Helping end-user programmers find and fix performance problems in visual code

Graduation date: 2015End-user programmers often struggle to create programs that run quickly and effectively, which can be a major deterrent in completing their tasks as desired. Current research has primarily focused on catching user mistakes, such as errors or misused formulas. However, end users deal with issues other than just correctness. In particular, there are very few tools and very little research aimed at helping end-user programmers to find and fix performance issues. This thesis details three specific methods: detecting code smells, combining static code smell detection with profiling information, and the semi-automatic or tool-guided removal of code smells. These methods have been prototyped to interface with the Labview IDE with the support of National Instruments. These methods have been evaluated through several user studies to ensure that they are effective and helpful