Variations in Jelinski-Moranda Model
JM Model is one of the first software reliability models. Different Researchers try to modify this model with respect to different parameters. Here are some of the parameters listed below.
- Lipow Modified Version of JM Geometric Model
- Sukert Modified Schick Wolverton Model
- Schick Wolverton Model
- GO-Imperfect Debugging Model
- Jelinski-Moranda Geometric Model
- Little-Verrall Bayesian Model
- Shanthikumar General Markov Model
- An Error Detection Model for Application during Software Development
- The Langberg Singpurwalla Model
- Jewell Bayesian Software Reliability Model
- Quantum Modification to the JM Model
- Optimal Software Released Based on Markovian Software Reliability Model
- A Modification to the Jelinski-Moranda Software Reliability Growth Model Based on Cloud Model Theory
- Modified JM Model with imperfect Debugging Phenomenon
Jelinski Moranda software reliability model – Software Engineering
The Jelinski-Moranda Software Reliability Model is a mathematical model used to predict the reliability of software systems. It was developed by M.A. Jelinski and P.A. Moranda in 1972 and is based on the assumption that the rate of software failures follows a non-homogeneous Poisson process.
The Jelinski-Moranda (JM) software reliability model is a mathematical model used to predict the reliability of a software system over time. The model assumes that the software system can be represented as a series of independent components, each with its own failure rate. The failure rate of each component is assumed to be constant over time.
Table of Content
- Assumptions Based on Jelinski-Moranda Model
- Purpose of Jelinski Moranda Software Reliability Model
- Characteristics of the Jelinski Moranda Model
- Variations in Jelinski-Moranda Model
- Advantages of the Jelinski-Moranda (JM) Software Reliability Model
- Disadvantages of the Jelinski-Moranda (JM) Software Reliability Model
- Future Developments
- Questions For Practice
- FAQ’s
The model assumes that software failures occur randomly over time and that the probability of failure decreases as the number of defects in the software is reduced.
The Jelinski-Moranda model uses an exponential distribution to model the rate of fault detection and assumes that the fault detection rate is proportional to the number of remaining faults in the software. The model can be used to predict the number of remaining faults in the software and to estimate the time required to achieve the desired level of reliability.