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An Empirical Analysis of Task Allocation in Scrum-based Agile Programming

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 Added by Han Yu
 Publication date 2014
and research's language is English




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Agile Software Development (ASD) methodology has become widely used in the industry. Understanding the challenges facing software engineering students is important to designing effective training methods to equip students with proper skills required for effectively using the ASD techniques. Existing empirical research mostly focused on eXtreme Programming (XP) based ASD methodologies. There is a lack of empirical studies about Scrum-based ASD programming which has become the most popular agile methodology among industry practitioners. In this paper, we present empirical findings regarding the aspects of task allocation decision-making, collaboration, and team morale related to the Scrum ASD process which have not yet been well studied by existing research. We draw our findings from a 12 week long course work project in 2014 involving 125 undergraduate software engineering students from a renowned university working in 21 Scrum teams. Instead of the traditional survey or interview based methods, which suffer from limitations in scale and level of details, we obtain fine grained data through logging students activities in our online agile project management (APM) platform - HASE. During this study, the platform logged over 10,000 ASD activities. Deviating from existing preconceptions, our results suggest negative correlations between collaboration and team performance as well as team morale.



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Developing sustainable scientific software for the needs of the scientific community requires expertise in both software engineering and domain science. This can be challenging due to the unique needs of scientific software, the insufficient resources for modern software engineering practices in the scientific community, and the complexity of evolving scientific contexts for developers. These difficulties can be reduced if scientists and developers collaborate. We present a case study wherein scientists from the SuperNova Early Warning System collaborated with software developers from the Scalable Cyberinfrastructure for Multi-Messenger Astrophysics project. The collaboration addressed the difficulties of scientific software development, but presented additional risks to each team. For the scientists, there was a concern of relying on external systems and lacking control in the development process. For the developers, there was a risk in supporting the needs of an user-group while maintaining core development. We mitigated these issues by utilizing an Agile Scrum framework to orchestrate the collaboration. This promoted communication and cooperation, ensuring that the scientists had an active role in development while allowing the developers to quickly evaluate and implement the scientists software requirements. While each system was still in an early stage, the collaboration provided benefits for each group: the scientists kick-started their development by using an existing platform, and the developers utilized the scientists use-case to improve their systems. This case study suggests that scientists and software developers can avoid some difficulties of scientific computing by collaborating and can address emergent concerns using Agile Scrum methods.
243 - Alan Romano 2021
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