- Adri82.W. R. Adrion, M. A. Branstad, and J. C. Cherniavsky, "Verification, validation, and testing of computer software," ACM Computing Surveys, Vol. 14, No. 2, PP. 159-192, June 1982. Google ScholarDigital Library
- Barn82.V. Barnett, Comparative Statistical Inference, Wiley, New York, NY, 1982.Google Scholar
- Box78.G. E. P. Box, W. G. Hunter, J. S. Hunter, Statistics for Experimenters, Wiley, New York, NY, 1978.Google Scholar
- Brow75.J. R. Brown and M. Lipow, "Testing for software reliability", Proceedings of the International Conference on Reliable Software, Los Angeles, CA, April 1975, pp. 518-527. Google ScholarDigital Library
- Budd80.T. A. Budd, R. A. DeMillo, R. J. Lipton, and F. G. Sayward, "Theoretical and empirical studies on using program mutation to test the functional correctness of programs ," Proceedings of the 7th Annual Symposium on Principles of Programming Languages, Las Vegas, NV, January 1980. Google ScholarDigital Library
- Calu88.C. Calude, Theories of Computational Complexity, North-Holland, Amsterdam, 1988. Google ScholarDigital Library
- Chai87.G. J. Chaitin, Algorithmic Information Theory, Cambridge University Press, Cambridge, England, 1987. Google ScholarDigital Library
- Cher86.J. C. Cherniavsky and C. H. Smith, "A theory of program testing with applications ," Proceedings of the Workshop on Soflware Testing, Banff, Alberta, July 1986, IEEE Computer Society Press, pp. 110-21.Google Scholar
- Cho87.C. Cho, Quality Programming, Wiley, New York, NY, 1987.Google Scholar
- Coch77.W. G. Cochran, Sampling Techniques, Wiley, New York, NY, 1977.Google Scholar
- Cohe89.L. J. Cohen, The Philosophy of Induction and Probability, oxford University Press, Oxford, England, 1989.Google Scholar
- Corm90.T. H. Cormen, C. E. Leiserson, and R. L. Rivest, Introduction to Algorithms, McGraw-Hill, New York, NY, 1990. Google ScholarDigital Library
- Curr86.P. A. Currit, M. Dyer, H. D. Mills, "Certifying the reliability y of software," IEEE Transactions on Software Engineering, Vol. SE-12, No. 1, pp. 3-11, January 1986. Google ScholarDigital Library
- Dale87.C. Dale, "Data requirements for software reliability prediction," Software Reliability: Assessment and Achievement, B. Littlewood editor, Blackwell, London, pp. 144-153, 1987.Google Scholar
- DeGr86.M. H. DeGroot, Probability and Statistics, Addison-Wesley, Reading, MA, 1986.Google Scholar
- DeMi79.R. A. DeMillo, R. J. Lipton, and A. J. Perlis, "Social processes and proofs of theorems and programs: Communications of the ACM, Vol. 22, No. 5, pp. 271-280, May 1979. Google ScholarDigital Library
- Dijk76.E. W. Dijkstra, A Discipline of Programming, Prentice-Hall, New York, NY, 1976. Google ScholarDigital Library
- Dura80.J. W. Duran and J. J. Wiorkowski, "Quantifying software validity by sampling," IEEE Transactions on Reliability, Vol. R- 29, No. 2, pp. 141-144, June 1980.Google ScholarCross Ref
- Dura81.J. W. Duran and S. Ntafos, "A report on random testing," Proceedings of the 5th International Conference on Software Engineering, 1981, IEEE Computer Society, pp. 179-183. Google ScholarDigital Library
- Dura84.J. W. Duran and S. Ntafos,"An evaluation of random testing," IEEE Transactions on Software Engineering, Vol. SE-10, pp. 438-444, July 1984.Google ScholarDigital Library
- Fine73.T. L. Fine, Theories of Probabihty, Academic Press, New York, NY, 1973.Google Scholar
- Foy67.R. W. Floyd, "Assigning meaning to programs," Proceedings of the Symposium on Applied Mathematics, American Mathematical Society, New York, NY, pp. 19-31, 1967.Google Scholar
- Goel85.A. L. Goel, "Soft ware reliability models: assumptions, limitations, applicability," IEEE Transactions on Software Engineering, Vol. SE11, No. 12, pp. 1411-1423, December 1985.Google ScholarDigital Library
- Haml87.D. Hamlet, "Probable correctness theory," Information Processing Letters, Vol. 25, pp. 17-25, April 1987. Google ScholarDigital Library
