Entropy-Based Two-Dimensional Software Reliability Growth Modeling for Open-Source Software Incorporating Change-Point

2020 ◽  
Vol 27 (05) ◽  
pp. 2040009
Author(s):  
P. K. Kapur ◽  
Saurabh Panwar ◽  
Vivek Kumar ◽  
Ompal Singh
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Reliability ◽  
Source Code ◽  
Entropy Measure ◽  
Two Dimensional ◽  
Field Environment ◽  
Proposed Model ◽  
Software Reliability Growth ◽  
Code Complexity

This study provides an analytical model to predict the fixing pattern of issues in the open-source software (OSS) packages to assist developers in software development and maintenance. Moreover, the continuous evolution of software due to bugs removal, new features addition or existing features modification results in the source code complexity. The proposed model quantifies the complexity in the source code using the Shannon entropy measure. In addition, the issues fixing growth behavior is viewed as a function of continuation time of the software in the field environment and amount of uncertainty or complexity present in the source code. Therefore, a two-dimensional function called Cobb–Douglas production function is applied to model the intensity function of the issues fixing rate. Furthermore, the rate of fixing the different issue types is considered variable that may alter after certain time points. Thus, this study incorporates the concept of multiple change-points to predict and assess the fixing behavior of issues in the software system. The performance of the proposed model is validated by fitting the proposed model to the actual issues data of three open-source projects. Findings of the data analysis exhibit excellent prediction and estimation capability of the model.

An SRGM for Multi-Release Open Source Software System

2018 ◽  
Vol 15 (02) ◽  
pp. 1850011 ◽  
Author(s):  
Nidhi Nijhawan ◽  
Anu G. Aggarwal ◽  
Vikas Dhaka
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Reliability ◽  
Goodness Of Fit ◽  
Reliability Growth ◽  
Modeling Framework ◽  
Release Policy ◽  
Proposed Model ◽  
Software Reliability Growth ◽  
Optimal Release Policy

A number of software reliability growth models have been reported in the literature for open source software (OSS) systems but the effect of up-gradations on the reliability growth of multi-releases of such software systems has been discussed by a few. In this paper, the discrete modeling framework has been proposed to study the reliability growth process of OSS systems with multiple releases. The proposed model is based upon the assumption that during up-gradation some new faults are introduced in the code in addition to the left over fault content of the previous version. To validate our model, we have chosen two successful open source projects-Mozilla and Apache for its multi release failure datasets. Graphs representing goodness of fit of the proposed model have been drawn. The parameter estimates and measures of goodness of fit criteria suggest that the proposed software reliability growth model for multi-release OSS fits the actual datasets very well. An optimal release policy has been formulated by taking into account the cost of fault removal during testing and operational phases and reliability targets pre-specified by the decision makers. In addition, numerical example along with the sensitivity analysis has been provided to illustrate optimal release policy.

Open Source Software Reliability Model with the Decreasing Trend of Fault Detection Rate

2018 ◽  
Vol 62 (9) ◽  
pp. 1301-1312
Author(s):  
Jinyong Wang ◽  
Xiaoping Mi
Keyword(s):  
Fault Detection ◽  
Open Source ◽  
Open Source Software ◽  
Software Reliability ◽  
Real World ◽  
Detection Rate ◽  
Failure Process ◽  
Model Performance ◽  
Predictive Performance ◽  
Proposed Model

Abstract Software reliability assessment methods have been changed from closed to open source software (OSS). Although numerous new approaches for improving OSS reliability are formulated, they are not used in practice due to their inaccuracy. A new proposed model considering the decreasing trend of fault detection rate is developed in this study to effectively improve OSS reliability. We analyse the changes of the instantaneous fault detection rate over time by using real-world software fault count data from two actual OSS projects, namely, Apache and GNOME, to validate the proposed model performance. Results show that the proposed model with the decreasing trend of fault detection rate has better fitting and predictive performance than the traditional closed source software and other OSS reliability models. The proposed model for OSS can further accurately fit and predict the failure process and thus can assist in improving the quality of OSS systems in real-world OSS projects.

scholarly journals Applying Information Measure for Predicting Release Time of Open Source Software

2017 ◽  
Vol 15 (1) ◽  
pp. 29-39
Author(s):  
Talat PARVEEN ◽  
Hari Darshan ARORA
Keyword(s):  
Regression Model ◽  
Open Source ◽  
Open Source Software ◽  
Goodness Of Fit ◽  
Source Code ◽  
Release Time ◽  
Entropy Measure ◽  
Frequent Change ◽  
Code Change ◽  
Code Changes

Open Source Software (OSS) is updated regularly to meet the requirements posed by the customers. The source code of OSS undergoes frequent change to diffuse new features and update existing features in the system, providing a user friendly interface. The source code changes for fixing bugs and meeting user end requirements again affects the complexity of the code change and creates bugs in the software which are accountable to the next release of software. In this paper, the complexity of code changes in various Bugzilla open source software releases, from version 2.0 on 19th Sep, 1998, to 5.0.1 on 10th Sep, 2015, bugs in each software version release, and the time of release of each software version are considered, and the data used to predict the next release time. The Shannon entropy measure is used to quantify the code change process in terms of entropy for each software release. Observed code changes are utilized to quantify them into entropy units and are further used to predict the next release time. A neural network-based regression model is used to predict the next release time. The performance is compared with the R measure calculated using the multi linear regression model, and a goodness of fit curve is produced.

A COMPONENT-ORIENTED RELIABILITY ASSESSMENT METHOD FOR OPEN SOURCE SOFTWARE

2008 ◽  
Vol 15 (01) ◽  
pp. 33-53 ◽  
Author(s):  
YOSHINOBU TAMURA ◽  
SHIGERU YAMADA
Keyword(s):  
Neural Network ◽  
Open Source ◽  
Open Source Software ◽  
Software Reliability ◽  
Reliability Assessment ◽  
Growth Modeling ◽  
Reliability Growth ◽  
Entire System ◽  
Development Environment ◽  
Software Reliability Growth

Software development environment has been changing into new development paradigms such as concurrent distributed development environment and the so-called open source project by using network computing technologies. Especially, an OSS (open source software) system which serves as key components of critical infrastructures in the society is still ever-expanding now. In case of considering the effect of the debugging process on an entire system in the development of a method of reliability assessment for the OSS, it is necessary to grasp the deeply-intertwined factors, such as programming path, size of each component, skill of fault reporter, and so on. In order to consider the effect of each software component on the reliability of an entire system, we propose a new approach to user-oriented software reliability assessment by creating a fusion of neural network and software reliability growth modeling. In this paper, we show application examples of component-oriented software reliability assessment based on neural network and software reliability growth modeling for the OSS. Also, we analyze actual software fault count data to show numerical examples of software reliability assessment for the OSS. Moreover, we develop the testing management tool for OSS.

Sign in / Sign up

Export Citation Format

Share Document