PhD defences - Tukaram Muske defended his thesis on postprocessing static analysis alarms


Tukaram Muske has successfully defended a PhD thesis on postprocessing static analysis alarms.


Static analysis, which detects errors in the source code without actually running it, is an important automated program analysis technique to find common programming errors and report on points of interest that could be errors.
Considering the effectiveness and usefulness of static analysis, a wide range of static analysis tools have been developed. However, these tools are known to generate a large number of false alarms. Tukaram Muske has developed alarm postprocessing techniques that significantly reduce the time and effort needed to inspect those alarms manually.
Reducing the number of static analysis alarms is an important challenge that academia and industry are both working on. Reporting fewer alarms by suppressing a subset of alarms is dangerous, because it can lead to missing critical errors. Muske addresses the problem of large numbers of alarms by processing the alarms after they are generated: postprocessing.
The postprocessing techniques designed by Muske work regardless of the static analysis tool in use, and manage to reduce the number of alarms by up to 36% and the time required to automatically eliminate false positives by up to 60%. This could prove an important time and cost savings and enable faster and more accurate response to software errors.

Tukaram Muske has conducted his research at the Tata Research Development and Design Center (Pune, India). He has been supervised by Alexander Serebrenik and Mark van den Brand (Eindhoven University of Technology). The PhD thesis can be found online: