Bayesian Software Prediction Models. Volume 1. An Imperfect Debugging Model for Reliability and other Quantitative Measures of Software Systems

Abstract

In this report a stochastic model for software failure phenomena is developed for the case when the errors are not corrected with certainty. Expressions for several quantities of interest are derived to establish quantitative measures for software performance assessment. Approximations for large-scale software systems using a gamma distribution are also discussed. Numerical examples are used to illustrate the computations and usefulness of various quantities.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1978
Accession Number
ADA057870

Entities

People

  • Amrit L. Goel
  • K. Okumoto

Organizations

  • Syracuse University

Tags

Communities of Interest

  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Computer Programming
  • Computer Programs
  • Computers
  • Debugging
  • Information Science
  • Markov Processes
  • Mathematical Models
  • Models
  • Operations Research
  • Probabilistic Models
  • Probability
  • Probability Distributions
  • Random Variables
  • Reliability
  • Software Development
  • Stochastic Processes

Fields of Study

  • Computer science
  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Calculus or Mathematical Analysis
  • Database Systems and Applications

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference