Why and How of Requirements Tracing
IEEE Software
Recovering Traceability Links between Code and Documentation
IEEE Transactions on Software Engineering
A Scenario-Driven Approach to Trace Dependency Analysis
IEEE Transactions on Software Engineering
A New Definition of the Subtype Relation
ECOOP '93 Proceedings of the 7th European Conference on Object-Oriented Programming
Using benchmarking to advance research: a challenge to software engineering
Proceedings of the 25th International Conference on Software Engineering
Recovering documentation-to-source-code traceability links using latent semantic indexing
Proceedings of the 25th International Conference on Software Engineering
Information Retrieval Models for Recovering Traceability Links between Code and Documentation
ICSM '00 Proceedings of the International Conference on Software Maintenance (ICSM'00)
Baselines in requirements tracing
PROMISE '05 Proceedings of the 2005 workshop on Predictor models in software engineering
Advancing Candidate Link Generation for Requirements Tracing: The Study of Methods
IEEE Transactions on Software Engineering
Introduction to Software Engineering Design: Processes, Principles and Patterns with UML2
Introduction to Software Engineering Design: Processes, Principles and Patterns with UML2
ICPC '08 Proceedings of the 2008 The 16th IEEE International Conference on Program Comprehension
A machine learning approach for tracing regulatory codes to product specific requirements
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 1
On the Equivalence of Information Retrieval Methods for Automated Traceability Link Recovery
ICPC '10 Proceedings of the 2010 IEEE 18th International Conference on Program Comprehension
Proceedings of the 6th International Workshop on Traceability in Emerging Forms of Software Engineering
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Rigorously evaluating and comparing traceability link generation techniques is a challenging task. In fact, traceability is still expensive to implement and it is therefore difficult to find a complete case study that includes both a rich set of artifacts and traceability links among them. Consequently, researchers usually have to create their own case studies by taking a number of existing artifacts and creating traceability links for them. There are two major issues related to the creation of one's own example. First, creating a meaningful case study is time consuming. Second, the created case usually covers a limited set of artifacts and has a limited applicability (e.g., a case with traces from high-level requirements to low-level requirements cannot be used to evaluate traceability techniques that are meant to generate links from documentation to source code). We propose a benchmark for traceability that includes all artifacts that are typically produced during the development of a software system and with end-to-end traceability linking. The benchmark is based on an irrigation system that was elaborated in a book about software design. The main task considered by the benchmark is the generation of traceability links among different types of software artifacts. Such a traceability benchmark will help advance research in this field because it facilitates the evaluation and comparison of traceability techniques and makes the replication of experiments an easy task. As a proof of concept we used the benchmark to evaluate the precision and recall of a link generation technique based on the vector space model. Our results are comparable to those obtained by other researchers using the same technique.