Date of Award

Summer 7-21-2020

Document Type

Thesis

Degree Name

Master of Arts (MA)

Departments/Programs

Computer Science

First Advisor

Raffi Khatchadourian

Second Advisor

Saptarshi Debroy

Academic Program Adviser

Subash Shankar

Abstract

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.

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