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shekhargulati/99-problems

This is an adaptation of the Ninety-Nine Prolog Problems written by Werner Hett.

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Java
★ 3,276
commit 7e120de6259b
scored 2026-11-14
scoring prov-5+qual-2+sec-2

AI provenance

none-detected

Confidence: 65%
Coverage: 100%

Estimated share of AI-generated code. Explicit attribution is a lower bound.

Code quality

89/100

strong

Confidence: 90%
Coverage: 100%

Complexity, duplication, lint density, tests, CI, docs and review process.

Security

81/100

adequate

Confidence: 85%
Coverage: 100%

Secrets, static analysis, vulnerable dependencies, CI and supply-chain posture.

Dispute or request a re-score Full report JSON

AI provenance

0% none-detected

No AI attribution or AI-consistent velocity signals detected.

How the score is built

Explicitly attributed share0%
Unattributed share in AI-pace bursts0%
Estimated AI-generated share0%
AI tool configuration files0
Work sessions at AI pace0
Releases at AI pacenot measured
Coding-style index (1.0+ means possible)0.00

Lines added per month all AI-attributed share

2015-11677 · 0% AI
2015-122,580 · 0% AI
2016-011,234 · 0% AI
2016-021,542 · 0% AI
2016-03790 · 0% AI
2016-04407 · 0% AI
2016-050 · 0% AI
2016-060 · 0% AI
2016-073 · 0% AI
2016-1157 · 0% AI
2017-098 · 0% AI
2020-100 · 0% AI

Evidence by analyzer

Explicit AI attributionok

attributed_commit_share: 0.0%
attributed_commits: 0
attributed_loc: 0
attributed_loc_share: 0.0%
commits: 225
effective_loc: 7,298
tools_detected: 0

AI tool configurationok

artifacts: 0
tools_configured: 0
workflow_agents: 0

Commit velocityok

excluded_import_loc: 0
flagged_loc: 0
flagged_loc_share: 0.0%
flagged_units: 0
max_loc_per_hour: 123.82
measured_loc: 7,298
median_loc_per_hour: 42.26
pr_timed_units: 5
pre_ai_era_burst_loc: 0
pre_ai_era_bursts: 0
pre_ai_era_measured_loc: 7,298
work_units: 83

Release velocityskipped

Coding styleok

count:assistant_voice: 0
count:emoji_in_code: 0
count:narrated_steps: 0
count:placeholder: 0
files:assistant_voice: 0
files:emoji_in_code: 0
files:narrated_steps: 0
files:placeholder: 0
index: 0
lines_scanned: 3,536
per_kloc:assistant_voice: 0
per_kloc:emoji_in_code: 0
per_kloc:narrated_steps: 0
per_kloc:placeholder: 0

Code quality

89 strong

Code quality is strong: test-to-source ratio 0.89, CI runs tests; 0% of function code in complex or long functions; 1% duplicated lines. Weakest area: docs.

How the score is built

Complexity100
Duplication92
Lint and smells100
Tests and CI90
Documentation45
Type safetynot measured
Review processnot measured

Evidence by analyzer

Complexity (lizard)ok

complex_functions: 0
function_nloc: 1,667
functions: 249
long_functions: 0
many_param_functions: 0
mean_ccn: 2.23
p90_ccn: 5
risky_nloc_share: 0.0%

Duplication (jscpd)ok2 items

compared_lines: 1,775
duplicated_lines: 26
duplicated_share: 1.5%
files: 117

Lintok

findings: 0
scanned_lines: 3,536
weighted_findings: 0

Tests and CIok2 items

CI config: .github/workflows/ci.yml .github/workflows/ci.yml
CI runs tests (mvn test)

check:ci_present: yes
check:ci_runs_lint: no
check:ci_runs_tests: yes
check:has_tests: yes
check:test_ratio: yes
check:tests_cochange: yes
ci_files: 1
cochange_commits: 150
cochange_share: 83.3%
source_lines: 3,536
test_lines: 3,138
test_ratio: 0.89

Documentationok2 items

README.md README.md
LICENSE LICENSE

check:changelog: no
check:contributing: no
check:license: yes
check:readme: no
readme_lines: 10

Type safetyskipped

Security

81 adequate

Security posture is adequate: 2 high-severity workflow issues. Weakest area: posture.

