Should We Adopt a New Version of a Standard? – A Method and Its Evaluation on AUTOSAR
The development of large software systems is usually based on a number of industrial standards that define a set of features and their requirements. In order to use new features specified in the standards, new releases of the standards need to be adopted together with their requirements. This requires a thorough impact analysis of the changes in the requirements that can be time-consuming considering their potentially high number. In order to facilitate the adoption of new releases of industrial standards in large software systems, we present a method based on both quantitative and qualitative analysis of requirements evolution. The method is evaluated in a case study of AUTOSAR - a standard used in the development of automotive software systems in cooperation with Volvo Car Group. The evaluation results show that the use of the proposed method can identify the most unstable AUTOSAR specifications and their requirements whose changes may have a significant impact on the automotive systems. This knowledge can increase the speed of adoption of new AUTOSAR releases by automotive vendors.
KeywordsRequirement evolution Metrics Industrial standards
The authors would like to thank Swedish Governmental Agency for Innovation Systems (VINNOVA) for funding this research (grant no. 2013-02630) and the AUTOSAR team at Volvo Car Group for contributing to the work.
- 3.AUTOSAR, www.autosar.org: Automotive Open System Architecture (2003)
- 5.Cook, T., Campbell, D.: Quasi-Experimentation: Design & Analysis Issues for Field Settings. Houghton Mifflin, Boston (1979)Google Scholar
- 6.Durisic, D., Staron, M., Tichy, M.: ARCA - Automated analysis of AUTOSAR meta-model changes. In: International Workshop on Modelling in Software Engineering (2015)Google Scholar
- 7.Durisic, D., Staron, M., Tichy, M., Hansson, J.: Evolution of long-term industrial meta-models - a case study of AUTOSAR. In: Euromicro Conference on Software Engineering and Advanced Applications, pp. 141–148 (2014)Google Scholar
- 9.Li, J., Zhang, H., Zhu, L., Jeffery, R., Wang, Q., Li, M.: Preliminary results of a systematic review on requirements evolution. In: Proceedings of the IEEE Conference on Evaluation Assessment in Software Engineering, pp. 12–21 (2012)Google Scholar
- 10.Motta, C.: Analyzing the Evolution of System Requirements. Chalmers — University of Gothenburg (2016)Google Scholar
- 11.Nurmuliani, N., Zowghi, D., Fowell, S.: Analysis of requirements volatility during software development life cycle. In: Proceedings of the Australian Software Engineering Conference, pp. 28–37 (2004)Google Scholar
- 12.Runeson, P., Host, M.: Guidelines for conducting and reporting case study research in software engineering. In: Proceedings of the Conference on Empirical Software Engineering, pp. 131–164 (2009)Google Scholar
- 13.Shi, L., Wang, Q., Li, M.: Learning from evolution history to predict future requirement changes. In: Proceedings of the International Conference on Requirements Engineering, pp. 135–144 (2013)Google Scholar
- 14.Stark, G., Skillicorn, A., Smeele, R.: A micro and macro based examination of the effects of requirements changes on aerospace software maintenance. In: Proceedings of the IEEE Conference on Aerospace, pp. 165–172 (1998)Google Scholar
- 15.Wang, H., Li, J., Wang, Q., Wang, Y.: Quantitative analysis of requirements evolution across multiple versions of an industrial software product. In: Proceedings of the 17th Conference on Asia-Pacific Software Engineering, pp. 43–49 (2010)Google Scholar
- 16.Wohlin, C.: Guidelines for snowballing in systematic literature studies and a replication in software engineering. In: Proceedings of the 18th International Conference on Evaluation and Assessment in Software Engineering (2014)Google Scholar