Handling Obstacles in Goal-Oriented Requirements Engineering
IEEE Transactions on Software Engineering - special section on current trends in exception handling—part II
A Cost-Value Approach for Prioritizing Requirements
IEEE Software
Multi-Criteria Preference Analysis for Systematic Requirements Negotiation
COMPSAC '02 Proceedings of the 26th International Computer Software and Applications Conference on Prolonging Software Life: Development and Redevelopment
Initial Industrial Experience of Misuse Cases in Trade-Off Analysis
RE '02 Proceedings of the 10th Anniversary IEEE Joint International Conference on Requirements Engineering
AGORA: Attributed Goal-Oriented Requirements Analysis Method
RE '02 Proceedings of the 10th Anniversary IEEE Joint International Conference on Requirements Engineering
Software Architecture in Practice
Software Architecture in Practice
A Systematic Tradeoff Analysis for Conflicting Imprecise Requirements
RE '97 Proceedings of the 3rd IEEE International Symposium on Requirements Engineering
Software Requirements Prioritizing
ICRE '96 Proceedings of the 2nd International Conference on Requirements Engineering (ICRE '96)
Modelling strategic relationships for process reengineering
Modelling strategic relationships for process reengineering
Reasoning about partial goal satisfaction for requirements and design engineering
Proceedings of the 12th ACM SIGSOFT twelfth international symposium on Foundations of software engineering
Dealing with imprecise quality factors in software design
3-WoSQ Proceedings of the third workshop on Software quality
Communications of the ACM - ACM at sixty: a look back in time
i*-prefer: optimizing requirements elicitation process based on actor preferences
Proceedings of the 2009 ACM symposium on Applied Computing
Preference Model Driven Services Selection
CAiSE '09 Proceedings of the 21st International Conference on Advanced Information Systems Engineering
Goal-oriented requirements analysis and reasoning in the Tropos methodology
Engineering Applications of Artificial Intelligence
Evaluating goal models within the goal-oriented requirement language
International Journal of Intelligent Systems - Goal-driven Requirements Engineering
Requirements trade-offs analysis in the absence of quantitative measures: a heuristic method
Proceedings of the 2011 ACM Symposium on Applied Computing
A Semi-automated Decision Support Tool for Requirements Trade-Off Analysis
COMPSAC '11 Proceedings of the 2011 IEEE 35th Annual Computer Software and Applications Conference
Modelling risk and identifying countermeasure in organizations
CRITIS'06 Proceedings of the First international conference on Critical Information Infrastructures Security
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Context: Choosing a design solution most often involves dealing with trade-offs and conflicts among requirements and design objectives. Making such trade-offs during early stages of requirements and design is challenging because costs and benefits of alternatives are often hard to quantify. Objective: The objective of this work is to develop a decision analysis method that assists in making trade-offs in the absence of quantitative data. Method: In this method, stakeholders qualitatively compare consequences of alternatives on decision criteria. We propose an algorithm that generates all possible consequences of alternatives on requirements, according to the rough qualitative comparisons that stakeholders made. The possible consequences generated by the algorithm are then analyzed by the Even Swaps Multi-Criteria Decision Analysis method to determine the best solution. The Even Swaps method is a technique developed in management science to assist in multi-criteria decision making when explicit value trade-offs are not available. Results and conclusions: Our algorithm teases out the need to accurately measure or estimate costs and benefits of alternative design solutions. The algorithm automates the Even Swap process, and reuses stakeholders' value trade-offs throughout the Even Swaps process. We applied the prototype tool in several case studies to evaluate the utility of the method. The results of case studies provide evidence that our decision aid method selects the optimum solution correctly compared to results of other similar quantitative methods, while our method does not rely on detailed numerical assessment of alternatives and importance weights of criteria.