Enhancing Code Quality with Generative AI: Boosting Developer Warning Compliance

--Programmers have long ignored warnings, especially those generated by static analysis tools, due to the potential for false-positives. In some cases, warnings may be indicative of larger issues, but programmers may not understand how a seemingly unimportant warning can grow into a vulnerability. Because these messages tend to be long and confusing, programmers tend to ignore them if they do not cause readily identifiable issues. Large language models can simplify these warnings, explain the gravity of important warnings, and suggest potential fixes to increase developer compliance with fixing warnings. The views expressed in this article are those of the author(s) and do not reflect the official policy or position of the U.S. Naval Academy, Department of the Navy, the Department of Defense, or the U.S. Government. Warning messages generated by compilers and static analysis tools [1] have historically been overlooked and ignored [2].