Leaderboard github.com
astorfi/TensorFlow-World
:earth_americas: Simple and ready-to-use tutorials for TensorFlow
AI provenance
0%
none-detected
- Confidence
- 65%
- Coverage
- 100%
Estimated share of AI-generated code. Explicit attribution is a lower bound.
Code quality
65/100
weak
- Confidence
- 90%
- Coverage
- 100%
Complexity, duplication, lint density, tests, CI, docs and review process.
Security
87/100
strong
- Confidence
- 85%
- Coverage
- 100%
Secrets, static analysis, vulnerable dependencies, CI and supply-chain posture.
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)0.45
Lines added per month all AI-attributed share
- 2017-039,753 · 0% AI
- 2017-041,161 · 0% AI
- 2017-0570 · 0% AI
- 2017-062,883 · 0% AI
- 2017-070 · 0% AI
- 2017-095 · 0% AI
- 2017-101 · 0% AI
- 2017-110 · 0% AI
- 2018-1099 · 0% AI
- 2018-110 · 0% AI
- 2019-010 · 0% AI
- 2019-050 · 0% AI
- 2020-030 · 0% AI
- 2020-040 · 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
- 639
- effective_loc
- 13,972
- tools_detected
- 0
AI tool configurationok
- artifacts
- 0
- tools_configured
- 0
- workflow_agents
- 0
Commit velocityok
- excluded_import_loc
- 5,632
- flagged_loc
- 0
- flagged_loc_share
- 0.0%
- flagged_units
- 0
- max_loc_per_hour
- 886.96
- measured_loc
- 7,816
- median_loc_per_hour
- 82.86
- pr_timed_units
- 0
- pre_ai_era_burst_loc
- 3,708
- pre_ai_era_bursts
- 1
- pre_ai_era_measured_loc
- 7,816
- work_units
- 34
Release velocityskipped
Coding styleok1 item
- count:assistant_voice
- 0
- count:emoji_in_code
- 0
- count:narrated_steps
- 1
- count:placeholder
- 0
- files:assistant_voice
- 0
- files:emoji_in_code
- 0
- files:narrated_steps
- 1
- files:placeholder
- 0
- index
- 0.45
- lines_scanned
- 2,210
- per_kloc:assistant_voice
- 0
- per_kloc:emoji_in_code
- 0
- per_kloc:narrated_steps
- 0.45
- per_kloc:placeholder
- 0
Code quality
65 weak
Code quality is weak: test-to-source ratio 0.22, no CI test run detected; 0% of function code in complex or long functions; 24% duplicated lines. Weakest area: duplication.
How the score is built
- Complexity100
- Duplication24
- Lint and smells67
- Tests and CI58
- Documentation80
- Type safety40
- Review processnot measured
Evidence by analyzer
Complexity (lizard)ok
- complex_functions
- 0
- function_nloc
- 255
- functions
- 28
- long_functions
- 0
- many_param_functions
- 0
- mean_ccn
- 1.57
- p90_ccn
- 4
- risky_nloc_share
- 0.0%
Duplication (jscpd)ok6 items
- 6+ duplicated lines: codes/2-basics_in_machine_learning/logistic_regression/code/logistic_regression.py:33 and codes/3-neural_networks/convolutional-neural-network/code/train_classifier.py:33
- 6+ duplicated lines: codes/2-basics_in_machine_learning/logistic_regression/code/logistic_regression.py:120 and codes/3-neural_networks/multi-layer-perceptron/code/train_mlp.py:101
- 6+ duplicated lines: codes/2-basics_in_machine_learning/logistic_regression/code/logistic_regression.py:234 and codes/3-neural_networks/convolutional-neural-network/code/train_evaluation.py:68
- 6+ duplicated lines: codes/3-neural_networks/convolutional-neural-network/code/train.sh:4 and codes/3-neural_networks/multi-layer-perceptron/code/train.sh:4
- 6+ duplicated lines: codes/3-neural_networks/convolutional-neural-network/code/train_classifier.py:20 and codes/3-neural_networks/multi-layer-perceptron/code/train_mlp.py:17
- 6+ duplicated lines: codes/3-neural_networks/convolutional-neural-network/code/train_evaluation.py:83 and codes/3-neural_networks/multi-layer-perceptron/code/train_mlp.py:262
- compared_lines
- 1,612
- duplicated_lines
- 386
- duplicated_share
- 23.9%
- files
- 26
Lintok
- category:correctness
- 2
- category:maintainability
- 3
- findings
- 5
- scanned_lines
- 2,210
- weighted_findings
- 3.50
Tests and CIok2 items
- CI config: .travis.yml
.travis.yml - CI runs linters (flake8)
- check:ci_present
- yes
- check:ci_runs_lint
- yes
- check:ci_runs_tests
- no
- check:has_tests
- yes
- check:test_ratio
- no
- check:tests_cochange
- no
- ci_files
- 1
- cochange_commits
- 47
- cochange_share
- 6.4%
- source_lines
- 2,210
- test_lines
- 480
- test_ratio
- 0.22
Documentationok3 items
- README.rst
README.rst - LICENSE
LICENSE - CONTRIBUTING.rst
CONTRIBUTING.rst
- check:changelog
- no
- check:contributing
- yes
- check:license
- yes
- check:readme
- yes
- readme_lines
- 275
Type safetyok
- check:low_escape_density
- yes
- check:strict_config
- no
- escapes
- 0
- escapes_per_kloc
- 0
Security
87 strong
Security posture is strong: no high-impact findings. Weakest area: posture.
