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Predicting accurate and actionable static analysis warnings
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Applied Linear Statistical Models
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Prioritizing Warning Categories by Analyzing Software History
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Correlation exploitation in error ranking
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Mining metrics to predict component failures
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Tracking defect warnings across versions
inferredcites →https://doi.org/10.1145/1146238.1146245openalex-snapshot
Experimental program analysis
inferredcites →https://doi.org/10.1145/1146238.1146246openalex-snapshot
Looking for bugs in all the right places
inferredcites →https://doi.org/10.1145/1251535.1251536openalex-snapshot
Evaluating static analysis defect warnings on production software
inferredcites →https://doi.org/10.1145/1273463.1273493openalex-snapshot
Automating algorithms for the identification of fault-prone files
inferredcites →https://doi.org/10.1145/1287624.1287633openalex-snapshot
Which warnings should I fix first?
inferredcites →https://doi.org/10.1145/1349332.1349339openalex-snapshot
Adaptively ranking alerts generated from automated static analysis
inferredcites →https://doi.org/10.5860/choice.50-5018openalex-snapshot
Experimentation in software engineering
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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