Title :
Evidence-Based Analysis and Inferring Preconditions for Bug Detection
Author :
Brand, Daniel ; Buss, Marcio ; Sreedhar, Vugranam C.
Author_Institution :
IBM TJ Watson Res. Center, Yorktown Heights
Abstract :
An important part of software maintenance is fixing software errors and bugs. Static analysis based tools can tremendously help and ease software maintenance. In order to gain user acceptance, a static analysis tool for detecting bugs has to minimize the incidence of false alarms. A common cause of false alarms is the uncertainty over which inputs into a program are considered legal. In this paper we introduce evidence-based analysis to address this problem. Evidence-based analysis allows one to infer legal preconditions over inputs, without having users to explicitly specify those preconditions. We have found that the approach drastically improves the usability of such static analysis tools. In this paper we report our experience with the analysis in an industrial deployment.
Keywords :
software maintenance; bug detection; evidence-based analysis; software maintenance; software tools; static analysis tool; Computer bugs; Information analysis; Law; Legal factors; Libraries; Software debugging; Software maintenance; Software tools; Uncertainty; Usability;
Conference_Titel :
Software Maintenance, 2007. ICSM 2007. IEEE International Conference on
Conference_Location :
Paris
Print_ISBN :
978-1-4244-1256-3
Electronic_ISBN :
1063-6773
DOI :
10.1109/ICSM.2007.4362617