As software continues eating the world and growing in size, the number of bugs in the wild keeps increasing.
Static analysis can uncover a multitude of bugs in a reasonable time frame compared to its dynamic equivalent
but is plagued by other issues such as high false-positive alert rates and unclear calls to action, making it
underutilized considering the benefits it can bring with its bug-finding abilities. This thesis aims to reduce
the shortcomings of static analysis by implementing and evaluating a template-based approach of automatically
repairing bugs found by static analysis. The approach is evaluated by automatically creating and submitting
patches containing bug fixes to open-source projects already utilizing static analysis. The results show that
the approach and developed tool are valuable and do increase the number of static bugs repaired. Two possible
ways of integrating the created tool into existing developer workflows are prototyped and a comparison with a
similar tool is performed to showcase the different approaches’ differences, strengths and weaknesses