Print Email Facebook Twitter Practical detection of CMS plugin conflicts in large plugin sets Title Practical detection of CMS plugin conflicts in large plugin sets Author Lima, Igor (Federal University of Pernambuco) Barros Cândido, J. (TU Delft Software Engineering; Federal University of Pernambuco) d'Amorim, Marcelo (Federal University of Pernambuco) Date 2020-02-01 Abstract Context: Content Management Systems (CMS), such as WordPress, are a very popular category of software for creating web sites and blogs. These systems typically build on top of plugin architectures. Unfortunately, it is not uncommon that the combined activation of multiple plugins in a CMS web site will produce unexpected behavior. Conflict-detection techniques exist but they do not scale. Objective: This paper proposes PENA, a technique to detect conflicts in large sets of plugins as those present in plugin market places. Method: PENA takes on input a configuration, consisting of a potentially large set of plugins, and reports on output the offending plugin combinations. PENA uses an iterative divide-and-conquer search to explore the large space of plugin combinations and a staged filtering process to eliminate false alarms. Results: We evaluated PENA with plugins selected from the WordPress official repository and compared its efficiency and accuracy against the technique that checks conflicts in all pairs of plugins. Results show that PENA is 12.4x to 19.6x more efficient than the comparison baseline and can find as many conflicts as it. Subject CMSPluginsTesting and debugging To reference this document use: http://resolver.tudelft.nl/uuid:1b347da6-70df-4e26-8b56-c37063d0d61f DOI https://doi.org/10.1016/j.infsof.2019.106212 Embargo date 2021-11-06 ISSN 0950-5849 Source Information and Software Technology, 118, 1-13 Bibliographical note Accepted author manuscript Part of collection Institutional Repository Document type journal article Rights © 2020 Igor Lima, J. Barros Cândido, Marcelo d'Amorim Files PDF paper.pdf 5.7 MB Close viewer /islandora/object/uuid:1b347da6-70df-4e26-8b56-c37063d0d61f/datastream/OBJ/view