Pub Date : 2018-10-01DOI: 10.4018/IJOSSP.2018100101
Amitpal Singh Sohal, S. Gupta, Hardeep Singh
This study presents the significance of trust for the formation of an Open Source Software Development (OSSD) community. OSSD has various challenges that must be overcome for its successful operation. First is the development of a community, which requires a healthy community formation environment. Taking into consideration various factors for community formation, a strong sense of TRUST among its members has been felt. Trust development is a slow process with various methods for building and maintaining it. OSSD is teamwork but the team is of unknowns and volunteers. Trust forms a pillar for effective cooperation, which leads to a reduction in conflicts and risks, associated with quality software development. This study offers an overview of various existing trust models, which aids in the development of a trust evaluation framework for OSSD communities. Towards the end of the study, various components of the trust evaluation along with an empirical framework for the same have been proposed.
{"title":"Trust in Open Source Software Development Communities: A Comprehensive Analysis","authors":"Amitpal Singh Sohal, S. Gupta, Hardeep Singh","doi":"10.4018/IJOSSP.2018100101","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018100101","url":null,"abstract":"This study presents the significance of trust for the formation of an Open Source Software Development (OSSD) community. OSSD has various challenges that must be overcome for its successful operation. First is the development of a community, which requires a healthy community formation environment. Taking into consideration various factors for community formation, a strong sense of TRUST among its members has been felt. Trust development is a slow process with various methods for building and maintaining it. OSSD is teamwork but the team is of unknowns and volunteers. Trust forms a pillar for effective cooperation, which leads to a reduction in conflicts and risks, associated with quality software development. This study offers an overview of various existing trust models, which aids in the development of a trust evaluation framework for OSSD communities. Towards the end of the study, various components of the trust evaluation along with an empirical framework for the same have been proposed.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"25 1","pages":"1-19"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90022270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.4018/IJOSSP.2018100102
Madhu Kumari, Meera Sharma, V. B. Singh
An accurate bug severity assessment is an important factor in bug fixing. Bugs are reported on the bug tracking system by different users with a fast speed. The size of software repositories is also increasing at an enormous rate. This increased size often has much uncertainty and irregularities. The factors that cause uncertainty are biases, noise and abnormality in data. The authors consider that software bug report phenomena on the bug tracking system keeps an irregular state. Without proper handling of these uncertainties and irregularities, the performance of learning strategies can be significantly reduced. To incorporate and consider these two phenomena, they have used entropy as an attribute to assess bug severity. The authors have predicted the bug severity by using machine learning techniques, namely KNN, J48, RF, RNG, NB, CNN and MLR. They have validated the classifiers using PITS, Eclipse and Mozilla projects. The results show that the proposed entropy-based approaches improves the performance as compared to the state of the art approach considered in this article.
{"title":"Severity Assessment of a Reported Bug by Considering its Uncertainty and Irregular State","authors":"Madhu Kumari, Meera Sharma, V. B. Singh","doi":"10.4018/IJOSSP.2018100102","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018100102","url":null,"abstract":"An accurate bug severity assessment is an important factor in bug fixing. Bugs are reported on the bug tracking system by different users with a fast speed. The size of software repositories is also increasing at an enormous rate. This increased size often has much uncertainty and irregularities. The factors that cause uncertainty are biases, noise and abnormality in data. The authors consider that software bug report phenomena on the bug tracking system keeps an irregular state. Without proper handling of these uncertainties and irregularities, the performance of learning strategies can be significantly reduced. To incorporate and consider these two phenomena, they have used entropy as an attribute to assess bug severity. The authors have predicted the bug severity by using machine learning techniques, namely KNN, J48, RF, RNG, NB, CNN and MLR. They have validated the classifiers using PITS, Eclipse and Mozilla projects. The results show that the proposed entropy-based approaches improves the performance as compared to the state of the art approach considered in this article.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"57 1","pages":"20-46"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82325806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-10-01DOI: 10.4018/IJOSSP.2018100104
Parita Jain, Arun Sharma, Laxmi Ahuja
Agile methodologies have gained wide acceptance for developing high-quality products with a quick and flexible approach. However, until now, the quality of the agile process has not been validated quantitatively. Quality being important for the software system, there is a need for measurement. Estimating different quality factors will lead to a quality product. Also, agile software development does not provide any precise models to evaluate maintainability. Therefore, there is a need for an algorithmic approach that can serve as the basis for estimation of maintainability. The article proposes an adaptive neuro-fuzzy inference system (ANFIS) model for estimating agile maintainability. Maintainability is one of the prominent quality factors in the case of agile development. The proposed model has been verified and found to be effective for assessing the maintainability of agile software.
