2 research outputs found
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Utility and accuracy of smell-driven performance analysis for end-user programmers
This paper proposes a technique, called Smell-driven performance analysis (SDPA), which automatically provides situated explanations within a visual dataflow language IDE to help end-user programmers to overcome performance problems without leaving the visual dataflow paradigm. An experiment showed SDPA increased end-user programmers’ success rates at finding performance problems and decreased the time required for finding solutions. Another study, based on using SDPA to analyze a corpus of example end-user programs, revealed that it is usually accurate at identifying performance problems. Based on these results, we conclude that SDPA provides a reliable basis for helping end-user programmers to troubleshoot performance problems, as well as a potential foundation for future work aimed at training users and at aiding code reuse.Keywords: End-user programming, Visual language, PerformanceKeywords: End-user programming, Visual language, Performanc
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Helping end-user programmers find and fix performance problems in visual code
End-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