How the score is built

Secrets100
Static analysis (SAST)93
Vulnerable dependencies100
CI workflows63
Security posture0
OpenSSF Scorecardnot measured

Evidence by analyzer

OpenSSF Scorecardskipped

no published OpenSSF Scorecard result for this repo

Package registriesskipped

no registry dependencies declared

Secrets (gitleaks)ok

secrets_current: 0
secrets_history: 0
secrets_low_confidence: 0
secrets_nonprod: 0

Static analysis (opengrep)ok

findings: 3
findings_high: 0
findings_low: 0
findings_medium: 3
parse_errors: 0
scanned_lines: 3,536
weighted_findings: 0.75

Dependencies (osv-scanner)ok

penalty: 0
vulnerabilities: 0
vulnerable_packages: 0
vulns_critical: 0
vulns_high: 0
vulns_low: 0
vulns_medium: 0
vulns_unknown: 0

CI workflows (zizmor)ok

findings: 4
findings_high: 2
findings_low: 0
findings_medium: 2
penalty: 27.60
workflows: 1

Security postureok

check:dependency_updates: no
check:lockfiles: yes
check:security_policy: no
check:signed_commits: no
signed_commit_share: 1.0%
unpinned_manifests: 0

Release downloadsok

binary_assets: 0
signals: 0
suspicious: 0

Findings

2 high5 medium

Severity	Rule	Location	Message	Tool
high	`zizmor/unpinned-uses`	.github/workflows/ci.yml:18	unpinned action reference [confidence high]	CI workflows (zizmor)
high	`zizmor/unpinned-uses`	.github/workflows/ci.yml:20	unpinned action reference [confidence high]	CI workflows (zizmor)
medium	`zizmor/artipacked`	.github/workflows/ci.yml:18	credential persistence through GitHub Actions artifacts [confidence low]	CI workflows (zizmor)
medium	`zizmor/excessive-permissions`	.github/workflows/ci.yml:7	overly broad permissions [confidence medium]	CI workflows (zizmor)
medium	`opengrep/java.lang.security.audit.crypto.weak-random`	java8/src/main/java/com/shekhargulati/ninetynine_problems/_01_lists/P23.java:15	Detected use of the functions `Math.random()` or `java.util.Random()`. These are both not cryptographically strong random number generators (RNGs). If you are using these RNGs to create passwords or secret tokens, use...	Static analysis (opengrep)
medium	`opengrep/java.lang.security.audit.crypto.weak-random`	java8/src/main/java/com/shekhargulati/ninetynine_problems/_01_lists/P23.java:22	Detected use of the functions `Math.random()` or `java.util.Random()`. These are both not cryptographically strong random number generators (RNGs). If you are using these RNGs to create passwords or secret tokens, use...	Static analysis (opengrep)
medium	`opengrep/scala.lang.security.audit.insecure-random`	scala/src/main/scala/com/shekhargulati/ninetynine_problems/_01_lists/P23.scala:3	Flags the use of a predictable random value from `scala.util.Random`. This can lead to vulnerabilities when used in security contexts, such as in a CSRF token, password reset token, or any other secret value. To fix this, use...	Static analysis (opengrep)

Tools and coverage

Every analyzer that ran on this commit. A failed or skipped tool is a coverage gap: its share of the score is left out and the coverage figure drops.

Analyzer	Pillar	Status	Version	Findings	Note
AI tool configuration	AI provenance	ok	`signatures-v1`	0
Explicit AI attribution	AI provenance	ok	`signatures-v1`	0
Release velocity	AI provenance	skipped	`—`	0
Coding style	AI provenance	ok	`—`	0
Commit velocity	AI provenance	ok	`prov-4`	0
Complexity (lizard)	Code quality	ok	`lizard 1.25.1`	0
Documentation	Code quality	ok	`—`	0
Duplication (jscpd)	Code quality	ok	`repotrust-dup-w6`	0
Lint	Code quality	ok	`opengrep 1.33.1; rules f1d2b562b414`	0
Tests and CI	Code quality	ok	`—`	0
Type safety	Code quality	skipped	`—`	0
CI workflows (zizmor)	Security	ok	`zizmor 1.32.0`	4
Dependencies (osv-scanner)	Security	ok	`osv-scanner version: 2.7.1`	0
Release downloads	Security	ok	`—`	0
Security posture	Security	ok	`—`	0
Package registries	Security	skipped	`—`	0	no registry dependencies declared
Static analysis (opengrep)	Security	ok	`opengrep 1.33.1; rules f1d2b562b414`	3
OpenSSF Scorecard	Security	skipped	`—`	0	no published OpenSSF Scorecard result for this repo
Secrets (gitleaks)	Security	ok	`gitleaks 8.30.1`	0

Score history

Scores from different scoring versions aren't directly comparable.

