• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Your Opinions Let us Know: Mining Social Network Sites to Evolve Software Product Lines


Abstract

Software product lines (SPLs) are complex software systems by nature due to their common reference architecture and interdependencies. Therefore, any form of evolution can lead to a more complex situation than a single system. On the other hand, software product lines are developed keeping long-term perspectives in mind, which are expected to have a considerable lifespan and a long-term investment. SPL development organizations need to consider software evolution in a systematic way due to their complexity and size. Addressing new user requirements over time is one of the most crucial factors in the successful implementation SPL. Thus, the addition of new requirements or the rapid context change is common in SPL products. To cope with rapid change several researchers have discussed the evolution of software product lines. However, for the evolution of an SPL, the literature did not present a systematic process that would define activities in such a way that would lead to the rapid evolution of software. Our study aims to provide a requirements-driven process that speeds up the requirements engineering process using social network sites in order to achieve rapid software evolution. We used classification, topic modeling, and sentiment extraction to elicit user requirements. Lastly, we conducted a case study on the smartwatch domain to validate our proposed approach. Our results show that users’ opinions can contain useful information which can be used by software SPL organizations to evolve their products. Furthermore, our investigation results demonstrate that machine learning algorithms have the capacity to identify relevant information automatically.


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Cite this article

[IEEE Style]
N. Ali, S. Hwang and J. Hong, "Your Opinions Let us Know: Mining Social Network Sites to Evolve Software Product Lines," KSII Transactions on Internet and Information Systems, vol. 13, no. 8, pp. 4191-4211, 2019. DOI: 10.3837/tiis.2019.08.021.

[ACM Style]
Nazakat Ali, Sangwon Hwang, and Jang-Eui Hong. 2019. Your Opinions Let us Know: Mining Social Network Sites to Evolve Software Product Lines. KSII Transactions on Internet and Information Systems, 13, 8, (2019), 4191-4211. DOI: 10.3837/tiis.2019.08.021.