Test case generation based on mutations over user execution traces

Paiva, Ana C. R.; Restivo, André; Almeida, Sheylla Susan Moreira da Silva de

doi:10.1007/s11219-020-09503-4

Cited by 9 publications

(2 citation statements)

References 13 publications

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“…It results in a time consuming process, which usually does not scale well. Finally, other approaches, e.g., (Paiva et al, 2020), propose a record and replay technique of event sequences extracted from event logs. Unfortunately, this technique does not work well for service compositions, as SUT may include various possibly non deterministic services, or not testable ones.…”

Section: Introductionmentioning

confidence: 99%

Automated Test Case Generation for Service Composition from Event Logs

Salva,

Sue

2023

2023 38th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)

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Service compositions, e.g., Internet of Things (IoT) service compositions or RESTful service compositions are widely used in the industry to enhance the interoperability and integration of their systems and applications. Testing service compositions is considered as a long and difficult activity as each service may be deployed on different servers and often requires specialised testing tools. This paper proposes an automated approach to help developers generate test cases for experimenting every service in isolation. These test cases can be later adapted or used for regression testing. This approach is based upon 4 steps that aim to: 1. extract traces from event logs, 2. gather similar behaviours to reduce the final number of test cases and to extract knowledge, which will be used while the test case generation, 3. produce generic test cases given under the form of IOTS (Input Output Transition Systems) that encode the use of mock components and provide test verdicts, 4. generate test scripts and mock components for every service. We evaluate our approach on 4 Web service compositions and show that our algorithms build effective test cases and scale well with the event log size.

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Section: Introductionmentioning

confidence: 99%

Automated Test Case Generation for Service Composition from Event Logs

Salva,

Sue

2023

2023 38th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW)

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“…Inthesoftwaredevelopmentstrategy,thetestcasescanbegeneratedwithUMLdiagrams.Based onthefunctionality,theproblemsandthebugsareidentifiedearliertosavetime.Thetestcasesare generatedsuchthatirrelevanttestcasesarereducedusingtheframeworkofobjectsandclasses. Varioustraditionalmethodsareusedonvariousapplications,likeJava,wherethetestsareeffectively generatedandexecuted (Dhir,2012).Testingistheprocedureofperformingthesourcecodebyvarying inputsunderdifferentscenariosandisvariouscontextstoensurewhethertheactualperformanceof thesystemmettheexpectedbehaviorinallthescenariosandcontexts (Zamani&Hemmati,2021) Kumar,etal.,2020).However,softwaretestingisacomplexactivity (Bertolino,2007;Paiva et al,2020).Thesoftwarebecomesmorecomplexandsotestingtheactualbehaviormanuallyisnot feasibleinthesystem (Moreiraet al,2017;Paivaet al,2020).Hence,automaticsoftwaretestisthe solutiontohandletherestrictionoftimeandthecomputationalcomplexity.However,differentsoftware testingtoolsareavailablesuchthattheyareclassifiedbasedontheircriteria (Poston&Sexton,1992). Withregardstothedegreeofautomation,mostofthetoolsonlyautomatetestexecution,whereas theothersautomatethegenerationofthetestcase,whicharenotrequiredtobeprintedbythetesters manually,buttheyarestillneededtoexecuteitphysically (Paivaet al,2020).…”

Section: Introductionmentioning

confidence: 99%

Spider Monkey Particle Swarm Optimization (SMPSO) With Coverage Criteria for Optimal Test Case Generation in Object-Oriented Systems

Panigrahi

Jena

2022

International Journal of Open Source Software and Processes

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System modeling in software engineering describes the procedure of creating a demonstration of real system in a conceptual way to know the system behavior. The software testing promotes reusing the model for the function of testing and this accelerates test case generation development. The test case generation verifies the reliability of system through enhanced test coverage. Test cases are the set of variables or conditions that defines the quality of product and level of correctness. This research aims to develop a method named Spider Monkey Particle Swarm Optimization (SMPSO) algorithm to generate test case using UML diagram. Accordingly, the proposed algorithm effectively generates the optimal test case by UML diagram through the construction of control graph. The proposed method achieved the coverage as 76, and generates the number of test cases as 82413.

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