Software product line tools: visualization of experimental data

Abstract

Software Product Line (SPL) is becoming widely adopted in industry due to its capability of minimizing costs and improving quality of software systems through systematic reuse of software artifacts. An SPL is a set of software systems sharing a common, managed set of features that satisfies the specific needs of a particular market segment. There are several tools to support variability management by modeling features in SPL. However, it is hard for a developer to choose the most appropriate tool due to several options available. In order to support this research, we developed the Vi\textbf{SPL}atform. It is a visual platform developed using Data Driven Documents (D3) to present and to favor the understanding of empirical data in the SPL context from two research methods. First, our work presents and discusses the findings from a Systematic Literature Review (SLR) of SPL management tools. Based on the results of the SLR, we designed and executed an empirical study. This empirical study compares and analyzes three SPL management tools, namely SPLOT, FeatureIDE, and pure::variants, based on data from 124 participants that used the analyzed tools. In this study, we performed a four-dimension quantitative and qualitative analysis with respect to common functionalities provided by SPL tools: (i) Feature Model Edition, (ii) Automated Feature Model Analysis, (iii) Product Configuration, and (iv) Feature Model Import/Export. Our aim with the Vi\textbf{SPL}atform is to explore different data types (multiple dimensional data) of our results and to provide visualization support to empirical software engineering data.