Predictive analytics for product configurations in software product lines

Author Affiliation

Tariq Mahmood is Associate Professor at Institute of Business Administration (IBA), Karachi

Faculty / School

School of Mathematics and Computer Science (SMCS)


Department of Computer Science

Was this content written or created while at IBA?


Document Type


Source Publication

International Journal of Computational Intelligence Systems




Computer Sciences | Mathematics


A Software Product Line (SPL) is a collection of software for configuring software products in which sets of features are configured by different teams of product developers. This process often leads to inconsistencies (or dissatisfaction of constraints) in the resulting product configurations, whose resolution consumes considerable business resources. In this paper, we aim to solve this problem by learning, or mathematically modeling, all previous patterns of feature selection by SPL developers, and then use these patterns to predict inconsistent configuration patterns at runtime. We propose and implement an informative Predictive Analytics tool called predictive Software Product LIne Tool (p-SPLIT) which provides runtime decision support to SPL developers in three ways: 1) by identifying configurations of feature selections (patterns) that lead to inconsistent product configurations, 2) by identifying feature selection patterns that lead to consistent product configurations, and 3) by predicting feature inconsistencies in the product that is currently being configured (at runtime). p-SPLIT provides the first application of Predictive Analytics for the SPL feature modeling domain at the application engineering level. With different experiments in representative SPL settings, we obtained 85% predictive accuracy for p-SPLIT and a 98% Area Under the Curve (AUC) score. We also obtained subjective feedback from the practitioners who validate the usability of p-SPLIT in providing runtime decision support to SPL developers. Our results prove that p-SPLIT technology is a potential addition for the global SPL product configuration community, and we further validate this by comparing p-SPLIT’s characteristics with state-of-the-art SPL development solutions.

Indexing Information

HJRS - X Category, Scopus, Web of Science - Science Citation Index Expanded (SCI)

Publication Status