Using groupings of static analysis alerts to identify files likely to contain field failures

In this paper, we propose a technique for leveraging historical field failure records in conjunction with automated static analysis alerts to determine which alerts or sets of alerts are predictive of a field failure. Our technique uses singular value decomposition to generate groupings of static analysis alert types, which we call alert signatures, that have been historically linked to field failure-prone files in previous releases of a software system. The signatures can be applied to sets of alerts from a current build of a software system. Files that have a matching alert signature are identified as having similar static analysis alert characteristics to files with known field failures in a previous release of the system. We performed a case study involving an industrial software system at IBM and found three distinct alert signatures that could be applied to the system. We found that 50% of the field failures reported since the last static analysis run could be discovered by exam...

• Type: Conference
• Year: 2007
• Where: SIGSOFT
• Authors: Mark Sherriff, Sarah Smith Heckman, J. Michael Lake, Laurie A. Williams
• Keywords: Keywords Static Analysis, SIGSOFT 2007, Similar Static Analysis, Software Engineering, Static Analysis Alerts