How the score is built
- Secrets100
- Static analysis (SAST)100
- Vulnerable dependencies100
- CI workflowsnot measured
- Security posture0
- OpenSSF Scorecardnot measured
Evidence by analyzer
OpenSSF Scorecardskipped
no published OpenSSF Scorecard result for this repo
Package registriesok
- checked
- 9
- declared
- 9
- lookup_errors
- 0
- missing
- 0
- recent
- 0
Secrets (gitleaks)ok
- secrets_current
- 0
- secrets_history
- 0
- secrets_low_confidence
- 0
- secrets_nonprod
- 0
Static analysis (opengrep)ok
- findings
- 0
- findings_high
- 0
- findings_low
- 0
- findings_medium
- 0
- parse_errors
- 0
- scanned_lines
- 2,210
- weighted_findings
- 0
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)skipped
Security postureok
- check:dependency_updates
- no
- check:lockfiles
- yes
- check:security_policy
- no
- check:signed_commits
- no
- signed_commit_share
- 6.0%
- unpinned_manifests
- 0
Release downloadsok
- binary_assets
- 0
- signals
- 0
- suspicious
- 0
Findings
3 medium2 low
5 findings
| Severity | Rule | Location | Message | Tool |
|---|---|---|---|---|
| medium | opengrep/python.lang.maintainability.is-function-without-parentheses |
codes/2-basics_in_machine_learning/linear_svm/code/linear_svm.py:132 | Is "is_evaluation" a function or an attribute? If it is a function, you may have meant FLAGS.is_evaluation() because FLAGS.is_evaluation is always true. | Lint |
| medium | opengrep/python.lang.maintainability.is-function-without-parentheses |
codes/3-neural_networks/convolutional-neural-network/code/train_classifier.py:142 | Is "is_training" a function or an attribute? If it is a function, you may have meant FLAGS.is_training() because FLAGS.is_training is always true. | Lint |
| medium | opengrep/python.lang.maintainability.is-function-without-parentheses |
codes/3-neural_networks/convolutional-neural-network/code/train_classifier.py:146 | Is "is_training" a function or an attribute? If it is a function, you may have meant FLAGS.is_training() because FLAGS.is_training is always true. | Lint |
| low | opengrep/bash.lang.correctness.unquoted-variable-expansion-in-command |
codes/3-neural_networks/convolutional-neural-network/code/script/evaluation.sh:9 | Variable expansions must be double-quoted so as to prevent being split into multiple pieces according to whitespace or whichever separator is specified by the IFS variable. If you really wish to split the variable's contents, you may... | Lint |
| low | opengrep/bash.lang.correctness.unquoted-variable-expansion-in-command |
codes/3-neural_networks/convolutional-neural-network/code/script/train.sh:9 | Variable expansions must be double-quoted so as to prevent being split into multiple pieces according to whitespace or whichever separator is specified by the IFS variable. If you really wish to split the variable's contents, you may... | Lint |
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 | 5 | |
| Tests and CI | Code quality | ok | — | 0 | |
| Type safety | Code quality | ok | — | 0 | |
| CI workflows (zizmor) | Security | skipped | — | 0 | |
| 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 | ok | — | 0 | |
| Static analysis (opengrep) | Security | ok | opengrep 1.33.1; rules f1d2b562b414 | 0 | |
| 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 | 70d92f6cbee2 | prov-5+qual-2+sec-2 | 0% | 65 | 87 |
| 2026-11-14 | 70d92f6cbee2 | prov-4+qual-2+sec-2 | 0% | 65 | 87 |
Full text report
- Repository: https://github.com/astorfi/TensorFlow-World
- Commit:
70d92f6cbee2d8ad911b84d370dffc1bf90bfa6b - Generated: 2026-11-14T14:52:02+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 | 65 | weak | 90% | 100% |
| Security | 87 | strong | 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%
-
Stylometry index: 0.45 per 1,000 lines (narrated steps 1, placeholders 0, assistant phrasing 0, emoji 0). Reported as a signal, not scored.
| Month | Lines added | Attributed to AI |
|---|---|---|
| 2017-03 | 9,753 | 0% |
| 2017-04 | 1,161 | 0% |
| 2017-05 | 70 | 0% |
| 2017-06 | 2,883 | 0% |
| 2017-09 | 5 | 0% |
| 2017-10 | 1 | 0% |
| 2018-10 | 99 | 0% |
Evidence
- step-by-step narration comment: # Step 8: train the model (codes/2-basi)
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 weak: test-to-source ratio 0.22, no CI test run detected; 0% of function code in complex or long functions; 24% duplicated lines. Weakest area: duplication.
| Area | Score |
|---|---|
| Complexity (lizard) | 100 |
| Duplication | 24 |
| Code smells (Opengrep) | 67 |
| Tests and CI | 58 |
| Documentation | 80 |
| Type safety | 40 |
| Process (Scorecard review/maintenance) | n/a |
- Functions: 28; mean complexity 1.6, 90th percentile 4; 0 complex and 0 long functions
- Duplicated lines: 23.9% of 1,612 compared
- Tests: 480 test lines for 2,210 source lines (ratio 0.22); CI test commands: none detected; 6% of recent source commits also change tests
- Docs missing or thin: changelog
Security
Security posture is strong: no high-impact findings. Weakest area: posture.
| Area | Score |
|---|---|
| Secrets (gitleaks, tree + history) | 100 |
| Static analysis (Opengrep) | 100 |
| Vulnerable dependencies (OSV) | 100 |
| CI workflows (zizmor) | n/a |
| Posture (policy, updates, signing, lockfiles) | 0 |
| OpenSSF Scorecard | n/a |
- Posture checks passed: lockfiles; missing: security policy, dependency updates, signed commits
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: 2,210; test lines: 480
| Language | Lines |
|---|---|
| Python | 2,616 |
| Shell | 74 |