Codequiry vs Dolos vs MOSS vs JPlag

A clean, objective comparison of the most known code similarity and plagiarism tools — focused on real classroom needs like web scanning, AI‑written code detection, and readable reports.

Feature‑by‑Feature Comparison

Scan the differences across coverage, AI detection, reporting, integrations, and more.

Web & GitHub scanning AI‑written code detection Explainable reports APIs & LMS integrations
Capability Codequiry Dolos JPlag MOSS
Detection approach Multi‑layer similarity + AI heuristics Similarity heuristics Similarity heuristics Token‑based similarity
AI‑written code detection Yes (ChatGPT, Copilot, Claude & more) Limited/No No No
Web & GitHub scanning Yes (40B+ sources, GitHub, Q&A sites) Limited/No No No
Peer‑to‑peer comparison Yes (clustering, collusion signals) Yes Yes Yes
Languages 51+ languages < 10 languages < 10 languages Multiple
Report quality Side‑by‑side diffs, source links, evidence Visual overview + matches Visual matches, similarity scores Basic match listing
LMS/API/CLI API + CLI + LMS options CLI/Local usage typical CLI/Local usage typical CLI
Scalability & speed High throughput, batch processing Depends on local resources Depends on local resources Depends on server slot & code size
Best for Universities, courses, enterprise integrity Research, small cohorts Research, CS courses baseline similarity Baseline similarity checks

Key takeaways

  • Codequiry offers the most complete coverage including web/repo scans, AI‑written code detection, explainable reports, and integrations for real classrooms.
  • Dolos is a useful academic/research tool for similarity but lacks broad web scanning and AI detection, and supports fewer than 10 languages.
  • JPlag is a solid baseline similarity tool for courses and research, but it does not scan the web or detect AI‑generated code, and supports fewer than 10 languages.
  • MOSS is widely known for similarity, but it does not scan the web, and it cannot detect AI‑generated code.