Busari, SA;
Letier, E;
(2017)
RADAR: A Lightweight Tool for Requirements and Architecture Decision Analysis.
In: Uchitel, S and Orso, A and Robillard, M, (eds.)
ICSE '17: Proceedings of the 39th International Conference on Software Engineering.
(pp. pp. 552-562).
Association for Computing Machinery (ACM): New York, NY, USA.
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Abstract
Uncertainty and conflicting stakeholders' objectives make many requirements and architecture decisions particularly hard. Quantitative probabilistic models allow software architects to analyse such decisions using stochastic simulation and multi-objective optimisation, but the difficulty of elaborating the models is an obstacle to the wider adoption of such techniques. To reduce this obstacle, this paper presents a novel modelling language and analysis tool, called RADAR, intended to facilitate requirements and architecture decision analysis. The language has relations to quantitative AND/OR goal models used in requirements engineering and to feature models used in software product lines. However, it simplifies such models to a minimum set of language constructs essential for decision analysis. The paper presents RADAR's modelling language, automated support for decision analysis, and evaluates its application to four real-world examples.
Type: | Proceedings paper |
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Title: | RADAR: A Lightweight Tool for Requirements and Architecture Decision Analysis |
Event: | 39th International Conference on Software Engineering (ICSE '17) |
Location: | Buenos Aires, Argentina |
Dates: | 20 May 2017 - 28 May 2017 |
ISBN-13: | 9781538638682 |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1109/ICSE.2017.57 |
Publisher version: | https://doi.org/10.1109/ICSE.2017.57 |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
Keywords: | Decision Analysis, Requirements Engineering, Software Architecture, Goal Modelling, Monte-Carlo Simulation, Multi-Objective Optimisation, Search-Based Software Engineering, Expected Value of Information |
UCL classification: | UCL UCL > Provost and Vice Provost Offices UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
URI: | https://discovery.ucl.ac.uk/id/eprint/1542214 |
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