Visualization of Unit and Selective Regression Software Tests

Tamisier, Thomas; Karski, Peter; Feltz, Fernand

doi:10.1007/978-3-642-40840-3_33

Cited by 5 publications

(4 citation statements)

References 2 publications

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“…The class dependencies will help to explain how much one class is dependent on another. The class dependencies will be generated from existing static code analysis tools, Classycle. 53 The tool used to generate graphs in this research is open‐source, and it has been experimented and proven to be effective in prior research 53–56 . We decided to exclude some of the commercial and proprietary static code analysis tools (Ndepend, Jhawks, SDMetrics) to be used in the research.…”

Section: Proposed Software Stability and Reusability (Ssr) Processmentioning

confidence: 99%

“…53 The tool used to generate graphs in this research is open-source, and it has been experimented and proven to be effective in prior research. [53][54][55][56] We decided to exclude some of the commercial and proprietary static code analysis tools (Ndepend, Jhawks, SDMetrics) to be used in the research. Figure 3 shows an example of dependencies generated from Classycle.…”

Section: Generating Class Dependenciesmentioning

confidence: 99%

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A metadata driven process for assessing stability and reusability based on risk of change of software systems

Mehboob

Chong

2023

Softw Pract Exp

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Measuring and estimating the reusability of software components are important steps toward finding reusable candidates. Reuse of software components can aid in the reduction of the development cost of new software or maintenance of existing ones. However, assessing the reusability of software is a challenging task. Even if reusable candidates can be identified, developers will need to decide on the reuse strategies, that is, reuse as it is without any modification, or introduce new changes to the reusable candidate to fulfill requirements in the new environment or releases. Thus, the stability of the reusable candidates plays a pivotal role because it will influence the ease of reuse. Assessing and predicting the stability of potential reusable candidates becomes a significant and important step in software reuse. In this research, we propose to leverage on risk of change as a proxy to measure software stability, where the latter is also a proxy measure for software reuse. Based on experiments conducted on 29 open-source software with different sizes and application types hosted on GitHub, we found that classes with high impact and high risk of change should be avoided from being reused due to their instability, while those classes with low impact and risk of change should be given priority. The proposed work can aid in providing a better understanding of the ease of reuse for software systems and can be used as a tool to assess its overall quality.

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Section: Proposed Software Stability and Reusability (Ssr) Processmentioning

confidence: 99%

Section: Generating Class Dependenciesmentioning

confidence: 99%

A metadata driven process for assessing stability and reusability based on risk of change of software systems

Mehboob

Chong

2023

Softw Pract Exp

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“…Moreover, TestQ [9] and ӼSuds [10] tools are also focused on fault localization purpose. Tamisier et al [11] proposed a tool to visualize test results and uncovered code segments information. Another tool is presented in [12], which is named ChronoTwigger.…”

Section: Related Workmentioning

confidence: 99%

Multiview Visualization of Software Testing Results

Maen¹

2020

IJCDS

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Software visualization can play a vital role in reducing testing efforts. It can be utilized to help testers in understanding the testing status of the code. This paper proposes a visualization technique to model the results of test cases that applied on object oriented code elements. The proposed visualization help testers to understand and to keep track on test cases and their tested code elements. Five views are proposed to cover different code levels; method, class, package, UML and system. A tool has been developed to automatically manage the software testing process and to generate the data model for the proposed visualizations. The evaluation results showed that the proposed views are useful and helpful in understanding the testing results.

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“…the adequacy of code testing [48], visualizing software faults [49], and evaluation code coverage of test suites' quality [50]. There has been a large amount of literature that deals with the visualization of test information, and a wide range of tools that have been proposed for the task of visualizing testing information.…”

Section: Visualization Of Testing Informationmentioning

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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Visualization of Unit and Selective Regression Software Tests

Cited by 5 publications

References 2 publications

A metadata driven process for assessing stability and reusability based on risk of change of software systems

A metadata driven process for assessing stability and reusability based on risk of change of software systems

Multiview Visualization of Software Testing Results

Towards Visualization of Unit Test and Source Code Relations

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