Automated Generation of Creative Software Requirements: A Data-Driven Approach
Creativity can often be seen in artistic productions when artists use their imagination to create original and novel work. However, the importance of creativity is being broadly recognized in various areas. Recently, the requirements engineering (RE) research community has been paying more attention to the matter of capturing and generating creative requirements as it plays a pivotal role in a software system sustainability. To further advance the literature, in this paper, we propose a automated system to alleviate creative feature generation by using a Hidden Markov Model with requirements data scraped from Google Play. To evaluate the performance of the system, We experiment our system in two settings, generating features from a specific application domain (i.e., Messaging platform) and from a mixed domains of successful applications including Google Chrome and Dropbox. The results offer encouraging insights on how our system can support capturing creative requirements and aid the development of more advanced software feature generators.
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