Exploratory Analysis of the Relations between Code Cloning and Open Source Software Quality

2010 ◽  
Author(s):  
Denis Kozlov ◽  
Jussi Koskinen ◽  
Markku Sakkinen ◽  
Jouni Markkula
Keyword(s):  
Open Source ◽  
Software Quality ◽  
Open Source Software ◽  
Exploratory Analysis

scholarly journals A systematic literature review of open source software quality assessment models

SpringerPlus ◽  
2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Adewole Adewumi ◽  
Sanjay Misra ◽  
Nicholas Omoregbe ◽  
Broderick Crawford ◽  
Ricardo Soto
Keyword(s):  
Literature Review ◽  
Quality Assessment ◽  
Open Source ◽  
Systematic Literature Review ◽  
Software Quality ◽  
Open Source Software

scholarly journals Similar Characteristics of Internal Software Quality Attributes for Object-Oriented Open-Source Software Projects

2014 ◽  
Author(s):  
Mariana Santos ◽  
Rodrigo Amador ◽  
Paulo Henrique De Souza Bermejo ◽  
Heitor Costa
Keyword(s):  
Cluster Analysis ◽  
Open Source ◽  
Software Quality ◽  
Open Source Software ◽  
Software Metrics ◽  
Object Oriented ◽  
Quality Attributes ◽  
Internal Quality ◽  
Software Systems ◽  
Systems Quality

Organizations are becoming increasingly concerned about software quality. In object-oriented (OO) systems, quality is characterized by measurements of internal quality attributes. An efficient and proper method to analyze software quality in the absence of fault-prone or defective data labels is cluster analysis. The aim of this paper is to find similarities among project structures by measuring characteristics of internal software quality. In a sample of 150 open-source software systems, we evaluated software using macro and micro categories. Results obtained using cluster analysis indicated that some domains such as Graphics, Games, and Development tend to have similarities in specialization, abstraction, stability, and complexity. These results exploit the ability of OO software metrics to find similar behavior across domains. The results provide an immediate view of the trends and characteristics of internal software quality of Java systems that need to be addressed so that software systems can continue to be maintainable.

An Exploratory Analysis and Classification of Papers Presented in a Decade of OSS Conferences Using Revised Taxonomy

2018 ◽  
pp. 1-57
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Exploratory Analysis ◽  
Ongoing Study ◽  
Interesting Observation ◽  
New Ideas ◽  
Open Source Systems

On the occasion of completion of ten years of Open Source Systems (OSS) conferences, this paper studies its contribution to the extension of Free and Open Source Software (FOSS) research. An existing taxonomy was used to initially classify the 347 full and short papers presented in the conferences. Because there were many new categories, which did not fit, in existing system, the taxonomy was revised and the reclassified papers are presented in this paper. The analysis of locations, themes, participants and citations of successive conferences results in interesting observation. The major takeaway of this ongoing study is to demonstrate that the goal of OSS conferences, as mentioned in the first edition, “to promote the exchange of new ideas, research and applications in the emerging field of Open Source Software,” is more than successful.

scholarly journals A Quantitative Study for the Characterization of Internal Quality of Open-Source Object-Oriented Software

2016 ◽  
Author(s):  
Mariana De Azevedo Santos ◽  
Paulo Henrique De Souza Bermejo ◽  
Heitor Costa
Keyword(s):  
Open Source ◽  
Software Quality ◽  
Open Source Software ◽  
Object Oriented ◽  
Internal Quality ◽  
Development Lifecycle ◽  
Study Results ◽  
Software Development Lifecycle ◽  
Software Quality Models

Although it is necessary, activities regarding quality assurance and maintenance of software are considered the longest and most complex in software development lifecycle. Taking advantage of this growing trend and of the benefits obtained from open-source initiative, researches on open-source software quality and maintainability have gained renewed interest. The use of robust statistical techniques, such as PLS-SEM to investigate and empirically validate software quality models has also been an efficient alternative to obtain information on open-source software quality. The aim of this study was evaluate and build a conceptual model to characterize the internal quality in Java open-source software in different domains, validated with the PLS-SEM technique. The study results indicate that there are domains with similarities among them and four factors can influence the internal quality of object-oriented software to present better maintainability (Complexity Reduce, Normalized Cohesion, Non-normalized Cohesion, and Increase of the Modularity Level). Besides, we identified some measures are more effective to evaluate internal quality in object-oriented open-source, such as, Fan-out (FOUT), Lack of Cohesion of Methods 2 (LCOM2), Response for Class (RFC), Tight Class Cohesion (TCC), and Loose Class Cohesion (LCC). Thus, this study aims at supporting software engineers and project managers to develop measurement strategies to ensure internal quality of source code and reduce maintenance costs.

scholarly journals On Predicting Rediscoveries of Software Defects

2021 ◽  
Author(s):  
Mefta Sadat
Keyword(s):  
Customer Satisfaction ◽  
Open Source ◽  
Predictive Model ◽  
Software Quality ◽  
Open Source Software ◽  
Large Scale ◽  
Software Defects ◽  
Enterprise Software ◽  
Software Projects ◽  
Multiple Clients

The same defect may be rediscovered by multiple clients, causing unplanned outages and leading to reduced customer satisfaction. One solution is forcing clients to install a fix for every defect. However, this approach is economically infeasible, because it requires extra resources and increases downtime. Moreover, it may lead to regression of functionality, as new fixes may break the existing functionality. Our goal is to find a way to proactively predict defects that a client may rediscover in the future. We build a predictive model by leveraging recommender algorithms. We evaluate our approach with extracted rediscovery data from four groups of large-scale open source software projects (namely, Eclipse, Gentoo, KDE, and Libre) and one enterprise software. The datasets contain information about ⇡ 1.33 million unique defect reports over a period of 18 years (1999-2017). Our proposed approach may help in understanding the defect rediscovery phenomenon, leading to improvement of software quality and customer satisfaction.

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