trekhleb/javascript-algorithms

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3 of your 27 findings came from Repobility's proprietary detections. ✓ Repobility tags below mark them.

Scan timing: clone 5.54s · analysis 10.42s · 10.1 MB · GitHub API rate-limit (preflight)

https://github.com/trekhleb/javascript-algorithms · scanned 2026-06-05 04:30 UTC (5 hours, 30 minutes ago) · 10 languages

150 findings (26 legacy + 124 scanner) 75th percentile · Javascript · medium (20-100K LoC) Scanner says 89 (lower by 12)

File as issue Image v2 schema

UNIFIED Repobility · multi-layer engine · AI coders

Complete repo analysis

Last scanned 5 hours, 30 minutes ago · v2 · 88 findings from 2 sources. Findings combine the legacy security pipeline AND the multi-layer engine (atlas, wiring, flows, ranked) AND verified AI agent contributions.

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Score breakdown â 2026-05-18-v5

Component	Sub-score	Weight	Contribution
`structure_score`	85.0	0.15	12.75
`security_score`	55.0	0.25	13.75
`testing_score`	95.0	0.20	19.00
`documentation_score`	82.0	0.15	12.30
`practices_score`	82.0	0.15	12.30
`code_quality`	76.8	0.10	7.68
Overall		1.00	77.8

Severity distribution — click a segment to filter

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Severity: Critical 0 High 15 Medium 7 Low 55 9-Layer: Software Security Quality Integrity Frontend Hardware Data Network Cicd Source: Legacy 26 9-layer 62 Crowd 0 Layer: Software 67 Quality 14 Api 1 Frontend 1 Security 1 Cicd 4

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Bug-class explainers. Each card groups findings of the same shape — these are the patterns most likely to ship to prod and reappear in future scans unless you systematically fix the cause, not just the instance.

Fragile runtime 9 findings

What it is: Code that runs but breaks under predictable input — division by zero, missing keys, unbounded loops, off-by-one slicing.

Why it matters: Reaches production undetected because happy-path tests pass. First user with a weird input crashes the request.

How AI causes it: AI loves writing the happy path; doesn't probe edge cases unless explicitly asked.

Fix approach: Add property-based tests. Wrap external inputs with explicit validators. Use the framework's typed deserializer (Pydantic, attrs).

9 matching findings on this repo

medium [SEC087] JS: weak Math.random for crypto: Math.random() is not cryptographicall… src/algorithms/statistics/weighted-random/weighte…:39
low Duplicated implementation block across source files src/data-structures/stack/Stack.js:3
low Duplicated implementation block across source files src/data-structures/linked-list/LinkedList.js:78
low Duplicated implementation block across source files src/data-structures/heap/MinHeapAdhoc.js:2
low Duplicated implementation block across source files src/algorithms/graph/depth-first-search/depthFirs…:1
low Duplicated implementation block across source files src/algorithms/graph/bridges/graphBridges.js:20
high [SEC128] Async function without await — fire-and-forget Promise (AI mistake): A… src/data-structures/priority-queue/PriorityQueue.…:39
high [SEC128] Async function without await — fire-and-forget Promise (AI mistake): A… src/data-structures/lru-cache/LRUCacheOnMap.js:30
high [SEC128] Async function without await — fire-and-forget Promise (AI mistake): A… src/data-structures/graph/GraphVertex.js:44

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Commented-out code 5 findings

What it is: Lines of source that were intentionally disabled but never deleted.

Why it matters: Git already remembers history — commented code rots, becomes wrong, and adds noise to diffs.

How AI causes it: AI sometimes comments out broken code instead of fixing it. Reviewers approve out of inertia.

Fix approach: Delete. Trust `git log`. If you really need to remember, save it in a notes file under `docs/`.

5 matching findings on this repo

info Commented-code block (9 lines) in src/algorithms/string/z-algorithm/zAlgorithm.…
info Commented-code block (5 lines) in src/algorithms/image-processing/seam-carving/…
info Commented-code block (5 lines) in src/algorithms/statistics/weighted-random/wei…
info Commented-code block (5 lines) in src/algorithms/math/square-root/squareRoot.js…
info Commented-code block (5 lines) in src/algorithms/graph/floyd-warshall/floydWars…

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Config drift 1 finding

What it is: Settings duplicated across env files, Docker compose, K8s, and code defaults, all with slightly different values.

Why it matters: Production behaviour depends on whichever copy your loader reads first. Subtle bugs in staging that don't reproduce in dev.

How AI causes it: AI writes new config from memory rather than reading the existing source.

Fix approach: Pick one source of truth (env vars + a settings module). Have every other place import from there. Lint for duplicates in CI.

1 matching finding on this repo

low File has no detected symbols: jest.config.js

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