Comparing SMarty and PLUS for Variability Identification and Representation at Product-Line UML Class Level: A Controlled Quasi-Experiment

Abstract

Although variability management is one of the main activities of software product lines, current literature provides almost no empirical evaluations on variability management approaches based on UML. This paper aims at experimentally comparing two approaches and picks SMarty and PLUS as representative examples. Such comparison takes into account their effectiveness of expressing correctly and incorrectly variabilities in UML class diagrams. We used a 2×2 factorial design for this study. We calculated and analyzed data from participants using the T-Test. The Spearman technique supported correlation of the effectiveness of the approaches and the participants prior variability knowledge. In general, PLUS was more effective than SMarty. Generalization of results is not possible as this is an incipient evidence of PLUS and SMarty effectiveness based on graduate students and lecturers. However, counting on students and lecturers provides several contributions as we discuss in this paper.