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Property-based testing of SPARQL queries

Published:01 September 2017Publication History

ABSTRACT

In this paper we describe a property-based testing tool for SPARQL. Given a SPARQL query, the tool randomly generates test cases which consist on instances of an ontology. The tool checks the well typed-ness of the SPARQL query as well as the consistency of the test cases with the ontology axioms. With this aim, a type system has been defined for SPARQL. Test cases are later used to execute the SPARQL query. The output of the SPARQL query is tested with a Boolean property which is defined in terms of membership of ontology individuals to ontology classes. The testing tool reports counterexamples when the Boolean property is not satisfied.

References

  1. Jesús M. Almendros-Jiménez and Antonio Becerra-Terón. 2015. XQuery Testing from XML Schema Based Random Test Cases. In Database and Expert Systems Applications,DEXA'2015. Vol. LNCS 9262. Springer, 268--282. Google ScholarGoogle ScholarCross RefCross Ref
  2. Jesús M. Almendros-Jiménez and Antonio Becerra-Terón. 2016. Automatic Generation of Ecore Models for Testing ATL Transformations. In Model and Data Engineering, MEDI'2016. Vol. LNCS 9893. Springer, 16--30. Google ScholarGoogle ScholarCross RefCross Ref
  3. Jesús M Almendros-Jiménez and Antonio Becerra-Terón. 2017. Automatic property-based testing and path validation of XQuery programs. Software Testing, Verification and Reliability 27, 1--2 (2017).Google ScholarGoogle ScholarCross RefCross Ref
  4. Saswat Anand, Edmund K Burke, Tsong Yueh Chen, John Clark, Myra B Cohen, Wolfgang Grieskamp, Mark Harman, Mary Jean Harrold, Phil McMinn, et al. 2013. An orchestrated survey of methodologies for automated software test case generation. Journal of Systems and Software 86, 8 (2013), 1978--2001.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Guillaume Bagan, Angela Bonifati, Radu Ciucanu, George HL Fletcher, Aurélien Lemay, and Nicky Advokaat. 2017. gMark: Schema-driven Generation of Graphs and Queries. IEEE Transactions on Knowledge and Data Engineering 29, 4 (2017), 856--869. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Antonia Bertolino, Jinghua Gao, Eda Marchetti, and Andrea Polini. 2007. Systematic generation of XML instances to test complex software applications. In Rapid Integration of Software Engineering Techniques. Springer, 114--129. Google ScholarGoogle ScholarCross RefCross Ref
  7. Chandrasekhar Boyapati, Sarfraz Khurshid, and Darko Marinov. 2002. Korat: Automated testing based on Java predicates. In ACM SIGSOFT Software Engineering Notes, Vol. 27. ACM, 123--133.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Stefan Brass and Christian Goldberg. 2006. Semantic errors in SQL queries: A quite complete list. Journal of Systems and Software 79, 5 (2006), 630--644. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Rafael Caballero, Yolanda García-Ruiz, and Fernando Sáenz-Pérez. 2010. Applying constraint logic programming to SQL test case generation. In International Symposium on Functional and Logic Programming. Springer, 191--206. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. David Chays, Yuetang Deng, Phyllis G Frankl, Saikat Dan, Filippos I Vokolos, and Elaine J Weyuker. 2004. An AGENDA for testing relational database applications. Software Testing, verification and reliability 14, 1 (2004), 17--44. Google ScholarGoogle ScholarCross RefCross Ref
  11. Koen Claessen and John Hughes. 2011. QuickCheck: a lightweight tool for random testing of Haskell programs. ACM SIGPLAN notices 46, 4 (2011), 53--64. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Claudio De La Riva, María José Suárez-Cabal, and Javier Tuya. 2010. Constraint-based test database generation for SQL queries. In Proceedings of the 5th Workshop on Automation of Software Test. ACM, 67--74. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Birte Glimm, Ian Horrocks, Boris Motik, Giorgos Stoilos, and Zhe Wang. 2014. HermiT: an OWL 2 reasoner. Journal of Automated Reasoning 53, 3 (2014), 245--269. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Christian Grun. 2016. BaseX. The XML Database. (2016). http://basex.org.Google ScholarGoogle Scholar
