Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  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  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.  performed a case study involving an industrial software system at IBM and found three distinct alert signatures that could be applied to the system.  found that 50% of the field failures reported since the last static analysis run could be discovered by examining the 10% of the files and static analysis alerts indicated by these three alert signatures. The remaining failures re either not detected by a signature which could be an indication of a new type of error in the field, or they re on areas of the code where no static analysis alerts re detected.
['Mark Sherriff', 'Sarah Smith Heckman', 'J. Michael Lake', 'Laurie Williams']
I am writing a research paper on a idea Using groupings of static analysis alerts to identify files likely to contain field failures
[{"from": "human", "value": "I am writing a research paper on a idea Using groupings of static analysis alerts to identify files likely to contain field failures"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  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  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.  performed a case study involving an industrial software system at IBM and found three distinct alert signatures that could be applied to the system.  found that 50% of the field failures reported since the last static analysis run could be discovered by examining the 10% of the files and static analysis alerts indicated by these three alert signatures. The remaining failures re either not detected by a signature which could be an indication of a new type of error in the field, or they re on areas of the code where no static analysis alerts re detected."}]