Matches in SemOpenAlex for { <https://semopenalex.org/work/W4226449842> ?p ?o ?g. }
Showing items 1 to 78 of
78
with 100 items per page.
- W4226449842 abstract "Software Fault Localization refers to the activity of finding code elements (e.g., statements) that are related to a software failure. The state-of-the-art fault localization techniques, however, produce coarse-grained results that can deter manual debugging or mislead automated repair tools. In this work, we focus specifically on the fine-grained identification of code elements (i.e., tokens) that must be changed to fix a buggy program: we refer to it as fix localization. This paper introduces a neural network architecture (named Beep) that builds on AST paths to predict the buggy code element as well as the change action that must be applied to repair a program. Leveraging massive data of bugs and patches within the CoCoNut dataset, we trained a model that was (1) effective in localizing the buggy tokens with the Mean First Rank significantly higher than a statistics based baseline and a machine learning-based baseline, and (2) effective in predicting the repair operators (with the associated buggy code elements) with a Recall@1= 30-45% and the Mean First Rank=7-12 (evaluated by CoCoNut, ManySStuBs4J, and Defects4J datasets). To showcase how fine-grained fix localization can help program repair, we employ it in two repair pipelines where we use either a code completion engine to predict the correct token or a set of heuristics to search for the suitable donor code. A key strength of accurate fix localization for program repair is that it reduces the chance of patch overfitting, a challenge in generate-and-validate automated program repair: both two repair pipelines achieve a correctness ratio of 100%, i.e., all generated patches are found to be correct. Moreover, accurate fix localization helps enhance the efficiency of program repair." @default.
- W4226449842 created "2022-05-05" @default.
- W4226449842 creator A5003679114 @default.
- W4226449842 creator A5027475930 @default.
- W4226449842 creator A5034806491 @default.
- W4226449842 creator A5040326968 @default.
- W4226449842 creator A5080183182 @default.
- W4226449842 creator A5081197883 @default.
- W4226449842 creator A5082835974 @default.
- W4226449842 date "2021-11-15" @default.
- W4226449842 modified "2023-10-16" @default.
- W4226449842 title "Beep: Fine-grained Fix Localization by Learning to Predict Buggy Code Elements" @default.
- W4226449842 hasPublicationYear "2021" @default.
- W4226449842 type Work @default.
- W4226449842 citedByCount "0" @default.
- W4226449842 crossrefType "posted-content" @default.
- W4226449842 hasAuthorship W4226449842A5003679114 @default.
- W4226449842 hasAuthorship W4226449842A5027475930 @default.
- W4226449842 hasAuthorship W4226449842A5034806491 @default.
- W4226449842 hasAuthorship W4226449842A5040326968 @default.
- W4226449842 hasAuthorship W4226449842A5080183182 @default.
- W4226449842 hasAuthorship W4226449842A5081197883 @default.
- W4226449842 hasAuthorship W4226449842A5082835974 @default.
- W4226449842 hasBestOaLocation W42264498421 @default.
- W4226449842 hasConcept C111368507 @default.
- W4226449842 hasConcept C111919701 @default.
- W4226449842 hasConcept C119857082 @default.
- W4226449842 hasConcept C12725497 @default.
- W4226449842 hasConcept C127313418 @default.
- W4226449842 hasConcept C127705205 @default.
- W4226449842 hasConcept C13280743 @default.
- W4226449842 hasConcept C154945302 @default.
- W4226449842 hasConcept C168065819 @default.
- W4226449842 hasConcept C177264268 @default.
- W4226449842 hasConcept C185798385 @default.
- W4226449842 hasConcept C199360897 @default.
- W4226449842 hasConcept C205649164 @default.
- W4226449842 hasConcept C22019652 @default.
- W4226449842 hasConcept C2776760102 @default.
- W4226449842 hasConcept C41008148 @default.
- W4226449842 hasConcept C43126263 @default.
- W4226449842 hasConcept C48145219 @default.
- W4226449842 hasConcept C50644808 @default.
- W4226449842 hasConceptScore W4226449842C111368507 @default.
- W4226449842 hasConceptScore W4226449842C111919701 @default.
- W4226449842 hasConceptScore W4226449842C119857082 @default.
- W4226449842 hasConceptScore W4226449842C12725497 @default.
- W4226449842 hasConceptScore W4226449842C127313418 @default.
- W4226449842 hasConceptScore W4226449842C127705205 @default.
- W4226449842 hasConceptScore W4226449842C13280743 @default.
- W4226449842 hasConceptScore W4226449842C154945302 @default.
- W4226449842 hasConceptScore W4226449842C168065819 @default.
- W4226449842 hasConceptScore W4226449842C177264268 @default.
- W4226449842 hasConceptScore W4226449842C185798385 @default.
- W4226449842 hasConceptScore W4226449842C199360897 @default.
- W4226449842 hasConceptScore W4226449842C205649164 @default.
- W4226449842 hasConceptScore W4226449842C22019652 @default.
- W4226449842 hasConceptScore W4226449842C2776760102 @default.
- W4226449842 hasConceptScore W4226449842C41008148 @default.
- W4226449842 hasConceptScore W4226449842C43126263 @default.
- W4226449842 hasConceptScore W4226449842C48145219 @default.
- W4226449842 hasConceptScore W4226449842C50644808 @default.
- W4226449842 hasLocation W42264498421 @default.
- W4226449842 hasOpenAccess W4226449842 @default.
- W4226449842 hasPrimaryLocation W42264498421 @default.
- W4226449842 hasRelatedWork W1198659 @default.
- W4226449842 hasRelatedWork W12199117 @default.
- W4226449842 hasRelatedWork W13135065 @default.
- W4226449842 hasRelatedWork W15914088 @default.
- W4226449842 hasRelatedWork W16556150 @default.
- W4226449842 hasRelatedWork W302949 @default.
- W4226449842 hasRelatedWork W482614 @default.
- W4226449842 hasRelatedWork W715329 @default.
- W4226449842 hasRelatedWork W728297 @default.
- W4226449842 hasRelatedWork W10637615 @default.
- W4226449842 isParatext "false" @default.
- W4226449842 isRetracted "false" @default.
- W4226449842 workType "article" @default.