REV '07 Proceedings of the Second International Workshop on Requirements Engineering Visualization
Constructing and Visualizing Transformation Chains
ECMDA-FA '08 Proceedings of the 4th European conference on Model Driven Architecture: Foundations and Applications
REV '08 Proceedings of the 2008 Requirements Engineering Visualization
Challenges for semi-automatic trace recovery in the automotive domain
TEFSE '09 Proceedings of the 2009 ICSE Workshop on Traceability in Emerging Forms of Software Engineering
REV '09 Proceedings of the 2009 Fourth International Workshop on Requirements Engineering Visualization
Requirements Engineering Visualization: A Survey on the State-of-the-Art
REV '09 Proceedings of the 2009 Fourth International Workshop on Requirements Engineering Visualization
A survey of traceability in requirements engineering and model-driven development
Software and Systems Modeling (SoSyM)
Which traceability visualization is suitable in this context? a comparative study
REFSQ'12 Proceedings of the 18th international conference on Requirements Engineering: foundation for software quality
| Hi-index | 0.00 |
This paper describes a new visualization technique for helping analysts to understand the potential impact of changing requirements, and for providing valuable early feedback on the quality of a software design. Based on the candidate links that are automatically generated by a trace retrieval tool, VisMatrix creates a graphical representation of the requirements trace matrix showing not only where candidate links exist, but also the strength of those links. New metrics derived from the trace visualization, and its underlying trace matrix, are introduced. These include 'trace clustering' for evaluating modularity, and 'trace scope' for analyzing fan-in and fan-out behavior of traces, where fan-in represents the number of requirements influencing a design artifact, and fan-out represents the degree of influence a single requirement has on the set of design artifacts. Examples are drawn from the automatically generated trace matrices of four different data sets to illustrate the visualization techniques and analyze the proposed metrics.