Scored	Commit	Scoring	AI provenance	Quality	Security
2026-11-14	`7e120de6259b`	`prov-5+qual-2+sec-2`	0%	89	81
2026-11-14	`7e120de6259b`	`prov-4+qual-2+sec-2`	0%	89	81

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Maintainers can show these in a README. Badges update when the repository is re-scored.

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Full text report

Repository: https://github.com/shekhargulati/99-problems
Commit: 7e120de6259b408eed8d1d17538b561a01bbfb9a
Generated: 2026-11-14T14:52:07+00:00
Scorer 0.1.0, scoring prov-5+qual-2+sec-2, report schema v2

Scores

Pillar	Score	Signal	Confidence	Coverage
AI provenance (estimated AI-generated share)	0	none-detected	65%	100%
Code quality	89	strong	90%	100%
Security	81	adequate	85%	100%

AI provenance

No AI attribution or AI-consistent velocity signals detected.

Explicitly attributed share (lower bound): 0.0%
Unattributed share in AI-consistent velocity bursts: 0.0%
Estimated AI-generated share: 0.0%

Month	Lines added	Attributed to AI
2015-11	677	0%
2015-12	2,580	0%
2016-01	1,234	0%
2016-02	1,542	0%
2016-03	790	0%
2016-04	407	0%
2016-07	3	0%
2016-11	57	0%
2017-09	8	0%

AI provenance describes how code was produced; it is not a quality judgment. Unless attribution is explicit, these are signals consistent with AI generation, not proof. Squash/rebase workflows, imported code, and rewritten history reduce accuracy.

Code quality

Code quality is strong: test-to-source ratio 0.89, CI runs tests; 0% of function code in complex or long functions; 1% duplicated lines. Weakest area: docs.

Area	Score
Complexity (lizard)	100
Duplication	92
Code smells (Opengrep)	100
Tests and CI	90
Documentation	45
Type safety	n/a
Process (Scorecard review/maintenance)	n/a

Functions: 249; mean complexity 2.2, 90th percentile 5; 0 complex and 0 long functions
Duplicated lines: 1.5% of 1,775 compared
Tests: 3,138 test lines for 3,536 source lines (ratio 0.89); CI test commands: mvn test; 83% of recent source commits also change tests
Docs missing or thin: readme, contributing, changelog

Security

Security posture is adequate: 2 high-severity workflow issues. Weakest area: posture.

Area	Score
Secrets (gitleaks, tree + history)	100
Static analysis (Opengrep)	93
Vulnerable dependencies (OSV)	100
CI workflows (zizmor)	63
Posture (policy, updates, signing, lockfiles)	0
OpenSSF Scorecard	n/a

Posture checks passed: lockfiles; missing: security policy, dependency updates, signed commits

Top findings

Severity	Finding	Location
high	`zizmor/unpinned-uses`: unpinned action reference [confidence high]	.github/workflows/ci.yml:18
high	`zizmor/unpinned-uses`: unpinned action reference [confidence high]	.github/workflows/ci.yml:20
medium	`opengrep/java.lang.security.audit.crypto.weak-random`: Detected use of the functions `Math.random()` or `java.util.Random()`. These are both not cryptographically strong random number generators (RNGs). If you are using these RNGs to create passwords or secret tokens, use `java.security.SecureRandom` instead. [confidence low]	java8/src/main/java/com/shekhargulati/ninetynine_problems/_01_lists/P23.java:15
medium	`opengrep/java.lang.security.audit.crypto.weak-random`: Detected use of the functions `Math.random()` or `java.util.Random()`. These are both not cryptographically strong random number generators (RNGs). If you are using these RNGs to create passwords or secret tokens, use `java.security.SecureRandom` instead. [confidence low]	java8/src/main/java/com/shekhargulati/ninetynine_problems/_01_lists/P23.java:22
medium	`opengrep/scala.lang.security.audit.insecure-random`: Flags the use of a predictable random value from `scala.util.Random`. This can lead to vulnerabilities when used in security contexts, such as in a CSRF token, password reset token, or any other secret value. To fix this, use java.security.SecureRandom instead. [confidence low]	scala/src/main/scala/com/shekhargulati/ninetynine_problems/_01_lists/P23.scala:3
medium	`zizmor/artipacked`: credential persistence through GitHub Actions artifacts [confidence low]	.github/workflows/ci.yml:18
medium	`zizmor/excessive-permissions`: overly broad permissions [confidence medium]	.github/workflows/ci.yml:7

Static signals only: the scorer never runs the project's code. Secret findings are pattern matches that were not verified, and secret values are never stored.

Repository profile

Source lines: 3,536; test lines: 3,138

Language	Lines
Java	4,031
Scala	2,643