Two Techniques For Automated Logging Statement Evolution
Allan Spektor · CUNY Academic Works (City University of New York) · 2020
This thesis presents and explores two techniques for automated logging statement evolution. The first technique reinvigorates logging statement levels to reduce information overload using degree of interest obtained via software repository mining. The second technique converts legacy method calls to deferred execution to achieve performance gains, eliminating unnecessary evaluation overhead.