Towards evidence‐based decision‐making for identification and usage of assets in composite software: A research roadmap. Issue 6 (19th March 2021) - Wohlin, Claes; Papatheocharous, Efi; Carlson, Jan; Petersen, Kai; Alégroth, Emil; Axelsson, Jakob; Badampudi, Deepika; Borg, Markus; Cicchetti, Antonio; Ciccozzi, Federicio; Olsson, Thomas; Sentilles, Séverine; et al.
Abstract: Software engineering is decision intensive. Evidence‐based software engineering is suggested for decision‐making concerning the use of methods and technologies when developing software. Software development often includes the reuse of software assets, for example, open‐source components. Which components to use have implications on the quality of the software (e.g., maintainability). Thus, research is needed to support decision‐making for composite software. This paper presents a roadmap for research required to support evidence‐based decision‐making for choosing and integrating assets in composite software systems. The roadmap is developed as an output from a 5‐year project in the area, including researchers from three different organizations. The roadmap is developed in an iterative process and is based on (1) systematic literature reviews of the area; (2) investigations of the state of practice, including a case survey and a survey; and (3) development and evaluation of solutions for asset identification and selection. The research activities resulted in identifying 11 areas in need of research. The areas are grouped into two categories: areas enabling evidence‐based decision‐making and those related to supporting the decision‐making. The roadmap outlines research needs in these 11 areas. The research challenges and research directions presented in this roadmap are key areas for further research to support evidence‐based decision‐making for composite software. Abstract : The paper presents a research roadmap for evidence‐based decision‐making for choosing and integrating assets in composite software systems. Eleven areas in need of research were identified in two categories. The first category outlines areas enabling evidence‐based decision‐making; the second category describes areas related to supporting decision‐making.