Home/Compare/CodeRL vs self-repair

Comparison

CodeRL vs self-repair

Verdict

Pick CodeRL if codeRL is an advanced tool that uses pretrained models and deep reinforcement learning to generate code; pick self-repair if self-repair provides tools to replicate research experiments on code generation systems self-reparation techniques.

Markdown twin · CodeRL alternatives · self-repair alternatives

GraphCanon updated 2w

CodeRL logo

CodeRL

salesforce/CodeRL

574pushed Jun 2, 2026
vs
self-repair logo

self-repair

theoxo/self-repair

15pushed May 2, 2024

Trust & integrity

SignalCodeRLself-repair
Maintenance
Steady (63d since push)
As of 2w · github_public_v1
Archived (825d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 2w · github_public_v1
Not a fork · Personal account
As of 2w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
No published findings from this source as of 2026-07-11
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

CodeRL
CodeRL: Combines pretrained models and reinforcement learning for code generation.
self-repair
Supports research on self-repair mechanisms for code generation

Stars

CodeRL
574
self-repair
15

Forks

CodeRL
69
self-repair
3

Open issues

CodeRL
42
self-repair
1

Language

CodeRL
Python
self-repair
Python

Adopt for

CodeRL
CodeRL is an advanced tool that uses pretrained models and deep reinforcement learning to generate code.
self-repair
Self-repair provides tools to replicate research experiments on code generation systems self-reparation techniques.

Persona

CodeRL
-
self-repair
-

Runtime

CodeRL
-
self-repair
-

License

CodeRL
BSD-3-Clause
self-repair
-

Last pushed

CodeRL
Jun 2, 2026
self-repair
May 2, 2024

Categories

CodeRL
Developer Tools, Model Training
self-repair
Developer Tools

Trust and health

Maintenance

CodeRL
Steady (60%)
self-repair
Archived (8%)

Days since push

CodeRL
63d
self-repair
825d

Archived on GitHub

CodeRL
No
self-repair
Yes

Open issues (now)

CodeRL
42
self-repair
1

Owner type

CodeRL
Organization
self-repair
User

OSV dependency advisories

CodeRL
Published findings
self-repair
No published findings from this source as of 2026-07-11

Full report

self-repair
Trust report

Shared compatibility

  • Python · CodeRL: Python runtime · self-repair: Python runtime

Choose CodeRL if…

  • Tags unique to CodeRL: ai, codegeneration, languagemodel, machinelearning.
  • Also covers Model Training.
  • When you need to generate complex and context-aware code snippets utilizing the latest in reinforcement learning techniques.

When NOT to use CodeRL

  • Avoid if your project requires only simple, quick code generation without deep reinforcement learning support.
  • Do not use if compatibility with versions of the Hugging Face transformers library other than 4.16.1 is critical to avoid potential issues.

Choose self-repair if…

  • Tags unique to self-repair: code-repair, experiments replication, python, research-tools.
  • When aiming to replicate specific experimental data from the ICLR 2024 paper on self-repair in code generation
  • Leaner open-issue backlog (1).

When NOT to use self-repair

  • For creating entirely new datasets or conducting large-scale human studies, as this repository focuses on replicating existing experiments
  • When the internal dependencies or incomplete code functions such as exec_sample in APPS are critical for your application without modification

Explore

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: CodeRL 574 · self-repair 15 (synced Aug 5, 2026).

Common questions

What is the difference between CodeRL and self-repair?
CodeRL: CodeRL: Combines pretrained models and reinforcement learning for code generation.. self-repair: Supports research on self-repair mechanisms for code generation. See the comparison table for live GitHub stats and shared categories.
When should I choose CodeRL over self-repair?
Choose CodeRL over self-repair when Tags unique to CodeRL: ai, codegeneration, languagemodel, machinelearning; Also covers Model Training; When you need to generate complex and context-aware code snippets utilizing the latest in reinforcement learning techniques.
When should I choose self-repair over CodeRL?
Choose self-repair over CodeRL when Tags unique to self-repair: code-repair, experiments replication, python, research-tools; When aiming to replicate specific experimental data from the ICLR 2024 paper on self-repair in code generation; Leaner open-issue backlog (1).
When should I avoid CodeRL?
Avoid if your project requires only simple, quick code generation without deep reinforcement learning support. Do not use if compatibility with versions of the Hugging Face transformers library other than 4.16.1 is critical to avoid potential issues.
When should I avoid self-repair?
For creating entirely new datasets or conducting large-scale human studies, as this repository focuses on replicating existing experiments When the internal dependencies or incomplete code functions such as exec_sample in APPS are critical for your application without modification
Is CodeRL or self-repair more popular on GitHub?
CodeRL has more GitHub stars (574 vs 15). Stars measure visibility, not whether either tool fits your constraints.
Are CodeRL and self-repair open source?
Yes - both are open-source projects on GitHub.
Where can I find alternatives to CodeRL or self-repair?
GraphCanon lists graph-backed alternatives at CodeRL alternatives and self-repair alternatives (CodeRL markdown twin, self-repair markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, CodeRL or self-repair?
CodeRL: Steady. self-repair: Archived. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for CodeRL and self-repair?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: CodeRL trust report; self-repair trust report.

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