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Operationalizing the Experience Factory for Effort Estimation in Agile Processes

: Taibi, Davide; Lenarduzzi, Valentina; Diebold, Philipp; Lunesu, Ilaria


Association for Computing Machinery -ACM-:
EASE 2017. Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering : Karlskrona, Sweden, June 15-16, 2017
New York: ACM Press, 2017
ISBN: 978-1-4503-4804-1
International Conference on Evaluation and Assessment in Software Engineering (EASE) <21, 2017, Karlskrona>
Fraunhofer IESE ()
knowledge management; experience factory; agile software development

The effort required to systematically collect historical data is not always allocable in agile processes and historical data management is usually delegated to the developers' experience, who need to remember previous project details. However, even if well trained, developers cannot precisely remember a huge number of details, resulting in wrong decisions being made during the development process.

The goal of this paper is to operationalize the Experience Factory in an agile way, i.e., defining a strategy for collecting historical project data using an agile approach. [Method] We provide a mechanism for understanding whether a measure must be collected or not, based on the Return on Invested Time (ROIT). In order to validate this approach, we instantiated the factory with an exploratory case study, comparing four projects that did not use our approach with one project that used it after 12 weeks out of 37 and two projects that used it from the beginning.

The proposed approach helps developers to constantly improve their estimation accuracy with a very positive ROIT of the collected measure.

From this first experience, we can conclude that the Experience Factory can be applied effectively to agile processes, supporting developers in improving their performance and reducing potential decision mistakes.