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Date of Award
Dissertation - NSU Access Only
Doctor of Philosophy in Computer Science (CISD)
Graduate School of Computer and Information Sciences
Current Requirements Engineering (RE) mechanisms used to measure Requirements Volatility (RV) employ textual-based artifacts for tracking changes to software requirements that primarily consist of detailed requirements documents that are difficult to understand by most software system stakeholders making it almost impossible for these stakeholders to gain a clear picture of how changes to a requirement will impact the total system overall. Research in the area of RE visualizations have proven that graphically representing software information in the form of visualizations can communicate complex information regarding requirements to system stakeholders in a manner that does not require an in-depth knowledge of RE technical documentation. This research used the concepts of Footprint Visualizations (FVs) to graphically represent software requirements as they evolved over time and analyzed these FV image artifacts to determine RV ratings. This work successfully demonstrated the use of FV analysis to measure RV. This work performed a qualitative study that compared the relationship between the RV ratings that were determined using the FV-based analysis methods proposed in this work to the RV ratings determined using traditional non-visual RV methods that relied on subject matter expert evaluation of a common requirements use case data set. The results of this study expanded the body of knowledge in the field of Requirements Engineering Visualization by demonstrating new analysis methods for measuring volatility in requirements use cases as they evolve over the software development life cycle process in order to aid system stakeholders in understanding the effects of changes made to requirements regardless of the individual stakeholders level of technical requirements documentation training.
Dennis Mize. 2012. A Study of Requirements Volatility and Footprint Visualization Properties in Evolving Use Case Data Sets. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, Graduate School of Computer and Information Sciences. (251)