A Tool for Runtime Reliability Estimation and Control Using Automata Based Software Reliability Model

نویسندگان

  • RITIKA WASON
  • P. AHMED
  • QASIM RAFIQ
چکیده

-The paper presents a novel approach for runtime reliability estimation of executable software during software execution. The proposed model does not depend on post failure data analysis whose accuracy depends on assumptions about some dubious statistical distribution. Instead the model captures required estimates during runtime from state to state transition. Thus, the model computes software reliability from the actual path taken by the software at runtime. Key-Words: Automata-Based Software Reliability Model, Self-Learning Automata, Finite State Automata, Software Reliability, Probabilistic Finite State Machine.

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تاریخ انتشار 2013