{"title":"Software Maintainability Estimation in Agile Software Development","authors":"Parita Jain, Arun Sharma, Laxmi Ahuja","doi":"10.4018/IJOSSP.2018100104","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018100104","url":null,"abstract":"Agile methodologies have gained wide acceptance for developing high-quality products with a quick and flexible approach. However, until now, the quality of the agile process has not been validated quantitatively. Quality being important for the software system, there is a need for measurement. Estimating different quality factors will lead to a quality product. Also, agile software development does not provide any precise models to evaluate maintainability. Therefore, there is a need for an algorithmic approach that can serve as the basis for estimation of maintainability. The article proposes an adaptive neuro-fuzzy inference system (ANFIS) model for estimating agile maintainability. Maintainability is one of the prominent quality factors in the case of agile development. The proposed model has been verified and found to be effective for assessing the maintainability of agile software.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"17 1","pages":"65-78"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78193011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/IJOSSP.2018070103
Pushpa Singh, Narendra Singh
Free and open source software (FOSS) differs from proprietary software. FOSS facilitates the design of various applications per the user's requirement. Web applications are not exceptional in this way. Web-based applications are mostly based on client server architecture. This article is an analytical study of FOSS products used in web-based client server architecture. This article will provide information about FOSS product such as FireFox (web browser), Apache (web server) and MySQL (RDBMS). These reveal that various FOSS products such as Apache server covers 65% of the market share, while MySQL covers 58.7% market share and hold the top-most rank.
{"title":"Analysis of Free and Open Source Software (FOSS) Product in Web Based Client-Server Architecture","authors":"Pushpa Singh, Narendra Singh","doi":"10.4018/IJOSSP.2018070103","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018070103","url":null,"abstract":"Free and open source software (FOSS) differs from proprietary software. FOSS facilitates the design of various applications per the user's requirement. Web applications are not exceptional in this way. Web-based applications are mostly based on client server architecture. This article is an analytical study of FOSS products used in web-based client server architecture. This article will provide information about FOSS product such as FireFox (web browser), Apache (web server) and MySQL (RDBMS). These reveal that various FOSS products such as Apache server covers 65% of the market share, while MySQL covers 58.7% market share and hold the top-most rank.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"363 1","pages":"36-47"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76553491","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/IJOSSP.2018070104
K. Srinivasa, Srinidhi Hiriyannaiah, G. Siddesh
Mobile applications are popularly known as apps. Energy and battery-life are critical factors that enable the development and sustainability of apps on mobile devices. Application software developers need to consider the minimization of energy consumption along with the development and deployment of applications. Intelligent software engineering practices and tools are needed in order to assist developers in energy management of Android application development. This article proposes a rule-engine driven framework for estimating the energy consumption of an Android application by using program analysis of the source code. The basis of this framework is to provide the developer with a notion of which part of the application source code consumes considerable energy, and what alternatives could be used to replace it without changing its core functionality. It presents metrics at the overall, event and source code level, allowing application developers to optimize their applications early in the software development cycle.
{"title":"Minimization of Energy in Smart Phone Application Development Using Code Analysis","authors":"K. Srinivasa, Srinidhi Hiriyannaiah, G. Siddesh","doi":"10.4018/IJOSSP.2018070104","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018070104","url":null,"abstract":"Mobile applications are popularly known as apps. Energy and battery-life are critical factors that enable the development and sustainability of apps on mobile devices. Application software developers need to consider the minimization of energy consumption along with the development and deployment of applications. Intelligent software engineering practices and tools are needed in order to assist developers in energy management of Android application development. This article proposes a rule-engine driven framework for estimating the energy consumption of an Android application by using program analysis of the source code. The basis of this framework is to provide the developer with a notion of which part of the application source code consumes considerable energy, and what alternatives could be used to replace it without changing its core functionality. It presents metrics at the overall, event and source code level, allowing application developers to optimize their applications early in the software development cycle.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"162 5","pages":"48-60"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72572668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/IJOSSP.2018070102
Rajvir Singh, Anita Singhrova, R. Bhatia
Detection of fault proneness classes helps software testers to generate effective class level test cases. In this article, a novel technique is presented for an optimized test case generation for ant-1.7 open source software. Class level object oriented (OO) metrics are considered as effective means to find fault proneness classes. The open source software ant-1.7 is considered for the evaluation of proposed techniques as a case study. The proposed mathematical model is the first of its kind generated using Weka open source software to select effective OO metrics. Effective and ineffective OO metrics are identified using feature selection techniques for generating test cases to cover fault proneness classes. In this methodology, only effective metrics are considered for assigning weights to test paths. The results indicate that the proposed methodology is effective and efficient as the average fault exposition potential of generated test cases is 90.16% and test cases execution time saving is 45.11%.
