Value-Oriented Requirements: Eliciting Domain Requirements from Social Network Services to Evolve Software Product Lines

• Published in: Applied sciences Vol. 9; no. 19; p. 3944
• Main Authors: Ali, Nazakat, Hong, Jang-Eui
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.10.2019
• Subjects: Commonality; Computer programs; End users; Experiments; Feedback; Gender; Keywords; Organizations; Personal information; Product lines; requirement engineering; Requirements analysis; requirements elicitation; Social networks; Social organization; Software; Software development; Software engineering; software product lines; Tagging; text analytics; User requirements; Variability; variability and commonality; Wearable computers
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app9193944

Social network services allow a large population of end-users of software products to publicly share their concerns and experiences about software systems. From a software engineering perspective, such data can be collected and analyzed to help software development organizations to infer users’ emerging demands, receive their feedback, and plan the rapid evolution of software product lines. For the evolution of software product lines, organizations supplement emerging requirements in their products to meet user’s needs and also to retain their dominance in the market. Therefore, social network services, being a communication channel, have supported a number of software development activities such as requirements engineering. It has supported software development organizations to cope with numerous limitations of the traditional requirements engineering approaches by eliciting, prioritizing, and negotiating user requirements. However, these approaches do not consider eliciting requirements in terms of variability and commonality while identifying requirements. To address this issue, we have proposed a social network service-based requirement engineering process. It considers the attributes of users’ opinions to determine variability and commonality. In order to justify our proposed approach, a controlled experiment was conducted on a sample set of end-users on Facebook and Twitter. The experimental results show that the team using the proposed approach performed better in terms of efficiency and effectiveness than the team that used a traditional requirements engineering approach.