + LD_PRELOAD counting), keeping numbers comparable.