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A Software Performance Evaluation Model with Mixed Debugging Process

혼합수리 과정을 고려한 소프트웨어성능 평가 모형

  • Jang, Kyu-Beom (Department of Finance & Information Statistics, Hallym University) ;
  • Lee, Chong-Hyung (Department of Hospital Management, Konyang University)
  • 장규범 (한림대학교 통계학과) ;
  • 이종형 (건양대학교 관저캠퍼스 병원관리학과)
  • Received : 20111000
  • Accepted : 20111000
  • Published : 2011.11.30

Abstract

In this paper, we derive an software mixed debugging model based on a Markov process, assuming that the length of time to perform the debugging is random and its distribution may depend on the fault type causing the failure. We assume that the debugging process starts as soon as a software failure occurs, and either a perfect debugging or an imperfect debugging is performed upon each fault type. One type is caused by a fault that is easily corrected and in this case, the perfect debugging process is performed. An Imperfect debugging process is performed to fix the failure caused by a fault that is difficult to correct. Distribution of the first passage time and working probability of the software system are obtained; in addition, an availability function of a software system which is the probability that the software is in working at a given time, is derived. Numerical examples are provided for illustrative purposes.

본 논문에서는 소프트웨어의 고장수리 과정 중 완전 수리와 불완전 수리를 모두 고려하는 혼합수리 모형을 제안하려고 한다. 이를 위해 소프트웨어가 가지고 있는 전체 결함의 유형을 고치기 쉬운 결함 유형과 고치기 어려운 결함 유형으로 나누고, 고치기 쉬운 결함의 경우에서는 수리 과정 중 결함을 완전하게 고친다고 가정한다. 또한 고치기 어려운 결함 유형은 완전 또는 불완전 수리가 가능하도록 가정하며, 이러한 가정과 마코프 과정(Markov process)하에서 소프트웨어 성능 평가를 위한 측도 중에 하나인 소프트웨어 가용성(software availability)을 제시하고자 한다.

Keywords

References

  1. Barlow, R. E. and Proschan, F. (1981). Statistical Theory of Reliability and Life Testing: Reliability Models, Silver Spring, Maryland.
  2. Lee, C. H., Nam, K. H. and Park, D. H. (2001). Optimal software release policy based on Markovian perfect debugging model, Communications in Statistics: Theory and Methods, 30, 2329-2342. https://doi.org/10.1081/STA-100107689
  3. Lee, C. H. and Park, D. H. (2003). Markovian imperfect software debugging model and its performance measures, Stochastic Analysis and Applications, 21,849-864. https://doi.org/10.1081/SAP-120022866
  4. Moranda, P. B. (1975). Prediction of software reliability during debugging, Proceedings of the 1975 Annual Reliability and Maintainability Symposium, 327-332.
  5. Shooman, M. L. and Trivedi, A. K. (1976). A many-state Markov model for computer software performance parameters, IEEE Transactions on Reliability, R-25, 66-68. https://doi.org/10.1109/TR.1976.5214978
  6. Tokuno, K. and Yamada, S. (2007). User-oriented and -perceived software availability measurement and assessment with environmental factors, Journal of the Operations Research Society of Japan, 50, 444-462. https://doi.org/10.15807/jorsj.50.444
  7. Tokuno, K. and Yamada, S. (2010). Availability-based software perform ability Model with user-perceived performance degradation, International Journal of Software Engineering and Its Applications, 4, 1-14

Cited by

  1. Software Taskset Processing Evaluation Based on a Mixed Debugging Process vol.19, pp.4, 2012, https://doi.org/10.5351/CKSS.2012.19.4.571