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KingJA/LoadSir

A lightweight, good expandability Android library used for displaying different pages like loading, error, empty, timeout or even your custom page when you load a page.(优雅地处理加载中,重试,无数据等)

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  • Java
  • ★ 3,467
  • commit 7ff786c73b01
  • scored 2026-11-14
  • scoring prov-5+qual-2+sec-2

AI provenance

0%

none-detected

Confidence
65%
Coverage
100%

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

Code quality

58/100

weak

Confidence
90%
Coverage
100%

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

Security

77/100

adequate

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 pace0
  • Coding-style index (1.0+ means possible)0.00

Lines added per month all AI-attributed share

  1. 2017-093,893 · 0% AI
  2. 2017-10966 · 0% AI
  3. 2017-1114 · 0% AI
  4. 2017-1222 · 0% AI
  5. 2018-034 · 0% AI
  6. 2019-010 · 0% AI
  7. 2019-08332 · 0% AI
  8. 2020-02197 · 0% AI
  9. 2020-0342 · 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
184
effective_loc
5,470
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
199.00
measured_loc
5,470
median_loc_per_hour
67.39
pr_timed_units
0
pre_ai_era_burst_loc
0
pre_ai_era_bursts
0
pre_ai_era_measured_loc
5,470
work_units
56
Release velocityok
flagged_releases
0
max_loc_per_day
75.50
releases
5
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
2,510
per_kloc:assistant_voice
0
per_kloc:emoji_in_code
0
per_kloc:narrated_steps
0
per_kloc:placeholder
0

Code quality

58 weak

Code quality is weak: test-to-source ratio 0.00, no CI test run detected; 0% of function code in complex or long functions; 11% duplicated lines. Weakest area: testing.

How the score is built

  • Complexity100
  • Duplication51
  • Lint and smells100
  • Tests and CI2
  • Documentation60
  • Type safetynot measured
  • Review processnot measured

Evidence by analyzer

Complexity (lizard)ok
complex_functions
0
function_nloc
1,060
functions
188
long_functions
0
many_param_functions
0
mean_ccn
1.27
p90_ccn
2
risky_nloc_share
0.0%
Duplication (jscpd)ok4 items
compared_lines
1,245
duplicated_lines
140
duplicated_share
11.2%
files
46
Lintok
findings
0
scanned_lines
2,510
weighted_findings
0
Tests and CIok
check:ci_present
no
check:ci_runs_lint
no
check:ci_runs_tests
no
check:has_tests
no
check:test_ratio
no
check:tests_cochange
no
ci_files
0
cochange_commits
71
cochange_share
5.6%
source_lines
2,510
test_lines
0
test_ratio
0
Documentationok2 items
  • README.md README.md
  • docs/changelog.md docs/changelog.md
check:changelog
yes
check:contributing
no
check:license
no
check:readme
yes
readme_lines
273
Type safetyskipped

Security

77 adequate

Security posture is adequate: no high-impact findings. Weakest area: posture.

How the score is built

  • Secrets100
  • Static analysis (SAST)86
  • Vulnerable dependenciesnot measured
  • CI workflowsnot measured
  • 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
2,510
weighted_findings
1.10
Dependencies (osv-scanner)skipped
CI workflows (zizmor)skipped
Security postureok
check:dependency_updates
no
check:lockfiles
yes
check:security_policy
no
check:signed_commits
no
signed_commit_share
0.0%
unpinned_manifests
0
Release downloadsok
binary_assets
0
signals
0
suspicious
0

Findings

3 medium

SeverityRuleLocationMessageTool
medium opengrep/java.android.security.exported_activity app/src/main/AndroidManifest.xml:12 The application exports an activity. Any application on the device can launch the exported activity which may compromise the integrity of your application or its data. Ensure that any exported activities do not have privileged access... Static analysis (opengrep)
medium opengrep/java.lang.security.audit.crypto.weak-random app/src/main/java/sample/kingja/loadsir/target/ConvertorActivity.java:38 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.object-deserialization loadsir/src/main/java/com/kingja/loadsir/callback/Callback.java:103 Found object deserialization using ObjectInputStream. Deserializing entire Java objects is dangerous because malicious actors can create Java object streams with unintended consequences. Ensure that the objects being deserialized are... 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.

