Reliability growth models for hardware and software systems based on nonhomogeneous Poisson processes: A survey

1983 ◽  
Vol 23 (1) ◽  
pp. 91-112 ◽  
Author(s):  
Shigeru Yamada ◽  
Shunji Osaki
Keyword(s):  
Growth Models ◽  
Poisson Processes ◽  
Software Systems ◽  
Reliability Growth ◽  
Nonhomogeneous Poisson Processes

Evaluation of Standard Reliability Growth Models in the Context of Automotive Software Systems

2013 ◽  
pp. 324-329 ◽  
Author(s):  
Rakesh Rana ◽  
Miroslaw Staron ◽  
Niklas Mellegård ◽  
Christian Berger ◽  
Jörgen Hansson ◽  
...  
Keyword(s):  
Growth Models ◽  
Software Systems ◽  
Reliability Growth ◽  
Automotive Software

scholarly journals A New Software Reliability Growth Model: Multigeneration Faults and a Power-Law Testing-Effort Function

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Fan Li ◽  
Ze-Long Yi
Keyword(s):  
Power Law ◽  
Software Reliability ◽  
Growth Models ◽  
Software Systems ◽  
Failure Behavior ◽  
Reliability Growth ◽  
Real World Data ◽  
Testing Effort ◽  
Software Reliability Growth ◽  
Effort Effect

Software reliability growth models (SRGMs) based on a nonhomogeneous Poisson process (NHPP) are widely used to describe the stochastic failure behavior and assess the reliability of software systems. For these models, the testing-effort effect and the fault interdependency play significant roles. Considering a power-law function of testing effort and the interdependency of multigeneration faults, we propose a modified SRGM to reconsider the reliability of open source software (OSS) systems and then to validate the model’s performance using several real-world data. Our empirical experiments show that the model well fits the failure data and presents a high-level prediction capability. We also formally examine the optimal policy of software release, considering both the testing cost and the reliability requirement. By conducting sensitivity analysis, we find that if the testing-effort effect or the fault interdependency was ignored, the best time to release software would be seriously delayed and more resources would be misplaced in testing the software.

DEBUGGING PROCESS-ORIENTED DISCRETE SOFTWARE RELIABILITY MODELING

2009 ◽  
Vol 16 (04) ◽  
pp. 357-370 ◽  
Author(s):  
SHINJI INOUE ◽  
NAOKI IWAMOTO ◽  
SHIGERU YAMADA
Keyword(s):  
Discrete Time ◽  
Software Reliability ◽  
Goodness Of Fit ◽  
Growth Models ◽  
Reliability Growth ◽  
Reliability Modeling ◽  
New Approach ◽  
Time Modeling ◽  
Software Reliability Growth ◽  
Discrete Time Modeling

This paper discusses an new approach for discrete-time software reliability growth modeling based on an discrete-time infinite server queueing model, which describes a debugging process in a testing phase. Our approach enables us to develop discrete-time software reliability growth models (SRGMs) which could not be developed under conventional discrete-time modeling approaches. This paper also discuss goodness-of-fit comparisons of our discrete-time SRGMs with conventional continuous-time SRGMs in terms of the criterion of the mean squared errors, and show numerical examples for software reliability analysis of our models by using actual data.

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