Effort estimation of open source Android projects via transaction analysis

2020 ◽  
Author(s):  
Kan Qi ◽  
Barry Boehm
Keyword(s):  
Open Source ◽  
Effort Estimation ◽  
Transaction Analysis

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.

Software effort estimation based on open source projects: Case study of Github

2017 ◽  
Vol 92 ◽  
pp. 145-157 ◽  
Author(s):  
Fumin Qi ◽  
Xiao-Yuan Jing ◽  
Xiaoke Zhu ◽  
Xiaoyuan Xie ◽  
Baowen Xu ◽  
...  
Keyword(s):  
Open Source ◽  
Effort Estimation ◽  
Software Effort Estimation

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 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.

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