Feature selection optimization in software product lines

Author Affiliation

Tariq Mahmood is Professor & Program Coordinator MS (CS) & MS (DS) Programs at Institute of Business Administration (IBA), Karachi

Faculty / School

Faculty of Computer Sciences (FCS)


Department of Computer Science

Was this content written or created while at IBA?


Document Type


Source Publication

IEEE Access




Computer Sciences | Engineering


Feature modeling is a common approach for configuring and capturing commonalities and variations among different Software Product Lines (SPL) products. This process is carried out by a set of SPL design teams, each working on a different configuration of the desired product. The integration of these configurations leads to inconsistencies in the final product design. The typical solution involves extensive deliberation and unnecessary resource usage, which makes SPL inconsistency resolution an expensive and unoptimized process. We present the first comprehensive evaluation of swarm intelligence (using Particle Swarm Optimization) to the problem of resolving inconsistencies in a configured integrated SPL product. We call it ${o}$ -SPLIT ( ${o}$ ptimization-based Software Product LIne Tool) and validate ${o}$ -SPLIT with standard ERP, SPLOT (Software Product Lines Online Tools), and BeTTy (BEnchmarking and TesTing on the analYsis) product configurations along with diverse feature set sizes. The results show that Particle Swarm Optimization can successfully optimize SPL product configurations. Finally, we implement ${o}$ -SPLIT as a decision-support tool in a real, local SPL setting and acquire subjective feedback from SPL designers which shows that the teams are convinced of the usability and high-level decision support provided by ${o}$ -SPLIT.

Indexing Information

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

Journal Quality Ranking

Impact Factor: 3.367

Publication Status