FLOSSMetrics: Free/Libre/Open Source Software Metrics

2009 ◽  
Author(s):  
Israel Herraiz ◽  
Daniel Izquierdo-Cortazar ◽  
Francisco Rivas-Hernández
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Metrics

scholarly journals First analysis of software metrics

2015 ◽  
Author(s):  
Martin Fenner
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Metrics ◽  
Software Repositories ◽  
First Results

Last week I wrote about software.lagotto.io, an instance of the lagotto open source software collecting metrics for the about 1,400 software repositories included in Sciencetoolbox. In this post I want to report the first results analyzing the data.Number of software repositories (out of 1,404) ...

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.

scholarly journals Statistical Analysis on Software Metrics Affecting Modularity in Open Source Software

2011 ◽  
Vol 3 (3) ◽  
pp. 105-118
Author(s):  
Andi Wahju Rahardjo Emanuel ◽  
Retantyo Wardoyo ◽  
Jazi Eko Istiyanto ◽  
Khabib Mustofa
Keyword(s):  
Statistical Analysis ◽  
Open Source ◽  
Open Source Software ◽  
Software Metrics

scholarly journals Impact of Historical Software Metric Changes in Predicting Future Maintainability Trends in Open-Source Software Development

2020 ◽  
Vol 10 (13) ◽  
pp. 4624
Author(s):  
Mitja Gradišnik ◽  
Tina Beranič ◽  
Sašo Karakatič
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Maintenance ◽  
Software Metrics ◽  
Prediction Models ◽  
Measurement Data ◽  
Software Project ◽  
Software Projects ◽  
Software Metric ◽  
Software Maintainability

Software maintenance is one of the key stages in the software lifecycle and it includes a variety of activities that consume the significant portion of the costs of a software project. Previous research suggest that future software maintainability can be predicted, based on various source code aspects, but most of the research focuses on the prediction based on the present state of the code and ignores its history. While taking the history into account in software maintainability prediction seems intuitive, the research empirically testing this has not been done, and is the main goal of this paper. This paper empirically evaluates the contribution of historical measurements of the Chidamber & Kemerer (C&K) software metrics to software maintainability prediction models. The main contribution of the paper is the building of the prediction models with classification and regression trees and random forest learners in iterations by adding historical measurement data extracted from previous releases gradually. The maintainability prediction models were built based on software metric measurements obtained from real-world open-source software projects. The analysis of the results show that an additional amount of historical metric measurements contributes to the maintainability prediction. Additionally, the study evaluates the contribution of individual C&K software metrics on the performance of maintainability prediction models.

scholarly journals Data Mining Techniques for Software Quality Prediction in Open Source Software

2019 ◽  
Vol 214 ◽  
pp. 05007
Author(s):  
Marco Canaparo ◽  
Elisabetta Ronchieri
Keyword(s):  
Data Mining ◽  
Software Engineering ◽  
Open Source ◽  
Software Quality ◽  
Open Source Software ◽  
Software Metrics ◽  
Prediction Models ◽  
Quality Prediction ◽  
Data Mining Techniques ◽  
Software Quality Prediction

Software quality monitoring and analysis are among the most productive topics in software engineering research. Their results may be effectively employed by engineers during software development life cycle. Open source software constitutes a valid test case for the assessment of software characteristics. The data mining approach has been proposed in literature to extract software characteristics from software engineering data. This paper aims at comparing diverse data mining techniques (e.g., derived from machine learning) for developing effective software quality prediction models. To achieve this goal, we tackled various issues, such as the collection of software metrics from open source repositories, the assessment of prediction models to detect software issues and the adoption of statistical methods to evaluate data mining techniques. The results of this study aspire to identify the data mining techniques that perform better amongst all the ones used in this paper for software quality prediction models.

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