  15. Yuanbo Guo, Zhengxiang Pan, and Jeff Heflin. 2005. LUBM: A benchmark for OWL knowledge base systems. Web Semantics: Science, Services and Agents on the World Wide Web 3, 2 (2005), 158--182. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Muhammad Akhter Javid and Suzanne M. Embury. 2012. Diagnosing faults in embedded queries in database applications. In Proceedings of the 2012 Joint EDBT/ICDT Workshops. ACM, 239--244. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Frédéric Jouault, Freddy Allilaire, Jean Bézivin, and Ivan Kurtev. 2008. ATL: A model transformation tool. Science of computer programming 72, 1 (2008), 31--39. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Gregory M Kapfhammer, Phil McMinn, and Chris J Wright. 2013. Search-based testing of relational schema integrity constraints across multiple database management systems. In 2013 IEEE Sixth International Conference on Software Testing, Verification and Validation. IEEE, 31--40.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Sarfraz Khurshid and Darko Marinov. 2004. TestEra: Specification-based testing of Java programs using SAT. Automated Software Engineering 11, 4 (2004), 403--434. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Dimitris Kontokostas, Patrick Westphal, Sören Auer, Sebastian Hellmann, Jens Lehmann, and Roland Cornelissen. 2014. Databugger: a test-driven framework for debugging the web of data. In Proceedings of the 23rd International Conference on World Wide Web. ACM, 115--118. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Dimitris Kontokostas, Patrick Westphal, Sören Auer, Sebastian Hellmann, Jens Lehmann, Roland Cornelissen, and Amrapali Zaveri. 2014. Test-driven evaluation of linked data quality. In Proceedings of the 23rd international conference on World Wide Web. ACM, 747--758. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Levi Lúcio, Bruno Barroca, and Vasco Amaral. 2010. A technique for automatic validation of model transformations. In Model Driven Engineering Languages and Systems. Springer, 136--150. Google ScholarGoogle ScholarCross RefCross Ref
  23. Manolis Papadakis and Konstantinos Sagonas. 2011. A PropEr Integration of Types and Function Specifications with Property-Based Testing. In Proceedings of the 2011 ACM SIGPLAN Erlang Workshop. ACM Press, New York, NY, 39--50. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Michael Schmidt, Thomas Hornung, Georg Lausen, and Christoph Pinkel. 2009. SP2Bench: a SPARQL performance benchmark. In 2009 IEEE 25th International Conference on Data Engineering. IEEE, 222--233.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Mark Utting, Alexander Pretschner, and Bruno Legeard. 2012. A taxonomy of model-based testing approaches. Software Testing, Verification and Reliability 22, 5 (2012), 297--312. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Priscilla Walmsley. 2007. XQuery - search across a variety of XML data. O'Reilly. I--XV, 1--491 pages.Google ScholarGoogle Scholar
  27. Jian Zhang, Chen Xu, and S-C Cheung. 2001. Automatic generation of database instances for white-box testing. In Computer Software and Applications Conference, 2001. COMPSAC 2001. 25th Annual International. IEEE, 161--165.Google ScholarGoogle ScholarCross RefCross Ref

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    • Published in

      cover image ACM Other conferences
      DBPL '17: Proceedings of The 16th International Symposium on Database Programming Languages
      September 2017
      99 pages
      ISBN:9781450353540
      DOI:10.1145/3122831

      Copyright © 2017 ACM

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      Publication History

      • Published: 1 September 2017

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      DBPL '17 Paper Acceptance Rate10of15submissions,67%Overall Acceptance Rate10of15submissions,67%

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