Does sentiment help requirement engineering: exploring sentiments in user comments to discover informative comments

Conventional requirements engineering (RE) is often a manual process that is tedious, time-consuming, susceptible to errors, and hard to scale in case of continuous updates. Recent advances in natural language processing (NLP) transformed the RE process via automation. However, automation works better with structured data and formal requirement formats, limiting the ability to elicit and extract requirements from unstructured data; the rapid growth of digital platforms accentuates the need for treating user posts, comments, opinions and feedback as primary data sources for requirements mining and modeling. However, research conducted on unstructured Egyptian Arabic text is largely underexplored, due to its inherent linguistic challenges. This paper fills a critical gap in Arabic NLP, by providing an automated feature extraction and UML modeling pipeline utilizing state of the art embedding models, density-based clustering algorithm, and Large Language Models (LLMs), specifically engineered for handling Egyptian-Arabic text. The proposed pipeline demonstrates strong positive results, producing quality features and meaningful use case diagrams, and further confirms the feasibility of applying this advanced NLP-based pipeline to real world Egyptian dialectal data.

Mobile apps have exploded in popularity, encouraging developers to provide content to the massive user base of the main app stores. Although there exist automated techniques that can classify user comments into various topics with high levels of precision, recent studies have shown that the top apps in the app stores do not have customer ratings that directly correlate with the app's success. This implies that no single requirements elicitation technique can cover the full depth required to produce a successful product and that applying alternative requirements gathering techniques can lead to success when these two are combined. Since user involvement has been found to be the most impactful contribution to project success, in this paper we will explore how the Wizard of Oz (WOz) technique and user reviews available in Google Play, can be integrated to produce a product that meets the demand of more stakeholders than either method alone. To compare the role of early interactive requirements specification and app reviews, we conducted two studies (i) a case study analysis on 13 mobile app development teams who used very early stages Requirements Engineering (RE) by applying WOz, and (ii) a study analyzing 40 (70, 592 reviews) similar mobile apps on Google Play. The results of both studies show that while each of WOz and app review analysis techniques can be applied to capture specific types of requirements, an integrated process including both methods would eliminate the communication gap between users and developers at early stages of the development process and mitigates the risk of requirements change in later stages.