DynaMine

DynaMine: finding common error patterns by mining software revision histories. A great deal of attention has lately been given to addressing software bugs such as errors in operating system drivers or security bugs. However, there are many other lesser known errors specific to individual applications or APIs and these violations of application-specific coding rules are responsible for a multitude of errors. In this paper we propose DynaMine, a tool that analyzes source code check-ins to find highly correlated method calls as well as common bug fixes in order to automatically discover application-specific coding patterns. Potential patterns discovered through mining are passed to a dynamic analysis tool for validation; finally, the results of dynamic analysis are presented to the user.The combination of revision history mining and dynamic analysis techniques leveraged in DynaMine proves effective for both discovering new application-specific patterns and for finding errors when applied to very large applications with many man-years of development and debugging effort behind them. We have analyzed Eclipse and jEdit, two widely-used, mature, highly extensible applications consisting of more than 3,600,000 lines of code combined. By mining revision histories, we have discovered 56 previously unknown, highly application-specific patterns. Out of these, 21 were dynamically confirmed as very likely valid patterns and a total of 263 pattern violations were found.


References in zbMATH (referenced in 4 articles )

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  1. Ibrahim Abdelaziz, Julian Dolby, James P. McCusker, Kavitha Srinivas: Graph4Code: A Machine Interpretable Knowledge Graph for Code (2020) arXiv
  2. Gómez, Verónica Uquillas; Ducasse, Stéphane; D’Hondt, Theo: Ring: a unifying meta-model and infrastructure for smalltalk source code analysis tools (2012) ioport
  3. Hata, Hideaki; Mizuno, Osamu; Kikuno, Tohru: Fault-prone module detection using large-scale text features based on spam filtering (2010) ioport
  4. Pan, Kai; Kim, Sunghun; Whitehead, E. James: Toward an understanding of bug fix patterns (2009) ioport