Practical Specificity of Models of Software Reliability Exploitation
Vestnik Natsional'nogo issledovatel'skogo yadernogo universiteta “MIFI”, 2017, vol. 6, no. 5, pp. 458–465. The Mills model, which is one of the basic software reliability models, has been analyzed in view of its practical application for analyzing software reliability. The number of artificial errors that should be inserted before testing and should be found to determine the number of initial errors in a program, as well as the validity of this prognostication, is calculated. It is emphasized that the Mills model provides only a certain forecast for the number of errors in the program. To obtain this forecast with a validity of about 0.5, it is enough to introduce about as many “artificial” errors as are expected in the debugged program. It is shown that the search for all but one artificial errors insignificantly reduces the degree of confidence in the result but it significantly reduces the time of testing. The main drawbacks of the Mills model are indicated: (i) the “seeded” errors should be distributed approximately in the same proportion as those in the debugged program and (ii) it is advisable to obtain in advance the expected number of errors in the program with some other reliability models such as Schuman or Jelinski–Moranda models. The main directions for further investigations related to the selection of a software reliability model for the step-by-step analysis of the results obtained in the study of the program by means of the Mills model with incompletely found seeded errors.