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The Compare of Solo Programming and Pair Programming Strategies in a Scrum Team: A Multi-agent Simulation

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Intelligent Algorithms in Software Engineering (CSOC 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1224))

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Abstract

Scrum is a popular software development process that addressed the complex software delivery through multi-sprint. However, the scrum team working strategy remain undefined, such as how-to delivery the software at each sprint by optimized task allocation for various team composition is a complex problem. This paper proposed a multi-agent based simulation methods to model scrum team and the proposed innovative team working strategy, in order to verify the performance of the team under different working strategies. A solo strategy and pair programming strategies for the scrum team are designed. Criteria such as completion time, effort time and idle time are considered into the evaluation of the designed team strategies. The testing experiment shows that the adoption of pair programming to scrum team can help the team to improve its performance under specific context.

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Acknowledgement

Sincerely, Thanks for Dr Patricia Anthony and Dr. Stuart Charter at Lincoln University, New Zealand to support this PhD research, also thanks for University of Technology Sydney provides funding in the related data analysis and machine learning research which I was doing my invited research at UTS, Australia. I also thanks to Edinburgh Napier University, United Kingdom where I get my MSc in Advanced Software Engineering. They are all my best Supervisors support me to growth and become more and more professional.

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Authors and Affiliations

  1. Lincoln University, Lincoln, New Zealand

    Zhe Wang

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  1. Zhe Wang
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Correspondence to Zhe Wang .

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  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Wang, Z. (2020). The Compare of Solo Programming and Pair Programming Strategies in a Scrum Team: A Multi-agent Simulation. In: Silhavy, R. (eds) Intelligent Algorithms in Software Engineering. CSOC 2020. Advances in Intelligent Systems and Computing, vol 1224. Springer, Cham. https://doi.org/10.1007/978-3-030-51965-0_11

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