Matches in SemOpenAlex for { <https://semopenalex.org/work/W2971474967> ?p ?o ?g. }
Showing items 1 to 72 of
72
with 100 items per page.
- W2971474967 abstract "While there is a wide variety of both open source and proprietary source code static analyzers available in the market, each of them usually performs better in a small set of problems, making it hard to choose one single tool to rely on when examining a program looking for bugs in the source code. Combining the analysis of different tools may reduce the number of false negatives, but yields a corresponding increase in the absolute number of false positives (which is already high for many tools). A possible solution, then, is to filter these results to identify the issues least likely to be false positives. In this study, we post-analyze the reports generated by three tools on synthetic test cases provided by the US National Institute of Standards and Technology. In order to make our technique as general as possible, we limit our data to the reports themselves, excluding other information such as change histories or code metrics. The features extracted from these reports are used to train a set of decision trees using AdaBoost to create a stronger classifier, achieving 0.8 classification accuracy (the combined false positive rate from the used tools was 0.61). Finally, we use this classifier to rank static analyzer alarms based on the probability of a given alarm being an actual bug in the source code." @default.
- W2971474967 created "2019-09-12" @default.
- W2971474967 creator A5030116148 @default.
- W2971474967 creator A5032725260 @default.
- W2971474967 creator A5069259459 @default.
- W2971474967 creator A5083465964 @default.
- W2971474967 date "2019-08-20" @default.
- W2971474967 modified "2023-10-01" @default.
- W2971474967 title "Ranking warnings from multiple source code static analyzers via ensemble learning" @default.
- W2971474967 cites W1912598576 @default.
- W2971474967 cites W1985048544 @default.
- W2971474967 cites W1988918904 @default.
- W2971474967 cites W2020841721 @default.
- W2971474967 cites W2021616144 @default.
- W2971474967 cites W2025411198 @default.
- W2971474967 cites W2060404290 @default.
- W2971474967 cites W2097336021 @default.
- W2971474967 cites W2100553995 @default.
- W2971474967 cites W2119648923 @default.
- W2971474967 cites W2130243914 @default.
- W2971474967 cites W2149598089 @default.
- W2971474967 cites W2168411647 @default.
- W2971474967 cites W2561266335 @default.
- W2971474967 cites W2743201390 @default.
- W2971474967 cites W2999074369 @default.
- W2971474967 doi "https://doi.org/10.1145/3306446.3340828" @default.
- W2971474967 hasPublicationYear "2019" @default.
- W2971474967 type Work @default.
- W2971474967 sameAs 2971474967 @default.
- W2971474967 citedByCount "5" @default.
- W2971474967 countsByYear W29714749672020 @default.
- W2971474967 countsByYear W29714749672021 @default.
- W2971474967 crossrefType "proceedings-article" @default.
- W2971474967 hasAuthorship W2971474967A5030116148 @default.
- W2971474967 hasAuthorship W2971474967A5032725260 @default.
- W2971474967 hasAuthorship W2971474967A5069259459 @default.
- W2971474967 hasAuthorship W2971474967A5083465964 @default.
- W2971474967 hasConcept C119857082 @default.
- W2971474967 hasConcept C154945302 @default.
- W2971474967 hasConcept C177264268 @default.
- W2971474967 hasConcept C189430467 @default.
- W2971474967 hasConcept C199360897 @default.
- W2971474967 hasConcept C2776760102 @default.
- W2971474967 hasConcept C41008148 @default.
- W2971474967 hasConcept C43126263 @default.
- W2971474967 hasConcept C45942800 @default.
- W2971474967 hasConceptScore W2971474967C119857082 @default.
- W2971474967 hasConceptScore W2971474967C154945302 @default.
- W2971474967 hasConceptScore W2971474967C177264268 @default.
- W2971474967 hasConceptScore W2971474967C189430467 @default.
- W2971474967 hasConceptScore W2971474967C199360897 @default.
- W2971474967 hasConceptScore W2971474967C2776760102 @default.
- W2971474967 hasConceptScore W2971474967C41008148 @default.
- W2971474967 hasConceptScore W2971474967C43126263 @default.
- W2971474967 hasConceptScore W2971474967C45942800 @default.
- W2971474967 hasLocation W29714749671 @default.
- W2971474967 hasOpenAccess W2971474967 @default.
- W2971474967 hasPrimaryLocation W29714749671 @default.
- W2971474967 hasRelatedWork W2380602769 @default.
- W2971474967 hasRelatedWork W3013699712 @default.
- W2971474967 hasRelatedWork W4200409985 @default.
- W2971474967 hasRelatedWork W4281757034 @default.
- W2971474967 hasRelatedWork W4285046548 @default.
- W2971474967 hasRelatedWork W4285741730 @default.
- W2971474967 hasRelatedWork W4292969247 @default.
- W2971474967 hasRelatedWork W4311847748 @default.
- W2971474967 hasRelatedWork W4312241010 @default.
- W2971474967 hasRelatedWork W4313488044 @default.
- W2971474967 isParatext "false" @default.
- W2971474967 isRetracted "false" @default.
- W2971474967 magId "2971474967" @default.
- W2971474967 workType "article" @default.