AnalyzerPillarStatusVersionFindingsNote
AI tool configurationAI provenanceoksignatures-v10
Explicit AI attributionAI provenanceoksignatures-v10
Release velocityAI provenanceokprov-40
Coding styleAI provenanceok—0
Commit velocityAI provenanceokprov-40
Complexity (lizard)Code qualityoklizard 1.25.10
DocumentationCode qualityok—0
Duplication (jscpd)Code qualityokrepotrust-dup-w60
LintCode qualityokopengrep 1.33.1; rules f1d2b562b4140
Tests and CICode qualityok—0
Type safetyCode qualityskipped—0
CI workflows (zizmor)Securityskipped—0
Dependencies (osv-scanner)Securityskipped—0
Release downloadsSecurityok—0
Security postureSecurityok—0
Package registriesSecurityskipped—0no registry dependencies declared
Static analysis (opengrep)Securityokopengrep 1.33.1; rules f1d2b562b4143
OpenSSF ScorecardSecurityskipped—0no published OpenSSF Scorecard result for this repo
Secrets (gitleaks)Securityokgitleaks 8.30.10

Score history

Scores from different scoring versions aren't directly comparable.

ScoredCommitScoringAI provenanceQualitySecurity
2026-11-147ff786c73b01prov-5+qual-2+sec-20%5877
2026-11-147ff786c73b01prov-4+qual-2+sec-20%5877

Embed a badge

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

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[![RepoTrust quality](https://repotrust.synapticcyber.com/badge/github.com/KingJA/LoadSir/quality.svg)](https://repotrust.synapticcyber.com/r/github.com/KingJA/LoadSir/)
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Full text report
  • Repository: https://github.com/KingJA/LoadSir
  • Commit: 7ff786c73b019997bccdb96a69f68e6c947e384b
  • Generated: 2026-11-14T14:52:00+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 58 weak 90% 100%
Security 77 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
2017-09 3,893 0%
2017-10 966 0%
2017-11 14 0%
2017-12 22 0%
2018-03 4 0%
2019-08 332 0%
2020-02 197 0%
2020-03 42 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 weak: test-to-source ratio 0.00, no CI test run detected; 0% of function code in complex or long functions; 11% duplicated lines. Weakest area: testing.

Area Score
Complexity (lizard) 100
Duplication 51
Code smells (Opengrep) 100
Tests and CI 2
Documentation 60
Type safety n/a
Process (Scorecard review/maintenance) n/a
  • Functions: 188; mean complexity 1.3, 90th percentile 2; 0 complex and 0 long functions
  • Duplicated lines: 11.2% of 1,245 compared
  • Tests: 0 test lines for 2,510 source lines (ratio 0.00); CI test commands: none detected; 6% of recent source commits also change tests
  • Docs missing or thin: license, contributing

Security

Security posture is adequate: no high-impact findings. Weakest area: posture.

Area Score
Secrets (gitleaks, tree + history) 100
Static analysis (Opengrep) 86
Vulnerable dependencies (OSV) n/a
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

Top findings

Severity Finding Location
medium opengrep/java.android.security.exported_activity: The application exports an activity. Any application on the device can launch the exported activity which may compromise the integrity of your application or its data. Ensure that any exported activities do not have privileged access to your application's control plane. [confidence medium] app/src/main/AndroidManifest.xml:12
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] app/src/main/java/sample/kingja/loadsir/target/ConvertorActivity.java:38
medium opengrep/java.lang.security.audit.object-deserialization: Found object deserialization using ObjectInputStream. Deserializing entire Java objects is dangerous because malicious actors can create Java object streams with unintended consequences. Ensure that the objects being deserialized are not user-controlled. If this must be done, consider using HMACs to [confidence low] loadsir/src/main/java/com/kingja/loadsir/callback/Callback.java:103

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: 2,510; test lines: 0
Language Lines
Java 2,510