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Understanding and improving effort estimation in agile software development. An industrial case study

: Tanveer, Binish; Guzman, Liliana; Engel, Ulf Martin


Association for Computing Machinery -ACM-; Association for Computing Machinery -ACM-, Special Interest Group on Software Engineering -SIGSOFT-:
International Conference on Software and System Process, ICSSP 2016. Proceedings : Co-Located with 38th International Conference on Software Engineering, Austin, Texas, May 14 - 22, 2016
New York: ACM Press, 2016
ISBN: 978-1-4503-4188-2
International Conference on Software and Systems Process (ICSSP) <2016, Austin/Tex.>
International Conference on Software Engineering (ICSE) <38, 2016, Austin/Tex.>
Fraunhofer IESE ()
effort estimation; agile software development; change impact

Effort estimation is more challenging in an agile context, as instead of exerting strict control over changes in requirements, dynamism is embraced. Current practice relies on expert judgment, where the accuracy of estimates is sensitive to the expertise of practitioners and prone to bias. In order to improve the effectiveness of the effort estimation process, the goal of this research is to investigate and understand the estimation process with respect to its accuracy in the context of agile software development from the perspective of agile development teams. Using case study research, two observations and eleven interviews were conducted with three agile development teams at SAP SE, a German multinational software corporation. The results reveal that factors such as the developer's knowledge and experience and the complexity and impact of changes on the underlying system affect the magnitude as well as the accuracy of estimation. Moreover, if certain aspects of the estimation process, such as the potential impact of a change on the underlying system, are supported by a tool can help improve estimation accuracy. We conclude that explicit consideration of these factors in the estimation process can support experts in making accurate and informed estimates. Furthermore, there is a need for a tool that incorporates expert knowledge, enables explicit consideration of cost drivers by experts and visualizes this information in order to improve the effectiveness of the effort estimation process.