Requirements engineering (RE) involves human-centric activities that require interaction among different stakeholders. Traditionally, RE has been considered as a centralized, collocated, and phase-specific process. However, in open source software (OSS) development environments, the core RE activities are iterative and dynamic and follow a rather decentralized software engineering paradigm. This crosscutting characteristic of open source RE can be conceptualized using the “Twin Peaks” model that weaves RE together with software architecture. Although many weaving mechanisms have been proposed in recent years, the lack of theoretical underpinning limits a mechanism’s applicability and usefulness in different scenarios. In this research, we hypothesize stakeholders’ social interaction as an ecologically valid weaving mechanism of the “Twin Peaks” in open source RE. In this work, we use the phrase “stakeholders’ social interaction” to indicate interaction among stakeholders regarding the software system that takes place through some communication means, such as posting comments and artifacts over the issue tracking system. We investigate the influence of stakeholders’ social interaction in different RE activities, in particular, requirements identification, creativity in RE, and requirements implementation of OSS systems. This research enables us to gain valuable insights to generate guidelines for enhancing software engineering practice in relevant areas.

Increasingly competitive software industry, where multiple systems serve the same application domain and compete for customers, favors software with creative features. To promote software creativity, research has proposed multi-day workshops with experienced facilitators, and semi-automated tools to provide a limited support for creative thinking. Such approach is either time consuming and demands substantial involvement from analysts with creative abilities, or useful only for existing large-scale software with a rich issue tracking system. In this dissertation, we present different approaches leveraging advanced natural language processing and machine learning techniques to provide automated support for generating creative software requirements with minimal human intervention. A controlled experiment is conducted to assess the effectiveness of our automated framework compared to the traditional brainstorming technique. The results demonstrate our frame-work’s ability to generate creative features for a wide range of stakeholders and provoke innovative thinking among developers with various experience levels.