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.

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

“…Ali et al [55] proposed an approach that aims to mine SNS such as twitter and Facebook data to elicit user requirements. The authors collected 30,633 tweets from Twitter and 18,482 comments from Facebook in order to determine user requirements.…”

“…The tual framework has three basic components that could work together to support continuous ion and negotiations: (1) CrowdFeed is proposed to allow users to communicate feedback ing the services and software products they use and to actively participate in negotiation, (2) ements and Sustainability Service clusters, classifies and analyses user feedback which is d from CrowdFeed component, (3) the Requirements and Sustainability Integrator nent supports visualization and assessment of effects on sustainability. li et al [55] proposed an approach that aims to mine SNS such as twitter and Facebook data to ser requirements. The authors collected 30,633 tweets from Twitter and 18,482 comments acebook in order to determine user requirements.…”

Data-Driven Requirements Elicitation: A Systematic Literature Review

“…• Microblog data from twitter, Facebook, and Weibo were used for automated requirements elicitation. Of total eleven studies that used twitter, four studies extracted only texts [64][65][66][67], while the rest extracted additional metadata [68][69][70][71][72][73][74]. The metadata include the number of retweets, likes, lexically similar tweets (i.e., duplicates), twitter followers and friends (i.e., social rank), replies to tweets, as well as hashtags, handles (i.e., indicated by an @ appended with a username), and demographic data of the person who tweeted.…”

“…The metadata include the number of retweets, likes, lexically similar tweets (i.e., duplicates), twitter followers and friends (i.e., social rank), replies to tweets, as well as hashtags, handles (i.e., indicated by an @ appended with a username), and demographic data of the person who tweeted. • Ali et al [66] and Han et al [75] used user comments on Facebook and Weibo, respectively. Seven out of 11 studies that used microdata performed sentiment analysis of tweets [64-66, 68, 69, 72, 73] Online discussion/forum Eight studies (12%) elicited requirements from different online discussion forums: online forum posts from the feature tracker of the Password Safe project on SourceForge [76], questions and answers on Stack Overflow [77], and feature requests from open-source forums of SugarCRM, SecondLife, and an Amazonlike portal specifically developed for students [78], OpenOffice online discussion forum [79], the Reddit forum [80][81][82], and the VLC media player and Firefox web browser forums [83]…”

“…On the other hand, Johann et al [94] integrated both app reviews and descriptions to provide information on which app features are or are not actually reviewed. In addition, Ali et al [66] combined tweets for a smartwatch and Facebook comments of wearable and smartwatch.…”