Fault Prediction Modelling in Open Source Software Under Imperfect Debugging and Change-Point

2021 ◽  
pp. 277-293
Author(s):  
Shozab Khurshid ◽  
A. K. Shrivastava ◽  
Javaid Iqbal
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Change Point ◽  
General Framework ◽  
Removal Rate ◽  
Fault Prediction ◽  
Imperfect Debugging ◽  
Fault Removal ◽  
Distance Approach ◽  
Prediction Capability

Instant demand of products and services by technologically active users has increased the demand for open source software (OSS)-based applications. Unfortunately, with the complexity and lack of understanding of OSS-based systems, it becomes difficult for a testing team to remove the faults and the fault removal rate becomes low in comparison to what it should be. This also results in generating new faults during removal. Also, the rate at which the testing team detects/corrects fault need not be same during the entire process of testing due to various reasons viz. change in testing strategy, understanding of code, change in resources, etc. In the existing literature on OSS, authors have developed many models considering the above aspects separately. In this article, all of the above aspects have been combined to develop a general framework for predicting the number of faults in OSS. The comparison of eight models on the basis of their prediction capability on two well-known Open Source Software datasets is created and then ranked using normalized criteria distance approach.

Fault Prediction Modelling in Open Source Software Under Imperfect Debugging and Change-Point

2018 ◽  
Vol 9 (2) ◽  
pp. 1-17
Author(s):  
Shozab Khurshid ◽  
A. K. Shrivastava ◽  
Javaid Iqbal
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Change Point ◽  
Removal Rate ◽  
Fault Prediction ◽  
Testing Strategy ◽  
Imperfect Debugging ◽  
Code Change ◽  
Distance Approach ◽  
Prediction Capability

Instant demand of products and services by technologically active users has increased the demand for open source software (OSS)-based applications. Unfortunately, with the complexity and lack of understanding of OSS-based systems, it becomes difficult for a testing team to remove the faults and the fault removal rate becomes low in comparison to what it should be. This also results in generating new faults during removal. Also, the rate at which the testing team detects/corrects fault need not be same during the entire process of testing due to various reasons viz. change in testing strategy, understanding of code, change in resources, etc. In the existing literature on OSS, authors have developed many models considering the above aspects separately. In this article, all of the above aspects have been combined to develop a general framework for predicting the number of faults in OSS. The comparison of eight models on the basis of their prediction capability on two well-known Open Source Software datasets is created and then ranked using normalized criteria distance approach.

Generalized Multi-Release Framework for Fault Prediction in Open Source Software

2019 ◽  
Vol 7 (4) ◽  
pp. 86-107 ◽  
Author(s):  
Shozab Khurshid ◽  
A.K. Shrivastava ◽  
Javaid Iqbal
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Change Point ◽  
General Framework ◽  
Fault Prediction ◽  
Change Points ◽  
Software Project ◽  
Imperfect Debugging ◽  
Developing Communities ◽  
Quality And Reliability

Software developing communities are shifting to open source software (OSS) because of the reason that software development takes place in successive releases, thereby improving its quality and reliability. Multi-release development of OSS can provide an opportunity to inculcate the dynamic needs of the user in a very short span of time to survive in the market. In spite of having these benefits, numerous challenges can be faced during the multi-release OSS development. Some of the challenges can be the generation of errors during the addition of new features. To address the changing fault detection process, a change point phenomenon is considered so as to give more practicality to the model. In this article, we present a general framework for multi-release OSS modelling incorporating imperfect debugging and change points. Parameter estimation and model validation is done on the three releases of Apache, an open source software project.

Generalized Multi-Release Framework for Fault Prediction in Open Source Software

2021 ◽  
pp. 710-732
Author(s):  
Shozab Khurshid ◽  
A.K. Shrivastava ◽  
Javaid Iqbal
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Change Point ◽  
General Framework ◽  
Fault Prediction ◽  
Software Project ◽  
Imperfect Debugging ◽  
Developing Communities ◽  
Quality And Reliability ◽  
Short Span

Software developing communities are shifting to open source software (OSS) because of the reason that software development takes place in successive releases, thereby improving its quality and reliability. Multi-release development of OSS can provide an opportunity to inculcate the dynamic needs of the user in a very short span of time to survive in the market. In spite of having these benefits, numerous challenges can be faced during the multi-release OSS development. Some of the challenges can be the generation of errors during the addition of new features. To address the changing fault detection process, a change point phenomenon is considered so as to give more practicality to the model. In this article, we present a general framework for multi-release OSS modelling incorporating imperfect debugging and change points. Parameter estimation and model validation is done on the three releases of Apache, an open source software project.

An NHPP SRGM with Change Point and Multiple Releases

2016 ◽  
Vol 8 (4) ◽  
pp. 57-68 ◽  
Author(s):  
Abhishek Tandon ◽  
Anu G. Aggarwal ◽  
Nidhi Nijhawan
Keyword(s):  
Software Reliability ◽  
Change Point ◽  
Goodness Of Fit ◽  
Removal Rate ◽  
Real Life ◽  
Logistic Distribution ◽  
Data Set ◽  
Reliability Modeling ◽  
Software Upgrades ◽  
Fault Removal

In an environment of intense competition, software upgrades have become the necessity for the survival in software industry. In this paper, the authors propose a discrete Software Reliability Growth Model (SRGM) for the software with successive releases by taking into consideration the realistic assumption that Fault Removal Rate (FRR) may not remain constant during the testing process, it changes due to severity of faults detected and due to change in strategies adapted by testing team and the time point where FRR changes is called the Change Point. Many researchers have developed SRGMs incorporating the concept of Change Point for single release software. The proposed model aims to present multi release software reliability modeling with change point. Discrete logistic distribution function has been used to model relationship between features enhancement and fault removal. It is helpul in developing a flexible SRGM, which is S-shaped in nature. In order to evaluate the proposed SRGM, parameter estimation is done using the real life data set for software with four releases and the goodness-of-fit of this model is analyzed.

AN EMBEDDED OSS RELIABILITY AND OPTIMIZATION ANALYSIS INCORPORATING IMPERFECT DEBUGGING

2009 ◽  
Vol 16 (04) ◽  
pp. 371-384
Author(s):  
YOSHINOBU TAMURA ◽  
SHIGERU YAMADA
Keyword(s):  
Software Development ◽  
Open Source ◽  
Open Source Software ◽  
Software Reliability ◽  
Software Maintenance ◽  
Reliability Assessment ◽  
Release Time ◽  
Network Computing ◽  
Imperfect Debugging ◽  
Network Technologies

As a result of the technological progress, software development environment has changed into development paradigm based on client/server systems by using network computing technologies. Network technologies have made rapid progress with the dissemination of computer systems in all areas. These network technologies become increasingly more complex in a wide sphere. Especially, open source software systems which serve as key components of critical infrastructures in the society are still ever-expanding now. In this paper, we propose a method of software reliability assessment based on stochastic differential equations. Especially, we derive several assessment measures in terms of imperfect debugging. Also, we analyze actual software fault-count data to show numerical examples of software reliability assessment for an embedded open source software. Further, it has been necessary to manage the software development process in terms of reliability, effort, and release time. Then, we find the optimal release time based on the total expected software maintenance effort.

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