scholarly journals Duration Estimation Models for Open Source Software Projects

2021 ◽  
Vol 13 (1) ◽  
pp. 1-17
Author(s):  
Donatien Koulla Moulla ◽  
◽  
Alain Abran ◽  
Kolyang
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Total Duration ◽  
Full Time ◽  
Effort Estimation ◽  
Estimation Model ◽  
Data Repositories ◽  
Independent Variable ◽  
Duration Estimation ◽  
Estimation Models

For software organizations that rely on Open Source Software (OSS) to develop customer solutions and products, it is essential to accurately estimate how long it will take to deliver the expected functionalities. While OSS is supported by government policies around the world, most of the research on software project estimation has focused on conventional projects with commercial licenses. OSS effort estimation is challenging since OSS participants do not record effort data in OSS repositories. However, OSS data repositories contain dates of the participants’ contributions and these can be used for duration estimation. This study analyses historical data on WordPress and Swift projects to estimate OSS project duration using either commits or lines of code (LOC) as the independent variable. This study proposes first an improved classification of contributors based on the number of active days for each contributor in the development period of a release. For the WordPress and Swift OSS projects environments the results indicate that duration estimation models using the number of commits as the independent variable perform better than those using LOC. The estimation model for full-time contributors gives an estimate of the total duration, while the models with part-time and occasional contributors lead to better estimates of projects duration with both for the commits data and the lines of data.

scholarly journals MINING EFFORT DATA FROM THE OSS REPOSITORY OF DEVELOPER’S BUG FIX ACTIVITY

2016 ◽  
Vol 3 (1) ◽  
pp. 107-128
Author(s):  
Syed Nadeem Ahsan ◽  
Muhammad Tanvir Afzal ◽  
Safdar Zaman ◽  
Christian Gütel ◽  
Franz Wotawa
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
State Of The Art ◽  
Tracking System ◽  
Previous History ◽  
Effort Estimation ◽  
Estimation Model ◽  
Activity Data ◽  
Actual Time ◽  
History Of

During the evolution of any software, efforts are made to fix bugs or to add new features in software. In software engineering, previous history of effort data is required to build an effort estimation model, which estimates the cost and complexity of any software. Therefore, the role of effort data is indispensable to build state-of-the-art effort estimation models. Most of the Open Source Software does not maintain any effort related information. Consequently there is no state-of-the-art effort estimation model for Open Source Software, whereas most of the existing effort models are for commercial software. In this paper we present an approach to build an effort estimation model for Open Source Software. For this purpose we suggest to mine effort data from the history of the developer’s bug fix activities. Our approach determines the actual time spend to fix a bug, and considers it as an estimated effort. Initially, we use the developer’s bug-fix-activity data to construct the developer’s activity log-book. The log-book is used to store the actual time elapsed to fix a bug. Subsequently, the log-book information is used to mine the bug fix effort data. Furthermore, the developer’s bug fix activity data is used to define three different measures for the developer’s contribution or expertise level. Finally, we used the bug-fix-activity data to visualize the developer’s collaborations and the involved source files. In order to perform an experiment we selected the Mozilla open source project and downloaded 93,607 bug reports from the Mozilla project bug tracking system i.e., Bugzilla. We also downloaded the available CVS-log data from the Mozilla project repository. In this study we reveal that in case of Mozilla only 4.9% developers have been involved in fixing 71.5% of the reported bugs.

scholarly journals The Economics of Community Open Source Software Projects: An Empirical Analysis of Maintenance Effort

2010 ◽  
Vol 2010 ◽  
pp. 1-17 ◽  
Author(s):  
Eugenio Capra ◽  
Chiara Francalanci ◽  
Francesco Merlo
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Effort Estimation ◽  
Estimation Model ◽  
Software Projects ◽  
Increasing Trend ◽  
Entropy Effect ◽  
Degradation Effect ◽  
Over Time

Previous contributions in the empirical software engineering literature have consistently observed a quality degradation effect of proprietary code as a consequence of maintenance. This degradation effect, referred to as entropy effect, has been recognized to be responsible for significant increases in maintenance effort. In the Open Source context, the quality of code is a fundamental design principle. As a consequence, the maintenance effort of Open Source applications may not show a similar increasing trend over time. The goal of this paper is to empirically verify the entropy effect for a sample of 4,289 community Open Source application versions. Analyses are based on the comparison with an estimate of effort obtained with a traditional effort estimation model. Findings indicate that community Open Source applications show a slower growth of maintenance effort over time, and, therefore, are less subject to the entropy effect.

The Effects of Communication Patterns on the Success of Open Source Software Projects

2016 ◽  
Vol 24 (4) ◽  
pp. 22-44 ◽  
Author(s):  
Jing Wu ◽  
Khim-Yong Goh ◽  
He Li ◽  
Chuan Luo ◽  
Haichao Zheng
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Fixed Effects ◽  
Communication Patterns ◽  
Estimation Model ◽  
Software Projects ◽  
Team Members ◽  
Analysis Methodology ◽  
Model Following ◽  
Time Period

Drawing on the theoretical lens of communication patterns in organizational theory, this research analyzed the longitudinal success of open source software (OSS) projects by employing social network analysis method, based on extensive analyses of empirical data. This study is expected to provide an understanding on how communication patterns established in different roles and different levels. The authors not only measured OSS success from both developers and users' perspectives, but also extended the existing research by including the potential relationships among these success measures in the estimation model. Following the panel data econometric analysis methodology, they evaluated their research hypotheses using the Three-Stage Least Squares model, accounting for both time-period and project fixed effects. The authors' results indicated that according to the objectives of projects, a proper and planned control for the communication among team members is crucial for the success of OSS projects.

