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Using Autonomous Agents for Software Testing Based on JADE
Mälardalen University, School of Innovation, Design and Engineering.
2019 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The thesis work describes the development of a multiagent testing application (MTA) based on an agent approach for solving challenges in regression testing domain, such as: reducing the complexity of testing, optimizing the time consumption, increasing the efficiency and implementing the automation of this approach for regression testing. All these challenges related to effectiveness and cost, can be represented as measures of achieved code coverage and number of test cases created. A multiagent approach is proposed in this thesis since it allows the implementation of the autonomous behaviour and optimizes the data processing in a heterogeneous environment. In addition, the agent-based approach provides flexible design methods for building multitask applications and conducting parallel task execution. However, all of these advantages of using an agent-based approach need to be investigated in the regression testing domain for realistic scenarios. Therefore, a hypothesis was formulated in order to investigate the efficiency of the MTA approach using an experiment as the main research method for obtaining results. The thesis includes a comparison analysis between the MTA and well-known test case generation tools (i.e. EvoSuite and JUnitTools) for identifying the differences in terms of efficiency and code coverage achieved. The comparison results showed advantages of the MTA within regression testing context due to optimal level of code coverage and test cases. The outcome of the thesis work moves toward solving the aforementioned problems in regression testing domain and shows some advantages of using the multagent approach within regression testing context.

Place, publisher, year, edition, pages
2019. , p. 55
Keywords [en]
software testing, regression testing, autonomous agents, test case selection, coverage optimization, JADE
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-45319OAI: oai:DiVA.org:mdh-45319DiVA, id: diva2:1355268
Subject / course
Computer Science
Presentation
2019-09-19, R2-141, Högskoleplan 1, Västerås, 15:30 (English)
Supervisors
Examiners
Available from: 2019-10-23 Created: 2019-09-27 Last updated: 2019-10-23Bibliographically approved

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1112131415161714 of 30
CiteExportLink to record
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Cite
Citation style
  • apa
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
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  • sv-SE
  • Other locale
More languages
Output format
  • html
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