Improving Program Matching to Automatically Repair Introductory Programs
Integrity signals
Registry
Cites
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Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Traditional semantic APR techniques based on Formal Methods are often slow and may struggle when the correct implementation diverges significantly from the erroneous one.
“Traditional semantic APR techniques based on Formal Methods (FM), while providing high-quality fixes, are often slow and may struggle when the correct implementation diverges significantly from the erroneous one (Contractor and Rivero 2022).”
From Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization (2025) · cites this paper as Contractor and Rivero 2022
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Counterexample Guided Program Repair Using Zero-Shot Learning and MaxSAT-based Fault Localization
Orvalho, P., Janota, M., & Manquinho, V. (2025) · arXiv · doi:10.48550/arxiv.2502.07786 · Cited by 4 · see citing works
- Authors
- Contractor, M. R., & Rivero, C. R.
- ORCID
- Rivero, Carlos R.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2022
- Pages
- 323-335
- ISSN
- 0302-9743
- 1611-3349
- Cited by
- 5
- References
- 0
- Language
- en
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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