METRIX: a new tool to evaluate the quality of software source codes

Varet, Antoine; Larrieu, Nicolas

doi:10.2514/6.2013-4567

Cited by 2 publications

(1 citation statement)

References 4 publications

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“…Most of studies have focused on visualizing source code related metrics and many approaches are proposed in this regard [150]. Metrics is a numerical/proportional value to describe and measure the quality of software artifacts [37], [38] (e.g. source code quality, testing quality, documentation quality), therefore it is called quality metric.…”

Section: Visualization Of Source Codementioning

confidence: 99%

Towards Visualization of Unit Test and Source Code Relations

Aljawabrah

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Test-to-code traceability is the ability to relate the test unit and source code artifacts created during the software development life cycle (SDLC). Traceability of test and code relations is fundamental to support various activities of software development such as program comprehension, verification and validation, impact analysis, reuse, maintenance, and software evolution. Notwithstanding its importance, many significant challenges are associated with traceability. One of these challenges is how to support the comprehension and maintenance of these links efficiently and effectively.Visualization is an important part that effectively supports understanding test-tocode relations. It provides enhanced process visibility, helps engineers, developers, and testers to verify the quality of TCT links, and understand which code modules are tested by which unit tests.As there are many sources from where the traceability relations can be inferred, one of the most important questions is to decide which source or combination of sources is the best to determine the test-to-code links. It is obvious that, if these sources disagree, this will make it harder to understand what is going on, what was the goal of the developer, and how the components are really related and change impact analysis can yield false results, etc. Fortunately, visualization can aid this task. The presented approach consists of three parts. The first part consists of the recognition of artifacts from two different areas, source code, and unit test. The second part presents different sources for capturing the links between code and test iv such as a naming convention, last call before assert, and the static call graph. The third part includes the visualization method used to visually present the traceability links inferred from traceability links sources. The trace visualization approach is implemented as a trace visualization tool, which is called TCTracVis.This thesis also provides an empirical study based on the implementation of the presented approach. The approach and its tool support are applied in different software development projects conducted with a group of students, academics, and from industry. The effectiveness and practicability of the presented approach and its tool support have been evaluated. The effectiveness results indicate that the visualization of multilevel test-to-code traceability links, inferred from multiple sources, is more effective for the testers and developers than using visualization of a single source of traceability links. It helps to get a bigger picture of what is going on with the tests, find solutions to the problems in testing, and understand the relationships between test cases and the corresponding units under test. At the same time, the usability results indicate that the participants found that the approach and its tool support usability, and enhance the overall browsing, comprehension, and maintenance of test-to-code traceability links of a system.

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Section: Visualization Of Source Codementioning

confidence: 99%