- Haml90.D. Hamlet and R. Taylor, "Partition testing does not inspire confidence," IEEE Transactions on Software Engineering, Vol. 16, No. 12, pp. 1401-1411, December 1990. Google ScholarDigital Library
- Hoar69.C. A. R. Hoare, "An axiomatic basis of computer programming," Communications of the ACM, Vol. 12, No. 10, pp. 576- 583, October 1969. Google ScholarDigital Library
- Howd76.W. E. Howden, "Reliability of the path analysis test ing strategy," IEEE Transactions on Software Engineering, Vol. SE-2, No. 3, pp. 280-295, September 1976.Google ScholarDigital Library
- Howd87.W. E. Howden, Functional Program Testing and Analysis, McGraw-Hill, New York, NY, 1987. Google ScholarDigital Library
- Kief87.J. C. Kiefer, Introduction to Statistical Inference, Springer, New York, NY, 1987. Google ScholarDigital Library
- Klem88.E. D. Klemke, R. Hollinger, and A. D. Kline, editors, Introductory Readings in the Philosophy of Science, Prometheus Books, Buffalo, NY, 1988.Google Scholar
- Knut81.D. E. Knuth, The Art of Computer Programming, Volume 2: Seminumerical Algorithms, Addison Wesley, Reading, MA, 1981. Google ScholarDigital Library
- Knut89.D. E. Knuth, "The errors of TeX ," Software Practice and Experience, Vol. 19, No. 7, pp. 607-685, July 1989. Google ScholarDigital Library
- Leve88.N. G. Leveson, "Software safety: why, what, and how," ACM Computing Surveys, Vol. 18, No. 2, pp. 25-69, June 1986. Google ScholarDigital Library
- Li90.M. Li and P. M. B. Vit~nyi, "Kolmogorov complexity and its applications," Handbook of Theoretical Computer Science, Volume A, Elsevier, New York, NY, 1990. Google ScholarDigital Library
- Litt80.B. Littlewood, "Theories of software reliability: How good are they and how can they be improved?", IEEE Transactions on Software Engineering, Vol. SE-6, No. 5, pp. 489-500, September 1980.Google ScholarDigital Library
- Litt90.B. Littlewood, "Modelling growth in software reliability," Software Reliability Handbook, P. Rook editor, Elsevier, New York, NY, pp. 137-154, 1990.Google Scholar
- Loec84.J. Loeckx and K. Sieber, Foundations of Program Verification, Wiley, New York, NY, 1984. Google ScholarDigital Library
- Mill72.H. D. Mills, "On the statistical validation of computer programs," IBM Federal Systems Division, Gaithersburg, MD, Rep. 72-6015, 1972.Google Scholar
- Mill88.D. R. Miller, "The role of statistical modelling and inference in software quality assurance," CSR Workshop on Software Certification, Gatwick, England, September 1988.Google Scholar
- Mise39.R. von Mises, Probability, Statistics, and Truth, MacMillan, New York, NY, 1939.Google Scholar
- Musa87.J. D. Muss, A. Iannino, K. Okumoto, Software Reliability: Measurement, Prediction, Application, McGraw-Hill, New York, NY, 1987. Google ScholarDigital Library
- Parn90.D. L. Parnas, A. J. van Schouwen, and S. P. Kwan, "Evaluation of safety critical software," Communications of the ACM, Vol. 33, No. 6, pp. 636-651, June 1990. Google ScholarDigital Library
- Roge67.H. Rogers, Theory of Recursive Functions and Effective Computability, McGraw- Hill, New York, NY, 1967. Google ScholarDigital Library
- Rowl81.J. H. Rowland and P. J. Davis, "On the use of transcendental for program testing," Journal of the ACM, Vol. 28, No. 1, pp. 181-190, January 1981. Google ScholarDigital Library
- Thay78.T. A. Thayer, M. Lipow, and E. C. Nelson, Software Reliability, TRW Series of Software Technology 2, North Holland, New York, NY, 1978.Google Scholar
- Weis86.S. N. Weiss and E. J. Weyuker, "A generalized domain-based definition of software reliability," Proceedings of the Workshop on Software Testing, Banff, Alberta, July 1986, IEEE Computer Society Press, PP. 98-107.Google Scholar
Index Terms
- Reliability, sampling, and algorithmic randomness
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