Dynamic testing from bounded data type specifications

  • Agnès Arnould
  • Pascale Le Gall
  • Bruno Marre
Session 7 Verification
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1150)


Due to practical limitations in software and hardware, data type implementations are always bounded. Such limitations are a frequent source of faults which are difficult to find out. As soon as boundaries are clearly identified in a specification, functional testing should be able to address any boundary fault.

We propose to enrich a data type specification formalism, namely algebraic specifications, allowing a natural description of data type boundaries. This enhancement allows us to adapt the existing testing theory, the method and the tool, initially dedicated to functional testing from unbounded data type specifications.

Several examples of test data selection with the LOFT tool, from two bounded data type specifications, will illustrate the benefit of our approach: an assisted test selection process, formally defined in a functional testing theory, allowing adequate coverage of both data types bounds and the definition domain of the specified operations.


functional testing software verification formal specifications bounded data types test data set selection 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    A. Arnould, P. Le Gall, and B. Marre. Dynamic testing from bounded data type specifications. Technical report, L.R.I, Université Paris-Sud, 1996.Google Scholar
  2. 2.
    G. Bernot. Testing against formal specifications: a theoretical view. In TAP-SOFT'91, LNCS 494, pages 99–119, Brighton UK, 1991. Springer Verlag.Google Scholar
  3. 3.
    G. Bernot, M.C. Gaudel, and B. Marre. Software testing based on formal specifications: a theory and a tool. Software Engineering Journal, 6(6):387–405, 1991.Google Scholar
  4. 4.
    G. Bernot, P. Le Gall, and M. Aiguier. Label algebras and exception handling. Journal of Science of Computer Programming, 23:227–286, 1994.Google Scholar
  5. 5.
    M. Breu. Bounded implementation of algebraic specifications. In Recent Trends in Data Type Specification, LNCS 655, pages 181–198, Dourdan, France, 1991. Springer Verlag.Google Scholar
  6. 6.
    E. Brinksma. A theory for the derivation of tests. 8th International Conference on Protocol Specification, Testing and Verification, North-Holland, 1988.Google Scholar
  7. 7.
    P. Dauchy, M.-C. Gaudel, and B. Marre. Using algebraic specifications in software testing: a case study on the software of an automatic subway. Journal of Systems and Software, 21(3):229–244, 1993.Google Scholar
  8. 8.
    J. Dick and A. Faivre. Automating the generation and sequencing of test cases from model-based specifications. In FME'93, LNCS 670, pages 268–284. Springer-Verlag, 1993.Google Scholar
  9. 9.
    R.K. Dong and P.G. Frankl. The astoot approach to testing object-oriented programs. ACM Transactions on Software Engineering and Methodology, 3(2), 1994.Google Scholar
  10. 10.
    H. Ehrig and B. Mahr. Fundamentals of algebraic specification. EATCS Monographs on Theoretical Computer Science, 6, 1985.Google Scholar
  11. 11.
    M.C. Gaudel. Testing can be formal, too. In TAPSOFT'95, LNCS 915, Aarhus, Denmark, 1995. Springer Verlag.Google Scholar
  12. 12.
    M. Gogolla, K. Drosten, U. Lipeck, and H. Ehrig. Algebraic and operational semantics of specification allowing exceptions and errors. Theorical Computer Science 34, p. 289–313, 1984.Google Scholar
  13. 13.
    B. Jeng and E.J. Weyuker. A simplified domain-testing strategy. ACM Transactions on Software Engineering and Methodology, 3(3):254–270, July 1994.Google Scholar
  14. 14.
    P. Le Gall and A. Arnould. Formal specification and test: correctness and oracle. In Recent Trends in Data Type Specification, Oslo, Norway, LNCS, 1996.Google Scholar
  15. 15.
    B. Marre. Toward automatic test data set selection using Algebraic Specifications and Logic Programming. ICLP'91, Paris, 25–28, MIT Press, 1991.Google Scholar
  16. 16.
    B. Marre, P. Thevenod-Fosse, H. Waeselynck, P. Le Gall, and Y. Crouset. An Experimental Evaluation of Formal Testing and Statistical Testing. SAFECOMP'92, Switzerland, Ed. Heinz H. Frey, Pergamon Press, 1992.Google Scholar
  17. 17.
    D.H. Pitt and Freestone D. The derivation of conformance tests from lotos specifications. IEEE Transactions on Software Engineering, 16(12): 1337–1343, 1990.Google Scholar
  18. 18.
    M. Presburger. Über die Vollständingen einer gewissen Systems der Arithmetik ganzer Zahlen, in welchem die Addition als einzige Operation hervortritt. In Comptes Rendus du premier Congrès des Mathématiciens des Pays slaves, Warszawa, 1929.Google Scholar
  19. 19.
    Dssouli R. and Bochmann G. Conformance testing with multiple observers. In In Protocol Specification Testing and Verification, North-Holland, pages 217–229, 1987.Google Scholar
  20. 20.
    D. Sannella and A. Tarlecki. Toward formal development of programs from algebraic specification: implementation revisited. Acta Informatica, 25:233–281, 1988.Google Scholar
  21. 21.
    P. Stocks and D.A. Carrington. Test template: A specification-based testing framework. In 15th ICSE, pages 405–414, 1993.Google Scholar
  22. 22.
    L.J. White and I.A. Perrera. An alternative measure for error analysis of the domain testing strategy. In Workshop on Software Testing, IEEE Computer Society Order 723, 1986.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1996

Authors and Affiliations

  • Agnès Arnould
    • 1
  • Pascale Le Gall
    • 2
  • Bruno Marre
    • 1
  1. 1.L.R.I, URA CNRS 410Université de Paris-SudOrsay CedexFrance
  2. 2.L.a.M.I.Université d'ÉvryEvry CedexFrance

Personalised recommendations