{"title":"Optimized Test Case Generation for Object Oriented Systems Using Weka Open Source Software","authors":"Rajvir Singh, Anita Singhrova, R. Bhatia","doi":"10.4018/IJOSSP.2018070102","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018070102","url":null,"abstract":"Detection of fault proneness classes helps software testers to generate effective class level test cases. In this article, a novel technique is presented for an optimized test case generation for ant-1.7 open source software. Class level object oriented (OO) metrics are considered as effective means to find fault proneness classes. The open source software ant-1.7 is considered for the evaluation of proposed techniques as a case study. The proposed mathematical model is the first of its kind generated using Weka open source software to select effective OO metrics. Effective and ineffective OO metrics are identified using feature selection techniques for generating test cases to cover fault proneness classes. In this methodology, only effective metrics are considered for assigning weights to test paths. The results indicate that the proposed methodology is effective and efficient as the average fault exposition potential of generated test cases is 90.16% and test cases execution time saving is 45.11%.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"73 1","pages":"15-35"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76221911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-07-01DOI: 10.4018/IJOSSP.2018070101
Pushpa Singh, R. Agrawal
This article focuses on the prospects of open source software and tools for maximizing the user expectations in heterogeneous networks. The open source software Python is used as a software tool in this research work for implementing machine learning technique for the categorization of the types of user in a heterogeneous network (HN). The KNN classifier available in Python defines the type of user category in real time to predict the available users in a particular category for maximizing profit for a business organization.
{"title":"Prospects of Open Source Software for Maximizing the User Expectations in Heterogeneous Network","authors":"Pushpa Singh, R. Agrawal","doi":"10.4018/IJOSSP.2018070101","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018070101","url":null,"abstract":"This article focuses on the prospects of open source software and tools for maximizing the user expectations in heterogeneous networks. The open source software Python is used as a software tool in this research work for implementing machine learning technique for the categorization of the types of user in a heterogeneous network (HN). The KNN classifier available in Python defines the type of user category in real time to predict the available users in a particular category for maximizing profit for a business organization.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"24 1","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73026182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-01DOI: 10.4018/IJOSSP.2018040104
Pratiksha Gautam, H. Saini
{"title":"Correlation and Performance Estimation of Clone Detection Tools","authors":"Pratiksha Gautam, H. Saini","doi":"10.4018/IJOSSP.2018040104","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018040104","url":null,"abstract":"","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"1 1","pages":"55-71"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79864524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-01DOI: 10.4018/IJOSSP.2018040102
Noureddine Aribi, Yahia Lebbah
Free and open source software (FOSS) distributions are increasingly based on the abstraction of packages to manage and accommodate new features before and after the deployment stage. However, due to inter-package dependencies, package upgrade entails challenging shortcomings of deployment and management of complex software systems, inhibiting their ability to cope with frequent upgrade failures. Moreover, the upgrade process may be achieved according to some criteria (maximize the stability, minimize outdated packages, etc.). This problem is actually a multi-objective optimization problem. Throughout the article, the authors propose a Leximax approach based on mixed integer linear programming (MILP) to tackle the upgradability problem, while ensuring efficiency and fairness requirements between the objective functions. Experiments performed on real-world instances, from the MANCOOSI project, show that the authors' approach efficiently finds solutions of consistently high quality.
{"title":"On Solving the Multi-Objective Software Package Upgradability Problem","authors":"Noureddine Aribi, Yahia Lebbah","doi":"10.4018/IJOSSP.2018040102","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018040102","url":null,"abstract":"Free and open source software (FOSS) distributions are increasingly based on the abstraction of packages to manage and accommodate new features before and after the deployment stage. However, due to inter-package dependencies, package upgrade entails challenging shortcomings of deployment and management of complex software systems, inhibiting their ability to cope with frequent upgrade failures. Moreover, the upgrade process may be achieved according to some criteria (maximize the stability, minimize outdated packages, etc.). This problem is actually a multi-objective optimization problem. Throughout the article, the authors propose a Leximax approach based on mixed integer linear programming (MILP) to tackle the upgradability problem, while ensuring efficiency and fairness requirements between the objective functions. Experiments performed on real-world instances, from the MANCOOSI project, show that the authors' approach efficiently finds solutions of consistently high quality.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"20 1","pages":"18-38"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89018731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-04-01DOI: 10.4018/IJOSSP.2018040101
Shozab Khurshid, A. Shrivastava, Javaid Iqbal
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.
{"title":"Fault Prediction Modelling in Open Source Software Under Imperfect Debugging and Change-Point","authors":"Shozab Khurshid, A. Shrivastava, Javaid Iqbal","doi":"10.4018/IJOSSP.2018040101","DOIUrl":"https://doi.org/10.4018/IJOSSP.2018040101","url":null,"abstract":"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.","PeriodicalId":53605,"journal":{"name":"International Journal of Open Source Software and Processes","volume":"44 1","pages":"1-17"},"PeriodicalIF":0.0,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91199772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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