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Test automation for Markov Chain Usage Models
Keywords:
JUMBL, TML, JWebUnit, Markov chain usage models, Test automationAbstract
Statistical testing with Markov Chain Usage Models is an effective method to be used by programmers and testers during web sites development, to guarantee the software reliability. The JUMBL software works on this models; it supports model construction with the TML language and analysis, tests generation and execution and analysis of tests results. This paper is targeted at test automation for web sites development with JUMBL and JWebUnit.
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References
[1] J.H. Poore, G.H. Walton, J.A. Whittaker: “A constraint-based approach to the representation of software usage models”, Information and Software Technology, vol. 42 (2000) p. 825–833.
[2] S. J. Prowell: “JUMBL: A Tool for Model-Based Statistical Testing”, Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS’03) (2002).
[3] Software Quality Research Laboratory (University of Tennessee, Knoxville): “JUMBL 4.5 User’s Guide”, 28th July 2003.
[4] S. J. Prowell: “Computations for Markov Chain Usage Models”, Technical Report UT-CS-03-505.
[5] K.W. Miller, L.J.Morell et al.: “Estimating the probability of failure when testing reveals no failures”, IEEE Transactions on Software Engineering, Vol. 18, No 1, January 1992.
[6] S.J. Prowell , J.H. Poore: “Computing system reliability using Markov chain usage models”, The Journal of Systems and Software 73 (2004) 219–225.
[7] Kirk Sayre: “Improved techniques for software testing based on Markov Chain Usage Models” ,Ph. D. thesis. The University of Tennessee, Knoxville.December 1999.
[8] K. Sayre, J.H. Poore : “Stopping criteria for statistical testing”, Information and Software Technology 42 (2000) 851–857.
[9] S.J. Prowell: “TML: a description language for Markov chain usage models”, Information and Software Technology 42 (2000) 835–844.
[10] S.J. Prowell: “A TML Tutorial”, Software Quality Research Laboratory (University of Tennessee, Knoxville) October 27, 2000.
[12] G. H. Walton, J. H. Poore: “Generating transition probabilities to support model-based software testing”, Software –Practice and Experience. 2000; 30:1095–1106.
[13] J.A.Whittaker, Michael Thomason: “A Markov Chain model for Statistical Software Testing” ”, IEEE Transactions on Software Engineering, Vol. 20, No 10, October 1994.
[2] S. J. Prowell: “JUMBL: A Tool for Model-Based Statistical Testing”, Proceedings of the 36th Hawaii International Conference on System Sciences (HICSS’03) (2002).
[3] Software Quality Research Laboratory (University of Tennessee, Knoxville): “JUMBL 4.5 User’s Guide”, 28th July 2003.
[4] S. J. Prowell: “Computations for Markov Chain Usage Models”, Technical Report UT-CS-03-505.
[5] K.W. Miller, L.J.Morell et al.: “Estimating the probability of failure when testing reveals no failures”, IEEE Transactions on Software Engineering, Vol. 18, No 1, January 1992.
[6] S.J. Prowell , J.H. Poore: “Computing system reliability using Markov chain usage models”, The Journal of Systems and Software 73 (2004) 219–225.
[7] Kirk Sayre: “Improved techniques for software testing based on Markov Chain Usage Models” ,Ph. D. thesis. The University of Tennessee, Knoxville.December 1999.
[8] K. Sayre, J.H. Poore : “Stopping criteria for statistical testing”, Information and Software Technology 42 (2000) 851–857.
[9] S.J. Prowell: “TML: a description language for Markov chain usage models”, Information and Software Technology 42 (2000) 835–844.
[10] S.J. Prowell: “A TML Tutorial”, Software Quality Research Laboratory (University of Tennessee, Knoxville) October 27, 2000.
[12] G. H. Walton, J. H. Poore: “Generating transition probabilities to support model-based software testing”, Software –Practice and Experience. 2000; 30:1095–1106.
[13] J.A.Whittaker, Michael Thomason: “A Markov Chain model for Statistical Software Testing” ”, IEEE Transactions on Software Engineering, Vol. 20, No 10, October 1994.
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Published
2011-10-03
How to Cite
Bettinotti, A. M., & Garavaglia, M. (2011). Test automation for Markov Chain Usage Models. Journal of Computer Science and Technology, 11(02), p. 93–99. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/674
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