scholarly journals Tools4MSP: an open source software package to support Maritime Spatial Planning

2018 ◽  
Vol 4 ◽  
pp. e165 ◽  
Author(s):  
Stefano Menegon ◽  
Alessandro Sarretta ◽  
Daniel Depellegrin ◽  
Giulio Farella ◽  
Chiara Venier ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Spatial Planning ◽  
Software Package ◽  
Integrated System ◽  
Third Party ◽  
Data Repositories ◽  
Open Source Software Package ◽  
Geospatial Datasets ◽  
Maritime Spatial Planning

This paper presents the Tools4MSP software package, a Python-based Free and Open Source Software (FOSS) for geospatial analysis in support of Maritime Spatial Planning (MSP) and marine environmental management. The suite was initially developed within the ADRIPLAN data portal, that has been recently upgraded into the Tools4MSP Geoplatform (data.tools4msp.eu), an integrated web platform that supports MSP through the application of different tools, e.g., collaborative geospatial modelling of cumulative effects assessment (CEA) and marine use conflict (MUC) analysis. The package can be used as stand-alone library or as collaborative webtool, providing user-friendly interfaces appropriate to decision-makers, regional authorities, academics and MSP stakeholders. An effective MSP-oriented integrated system of web-based software, users and services is proposed. It includes four components: the Tools4MSP Geoplatform for interoperable and collaborative sharing of geospatial datasets and for MSP-oriented analysis, the Tools4MSP package as stand-alone library for advanced geospatial and statistical analysis, the desktop applications to simplify data curation and the third party data repositories for multidisciplinary and multilevel geospatial datasets integration. The paper presents an application example of the Tools4MSP GeoNode plugin and an example of Tools4MSP stand-alone library for CEA in the Adriatic Sea. The Tools4MSP and the developed software have been released as FOSS under the GPL 3 license and are currently under further development.

scholarly journals OPEN FORIS AND GOOGLE EARTH ENGINE LINKING EXPERT PARTICIPATION WITH NATURAL RESOURCE MAPPING AND REMOTE SENSING TRAINING IN TANZANIA

2018 ◽  
Vol XLII-4/W8 ◽  
pp. 117-122 ◽  
Author(s):  
U. Leinonen ◽  
J. Koskinen ◽  
H. Makandi ◽  
E. Mauya ◽  
N. Käyhkö
Keyword(s):  
Remote Sensing ◽  
Open Source ◽  
Open Source Software ◽  
Google Earth ◽  
Earth Observation ◽  
Teaching Staff ◽  
Participatory Mapping ◽  
Observation Data ◽  
Data Repositories ◽  
Google Earth Engine

<p><strong>Abstract.</strong> There is an increasing amount of open Earth observation (EO) data available, offering solutions to map, assess and monitor natural resources and to obtain answers to global and local societal challenges. With the help of free and open source software (FOSS) and open access cloud computing resources, the remote sensing community can take the full advantage of these vast geospatial data repositories. To empower developing societies, support should be given to higher education institutions (HEIs) to train professionals in using the open data, software and tools. In this paper, we describe a participatory mapping methodology, which utilizes open source software Open Foris and QGIS, various open Earth observation data catalogues, and computing capacity of the free Google Earth Engine cloud platform. Using this methodology, we arranged a collaborative data collection event, Mapathon, in Tanzania, followed by a training of the related FOSS tools for HEIs’ teaching staff. We collected feedback from the Mapathon participants about their learning experiences and from teachers about the usability of the methodology in remote sensing training in Tanzania. Based on our experiences and the received feedback, using a participatory mapping campaign as a training method can offer effective learning about environmental remote sensing through a real-world example, as well as networking and knowledge sharing possibilities for the participating group.</p>

scholarly journals Reproducible Software Environment: a tool enabling computational reproducibility in geospace sciences and facilitating collaboration

2020 ◽  
Vol 10 ◽  
pp. 12
Author(s):  
Asti Bhatt ◽  
Todd Valentic ◽  
Ashton Reimer ◽  
Leslie Lamarche ◽  
Pablo Reyes ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Tool ◽  
Software Tools ◽  
Reproducible Research ◽  
Multiple Sources ◽  
Community Members ◽  
Software Environment ◽  
Data Repositories ◽  
Scientific Results

The Reproducible Software Environment (Resen) is an open-source software tool enabling computationally reproducible scientific results in the geospace science community. Resen was developed as part of a larger project called the Integrated Geoscience Observatory (InGeO), which aims to help geospace researchers bring together diverse datasets from disparate instruments and data repositories, with software tools contributed by instrument providers and community members. The main goals of InGeO are to remove barriers in accessing, processing, and visualizing geospatially resolved data from multiple sources using methodologies and tools that are reproducible. The architecture of Resen combines two mainstream open source software tools, Docker and JupyterHub, to produce a software environment that not only facilitates computationally reproducible research results, but also facilitates effective collaboration among researchers. In this technical paper, we discuss some challenges for performing reproducible science and a potential solution via Resen, which is demonstrated using a case study of a geospace event. Finally we discuss how the usage of mainstream, open-source technologies seems to provide a sustainable path towards enabling reproducible science compared to proprietary and closed-source software.

Sign in / Sign up

Export Citation Format

Share Document