Revisiting the Product Configuration Systems Development Procedure for Scrum Compliance: An i* Driven Process Fragment

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Abstract

Product Configuration Systems (PCS) are software applications supporting the design of products tailored to the individual desiderata of customers. PCS development does not follow the same procedure as traditional software: indeed, due to its nature, specific knowledge needs to be collected, a set of custom engineering stages have thus been built-up. Within these stages, special requirements representation and design artifacts are used notably to deal with features inter-dependencies. More specifically, the Product Variant Master (PVM) has been specifically created for PCS knowledge representation while Class-Responsibility-Collaboration (CRC) cards and a UML Class Diagram are often indispensable for PCS object-oriented design. PCS development projects have gradually started to use agile methods like the Scrum. This paper presents a process fragment for conducting PCS development projects with Scrum; it overviews how the development team of a specific organization adapted the agile process to the PCS context. This process fragment has indeed been built on the basis of practitioners knowledge collected through 5 qualitative interviews (inductive approach) and exhaustively depict the activities performed by the team on PCS development projects of various size and context. Because of the possibility to represent social (role) dependencies, the fragment is visually represented using an i* Strategic Rationale Diagram. The main contribution of the paper is the fragment itself, it is intended to be dynamically used as an initial guidance for PCS development teams willing to conduct projects using Scrum; it can be tailored to any project/sprint and enriched at will.

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Wautelet, Y., Shafiee, S., & Heng, S. (2019). Revisiting the Product Configuration Systems Development Procedure for Scrum Compliance: An i* Driven Process Fragment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11915 LNCS, pp. 433–451). Springer. https://doi.org/10.1007/978-3-030-35333-9_31

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