A unified approach of testing coverage‐based software reliability growth modelling with fault detection probability, imperfect debugging, and change point

2018 ◽  
Vol 31 (3) ◽  
pp. e2150 ◽  
Author(s):  
Subhashis Chatterjee ◽  
Ankur Shukla
Keyword(s):  
Fault Detection ◽  
Software Reliability ◽  
Change Point ◽  
Detection Probability ◽  
Reliability Growth ◽  
Growth Modelling ◽  
Unified Approach ◽  
Imperfect Debugging ◽  
Software Reliability Growth ◽  
Testing Coverage

Change point–based software reliability model under imperfect debugging with revised concept of fault dependency

2016 ◽  
Vol 230 (6) ◽  
pp. 579-597 ◽  
Author(s):  
Subhashis Chatterjee ◽  
Ankur Shukla
Keyword(s):  
Software Reliability ◽  
Change Point ◽  
Growth Models ◽  
Reliability Growth ◽  
Imperfect Debugging ◽  
Software Reliability Growth Models ◽  
Software Reliability Growth ◽  
Fault Dependency ◽  
Different Characteristics ◽  
Types Of Faults

A detailed study about the characteristics of different types of faults is necessary to enhance the accuracy of software reliability estimation. Over the last three decades, some software reliability growth models have been proposed considering the possibility of existence of two types of faults in a software: (1) independent and (2) dependent faults. In these software reliability growth models, it is considered that the removal of a leading fault or independent fault causes detection of corresponding dependent faults. In practical, it is noticed that some dependent faults are possible in a software which are removed during the removal of other faults. Moreover, dependent faults may have different characteristics, which cannot be ignored. Considering these facts, a detailed study about the different characteristics of both dependent and independent faults has been performed, and based on this study, dependent faults have been categorized into different categories. Furthermore, a new software reliability growth model has been proposed with revised concept of fault dependency under imperfect debugging by introducing the fault removal proportionality. In addition, the effect of change point on model’s parameters due to different environmental factors has been considered. The fault reduction factor is considered as a proportionality function. Experimental results establish the fact that the performance of the proposed model is better with respect to estimated and predicted cumulative number of faults on some real software failure datasets.

Markovian Software Reliability Modeling with Change-Point

2018 ◽  
Vol 25 (02) ◽  
pp. 1850009 ◽  
Author(s):  
Shinji Inoue ◽  
Shigeru Yamada
Keyword(s):  
Software Reliability ◽  
Change Point ◽  
Reliability Assessment ◽  
Testing Time ◽  
Reliability Growth ◽  
Reliability Modeling ◽  
Imperfect Debugging ◽  
Modeling Approach ◽  
Semi Markov Process ◽  
Software Reliability Growth

We discuss a Markovian modeling approach for software reliability assessment with the effects of change-point and imperfect debugging environment. Testing-time when the characteristic of the software failure-occurrence or fault-detection phenomenon changes notably is called change-point. Taking into account the effect at change-point in software reliability growth modeling is important to improve the accuracy of software reliability assessment. Our modeling approach describes a software reliability growth process with not only the effect of change-point but also the imperfect debugging activities based on a semi-Markov process for reflecting actual situation of debugging activities. Finally, we show numerical examples of our model for software reliability analysis and check the performance of our model with an existing Markovian software reliability growth model by using actual data.

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