Toward Reference Models for Requirements Traceability
IEEE Transactions on Software Engineering
Event-Based Traceability for Managing Evolutionary Change
IEEE Transactions on Software Engineering
Ambient Findability: What We Find Changes Who We Become
Ambient Findability: What We Find Changes Who We Become
Empirical research methods for software engineering
Proceedings of the twenty-second IEEE/ACM international conference on Automated software engineering
Can We Beat the Complexity of Very Large-Scale Requirements Engineering?
REFSQ '08 Proceedings of the 14th international conference on Requirements Engineering: Foundation for Software Quality
Architecting and Coordinating Thousands of Requirements --- An Industrial Case Study
REFSQ '09 Proceedings of the 15th International Working Conference on Requirements Engineering: Foundation for Software Quality
Software & Systems Requirements Engineering: In Practice
Software & Systems Requirements Engineering: In Practice
Towards metamodel support for variability and traceability in software product lines
Proceedings of the 5th Workshop on Variability Modeling of Software-Intensive Systems
REFSQ'11 Proceedings of the 17th international working conference on Requirements engineering: foundation for software quality
Do better IR tools improve the accuracy of engineers' traceability recovery?
Proceedings of the International Workshop on Machine Learning Technologies in Software Engineering
International Journal of Information Management: The Journal for Information Professionals
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The amount of data in large-scale software engineering contexts continues to grow and challenges efficiency of software engineering efforts. At the same time, information related to requirements plays a vital role in the success of software products and projects. To face the current challenges in software engineering information management, software companies need to reconsider the current models of information. In this paper, we present a modeling framework for requirements artifacts dedicated to a large-scale market-driven requirements engineering context. The underlying meta-model is grounded in a clear industrial need for improved flexible models for storing requirements engineering information. The presented framework is created in collaboration with industry and initially evaluated by industry practitioners from three large companies. Participants of the evaluation positively evaluated the presented modeling framework as well as pointed out directions for further research and improvements.