Abstract
In the software development process, traceability links between unit tests and code are not explicitly maintained, and dependencies in most cases are manually identified. As a result, a large amount of effort and time is required during the comprehension process to establish the links between these artifacts. Although there are several methods that can infer such links based on different phenomenons, these methods usually produce different set of traceability links. This work expands upon previous traceability link recovery and visualization studies by implementing a combination of traceability recovery methods that automatically retrieve the links, and visualizing them to help developers to overview the links inferred by various recovery techniques, and also to select the right relations for analyses. The results of the usability study show that the visualization model presented herein can effectively support browsing, comprehension, and maintenance of Test-to Code Traceability (TCT) links in a system with enhanced efficiency, as well as visualization of TCT links from multiple sources is better than a visualization of single source of traceability links.
Highlights
System source code constitutes the main development artifact in agile development; unit tests, code and user stories are usually the artifacts produced during the agile development process itself
RELATED WORK In the following subsections, we analyze some of the existing techniques used for TCT links recovery, and we introduce some of the visualization techniques usually used to display the links between software artifacts
TCT LINK RECOVERY In [1], we presented a prototype of a tool that supports visualization of traceability links retrieved using class invocations in test cases
Summary
System source code constitutes the main development artifact in agile development; unit tests, code and user stories are usually the artifacts produced during the agile development process itself. As such, creating and visualizing the links between code classes and unit tests can be helpful during software development processes in a number of tasks such as in program comprehension, impact analysis, maintenance, and artifact reuse. Several approaches have been explored to extract the links between test and code [21]. While traceability recovery approaches can be automated, none of them is itself accurate. Manual recovery is a complex, errorprone, and time-consuming task. The unsolved issue remains is how to efficiently support the comprehension, browsing, and maintenance of
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