In addition, it would also allow researchers to identify the state-of-the-art FL techniques on which to build newly proposed FL solutions. Comparison to commonly used baseline techniques would facilitate cross-comparison and ultimately, may enable developers to choose an appropriate FL technique for a given software maintenance task. However, this proliferation of FLTs means it can be difficult to compare across these techniques (Razzaq et al. ( 2015), Bassett and Kraft ( 2013), and Ali et al. ( 2013), Heck and Zaidman ( 2014), Cleary et al. ( 2013), Mahmoud and Bradshaw ( 2015), Kagdi et al. Also, original FLTs have been gradually refined with the intention of enhancing their efficacy. 2009) tailored to different software maintenance activities (Cornelissen et al. 2008 Marcus and Maletic 2003 Marcus et al. From these early efforts, the number of structural and textual analysis approaches for FL has expanded dramatically and many new FLTs have been developed (Chen and Rajlich 2000 Antoniol et al. ( 2002), who used an Information Retrieval (IR) technique (textual analysis) to support the feature location task. ( 2001), who used program traces gathered during dynamic analysis, and Antoniol et al. Notably influential works include Chen and Rajlich ( 2000), whose technique achieved FL through the examination of the software’s structure via a dependency graph, Wilde et al. 2013 Rubin and Chechik 2013 Cornelissen et al. ![]() Since the 2000s, hundreds of articles to address the task of feature location have been published in software engineering venues (Razzaq et al. Feature Location (FL) concerns itself with the location of feature-related, source code elements. Finally, the results suggest that the performance of FLTs partially depends on system/benchmark characteristics, in addition to the FLTs themselves.Ī feature is an observable functionality in a software system that can be triggered by the user (Eisenbarth et al. By presenting the relative performances of baseline techniques this paper facilitates empirical cross-comparison of existing and future FLTs. Results of the case studies suggest that different baseline techniques perform differently and that VSM-Lucene and LSI-Matlab performed better than other implementations. These baseline techniques are assessed in twelve case studies to rank their performance. This paper moves towards standardizing FLT comparability by assessing eight baseline techniques in an empirical design that addresses these confounding factors. But evaluation across FLTs is confounded by empirical designs that incorporate different FL goals and evaluation criteria. In order to relate the performance of FLTs compared against different baseline techniques, these compare-to techniques should be evaluated against each other. To compare FLTs, an open, standard set of non-subjective, reproducible “compare-to” FLT techniques (baseline techniques) should be used for evaluation. Considering its key role in software maintenance, a vast array of automated and semi-automated Feature Location Techniques (FLTs) have been proposed. ![]() Feature Location (FL) aims to locate observable functionalities in source code.
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