Context-Aware Automated Sprint Plan Generation for Agile Software Development

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Abstract

Sprint planning is essential for the successful execution of agile software projects. While various prioritization criteria influence the selection of user stories for sprint planning, their relative importance remains largely unexplored, especially across different project contexts. In this paper, we investigate how prioritization criteria vary across project settings and propose a model for generating sprint plans that are tailored to the context of individual teams. Through a survey conducted at ING, we identify urgency, sprint goal alignment, and business value as the top prioritization criteria, influenced by project factors such as resource availability and client type. These results highlight the need for contextual support in sprint planning. To address this need, we develop an optimization model that generates sprint plans aligned with the specific goals and performance of a team. By integrating teams' planning objectives and sprint history, the model adapts to unique team contexts, estimating prioritization criteria and identifying patterns in planning behavior. We apply our approach to real-world data from 4,841 sprints at ING, demonstrating significant improvements in team alignment and sprint plan effectiveness. Our model boosts team performance by generating plans that deliver more business value, align more closely with sprint goals, and better mitigate delay risks. Overall, our results show that the efficiency and outcomes of sprint planning practices can be significantly improved through the use of context-aware optimization methods.

Original languageEnglish
Title of host publicationProceedings - 2024 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
PublisherAssociation for Computing Machinery (ACM)
Pages1745-1756
Number of pages12
ISBN (Electronic)9798400712487
DOIs
Publication statusPublished - 2024
Event39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024 - Sacramento, United States
Duration: 28 Oct 20241 Nov 2024

Publication series

NameProceedings - 2024 39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024

Conference

Conference39th ACM/IEEE International Conference on Automated Software Engineering, ASE 2024
Country/TerritoryUnited States
CitySacramento
Period28/10/241/11/24

Keywords

  • agile methods
  • context-aware optimization
  • sprint planning

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