IEEE Transactions on Reliability · 1979 · 204 citations · 10 references
Software MaintenanceSoftware Reliability TestingEngineeringSoftware EngineeringSystem ReliabilitySoftware AnalysisModular ProgramOperations ResearchReliability EngineeringModular Program StructureSystems EngineeringModeling And SimulationQuantitative ManagementReliabilitySoftware ReliabilityStochastic SystemComputer ScienceProbability TheoryDependability ModellingSoftware DesignReliability ModellingProgram AnalysisSoftware TestingProcess ControlBusinessFailure RateProgram AvailabilitySystem Software
The study focuses on modular programs where control transfers between modules follow a semi‑Markov process, with each module and its interfaces modeled as Poisson failure processes. The authors aim to characterize the overall failure process of such modular programs, approximate it by an asymptotic Poisson model under high reliability, and analyze the resulting cost and availability implications. They model the program as a semi‑Markov system with Poisson module and interface failures, derive an asymptotic Poisson approximation for the overall failure process, and use it to compute cost distributions and availability, with parameters estimated from means and variances of underlying distributions. Under the limiting condition of highly reliable modules and interfaces, the model yields a simple closed‑form expression for the program’s failure rate (and mean time between failures) and provides an example calculation of program availability.
The paper treats a modular program in which transfers of control between modules follow a semi-Markov process. Each module is failure-prone, and the different failure processes are assumed to be Poisson. The transfers of control between modules (interfaces) are themselves subject to failure. The overall failure process of the program is described, and an asymptotic Poisson process approximation is given for the case when the individual modules and interfaces are very reliable. A simple formula gives the failure rate of the overall program (and hence mean time between failures) under this limiting condition. The remainder of the paper treats the consequences of failures. Each failure results in a cost, represented by a random variable with a distribution typical of the type of failure. The quantity of interest is the total cost of running the program for a time t, and a simple approximating distribution is given for large t. The parameters of this limiting distribution are functions only of the means and variances of the underlying distributions, and are thus readily estimable. A calculation of program availability is given as an example of the cost process. There follows a brief discussion of methods of estimating the parameters of the model, with suggestions of areas in which it might be used.
10