|author(s)||Sascha El-Sharkawy, Nozomi Yamagishi-Eichler and Klaus Schmid|
|title||Metrics for Analyzing Variability and Its Implementation in Software Product Lines: A Systematic Literature Review|
|publication type||Beitrag zu einer Tagung / Konferenz|
|booktitle||Proceedings of the 23rd International Systems and Software Product Line Conference (SPLC'19)|
This summary refers to the paper Metrics for analyzing variability and its implementation in software product lines: A systematic literature review. It was online first in 2018 and was finally published 2019 in the Information and Software Technology (IST) journal.
The use of metrics for assessing software products and their qualities is well established in traditional Software Engineering (SE). However, such traditional metrics are typically not applicable to Software Product Line (SPL) engineering as they do not address variability management, a key part of product line engineering. Over time, various specialized product line metrics for SPLs have been described in literature, but no systematic description of these metrics and their characteristics is currently available.
This paper presents a systematic literature review, where we identify metrics explicitly designed for variability models, code artifacts, and metrics taking both kinds of artifacts into account. This captures the core of variability management for product lines. We discovered 42 relevant papers reporting 147 metrics designed for SPLs.We provide a categorization of these metrics and discuss problematic issues regarding their definitions. We also systematically assess the evaluation status of the metrics showing a current lack of high-quality evaluation in the field. Researchers and practitioners can benefit from the published catalog of variability-aware metrics