Utility and accuracy of smell-driven performance analysis for end-user programmers. (February 2015)

• Record Type: Journal Article
• Authors: Chambers, Christopher; Scaffidi, Christopher
• Is Part Of: Journal of visual languages & computing. Volume 26(2015)
• Page Start: 1
• Page End: 14
• Publication Date: 2015-02
• Subjects: End-user programming -- Performance -- Visual language; Visual programming languages (Computer science) -- Periodicals; Visual programming (Computer science) -- Periodicals; Programming languages (Electronic computers) -- Semantics -- Periodicals; Langages de programmation visuelle -- Périodiques; Programmation visuelle -- Périodiques; Langages de programmation -- Sémantique -- Périodiques; Programming languages (Electronic computers) -- Semantics; Visual programming (Computer science); Visual programming languages (Computer science); Periodicals; Electronic journals; 005
• DOI: 10.1016/j.jvlc.2014.10.017
• Languages: English
• ISSNs: 1045-926X

Abstract

Abstract: 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. Highlights: Smell-driven performance analysis (SDPA) finds dataflow performance problems. SDPA provides situated explanations within the visual dataflow language. We present an extended form of the technique that incorporates runtime profiling. In a user study, participants could more easily diagnose performance problems. A second study confirmed that profiling improves accuracy.