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Automating Test Data Generation for Testing Context-Aware Applications
Balochistan University of Information Technology, Engineering and Management Sciences, Pakistan.
Balochistan University of Information Technology, Engineering and Management Sciences, Pakistan.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-0611-2655
2018 (English)In: Proceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS, IEEE Computer Society , 2018, p. 104-108Conference paper, Published paper (Refereed)
Abstract [en]

Context-aware applications are emerging applications in the modern era of computing. These applications can determine and adapt to situational context to provide better user experience. Testing these applications is not straightforward and poses several challenges such as developing context-aware test cases and generating test data etc. However, by employing model based testing technique, testing process for context-aware applications can be automated. To achieve maximum degree of automation, it is necessary to automate model transformation, test data generation and test cases execution. To execute test cases, test data is required and developing test data for context-aware applications is a challenging task. The aim of this study is to address this issue; thus, we propose automated test data generation for functional testing of context-aware applications. This automated test data generation can reduce testing time and cost, thus enabling test engineers to execute more testing cycles to attain higher degree of test coverage.

Place, publisher, year, edition, pages
IEEE Computer Society , 2018. p. 104-108
Keywords [en]
Context-Aware Applications, Software Testing, Test Data, Application programs, Automatic test pattern generation, Automation, Metadata, Model checking, Automated test data generation, Context aware applications, Emerging applications, Model based testing, Model transformation, Situational context, Test data generation
National Category
Computer Sciences Software Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-43069DOI: 10.1109/ICSESS.2018.8663920ISI: 000467282900021Scopus ID: 2-s2.0-85063624322ISBN: 9781538665640 (print)OAI: oai:DiVA.org:mdh-43069DiVA, id: diva2:1314701
Conference
9th IEEE International Conference on Software Engineering and Service Science, ICSESS 2018, 23 November 2018 through 25 November 2018
Available from: 2019-05-09 Created: 2019-05-09 Last updated: 2019-06-11Bibliographically approved

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Afzal, Wasif

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf