scholarly journals Improving Software Maintenance with Improved Bug Triaging in Open Source Cloud and non-Cloud Based Bug Tracking Systems

2021 ◽  
Author(s):  
Chetna Gupta ◽  
Pedro R.M. Inácio ◽  
Mário M Freire
Keyword(s):  
Open Source ◽  
Software Maintenance ◽  
Tracking Systems ◽  
Bug Triaging ◽  
Bug Tracking

scholarly journals Mining Severe Priority Bugs in Software Maintenance

2019 ◽  
Vol 8 (4S2) ◽  
pp. 729-732
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Maintenance ◽  
Maintenance Phase ◽  
Bug Reports ◽  
Bug Tracking ◽  
The Right ◽  
Software Bug ◽  
Positive Results

Maintenance of open source software is a hectic task as the number of bugs reported is huge. The number of projects, components and versions in an open source project also contribute to the number of bugs that are being reported. Classification of bugs based on priority and identification of the suitable engineers for assignment of bugs for such huge systems still remains a major challenge. Bugs that are misclassified or assigned to engineers who don’t have the component expertise, drastically affect the time taken towards bug resolution. In this paper we have explored the usage of data mining techniques on the classification of bugs and assignment of bugs to engineers.Our focus was on classifying bugs as either severe or non-severe and identification of engineers who have the right expertise to fix the bugs. The prediction of bug severity and identification of engineers were done by mining bug reports from JIRA, an open source software bug tracking tool. The mining process yielded positive results and will be a decision enhancer for severe bugs in the maintenance phase

Social Networks Structures in Open Source Software Development Teams

2009 ◽  
pp. 346-359
Author(s):  
Yuan Long ◽  
Keng Siau
Keyword(s):  
Social Network ◽  
Open Source ◽  
Open Source Software ◽  
Interaction Pattern ◽  
Tracking Systems ◽  
Monthly Data ◽  
Development Teams ◽  
Longitudinal View ◽  
Software Development Teams ◽  
Bug Tracking

Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in Open Source Software (OSS) teams. Three projects were selected from Source- Forge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a core/periphery model as the projects move forward.

Applicability of Lehman Laws on Open Source Evolution

2015 ◽  
pp. 199-224
Author(s):  
Nisha Ratti ◽  
Parminder Kaur
Keyword(s):  
Open Source ◽  
Real World ◽  
Software Maintenance ◽  
Software Evolution ◽  
Object Oriented ◽  
User Requirements ◽  
Continuous Change ◽  
Essential Characteristic ◽  
Time Period ◽  
Object Oriented Metrics

Software evolution is the essential characteristic of the real world software as the user requirements changes software needs to change otherwise it becomes less useful. In order to be used for longer time period, software needs to evolve. The software evolution can be a result of software maintenance. In this chapter, a study has been conducted on 10 versions of GLE (Graphics Layout Engine) and FGS (Flight Gear Simulator) evolved over the period of eight years. An effort is made to find the applicability of Lehman Laws on different releases of two softwares developed in C++ using Object Oriented metrics. The laws of continuous change, growth and complexity are found applicable according to data collected.

Social Network Structures in Open Source Software Development Teams

2009 ◽  
pp. 645-658
Author(s):  
Yuan Long ◽  
Keng Siau
Keyword(s):  
Social Network ◽  
Open Source ◽  
Open Source Software ◽  
Interaction Pattern ◽  
Network Structures ◽  
Monthly Data ◽  
Development Teams ◽  
Longitudinal View ◽  
Software Development Teams ◽  
Bug Tracking

Drawing on social network theories and previous studies, this research examines the dynamics of social network structures in open source software (OSS) teams. Three projects were selected from SourceForge.net in terms of their similarities as well as their differences. Monthly data were extracted from the bug tracking systems in order to achieve a longitudinal view of the interaction pattern of each project. Social network analysis was used to generate the indices of social structure. The finding suggests that the interaction pattern of OSS projects evolves from a single hub at the beginning to a core/periphery model as the projects move forward.

From Android Bug Reports to Android Bug Handling Process

2016 ◽  
Vol 7 (4) ◽  
pp. 1-18
Author(s):  
Liguo Yu
Keyword(s):  
Project Management ◽  
Open Source ◽  
Tracking System ◽  
Software Project ◽  
Bug Reports ◽  
Bug Report ◽  
Bug Tracking ◽  
Android Development ◽  
Comprehensive Study

Android is an operating system for mobile devices. Its development is led by Google and some other companies. Because of the open-source property of Android, anyone can report a bug through its online bug tracking system. In this paper, we analyze the bug reports of Android operating systems. Specifically, through this study, we would like to answer the following questions regarding Android development and its project management: (1) Could Android bug reports be handled on time? (2) What is the distribution of different maintenance activities initiated by Android bug reports? (3) How long does it take to handle an Android bug report? (4) Are the number of followers and the number of following messages of an Android bug report related to the effort spent on handling this bug report? Through answering these questions, this paper presents a comprehensive study of Android bug reporting and handling process. The information and knowledge obtained through this case study could help us better understand open-source software project, such as its development process and project management.

A Commit Messages-Based Bug Localization for Android Applications

2019 ◽  
Vol 29 (04) ◽  
pp. 457-487 ◽  
Author(s):  
Tao Zhang ◽  
Wenjun Hu ◽  
Xiapu Luo ◽  
Xiaobo Ma
Keyword(s):  
Open Source ◽  
Software Maintenance ◽  
State Of The Art ◽  
Bug Localization ◽  
Two Phase ◽  
Android Apps ◽  
Bug Reports ◽  
Android Applications ◽  
The Given ◽  
General Method

Recently, there has been consistent growth in Android applications (apps). Under these circumstances, software maintenance for Android apps becomes an essential and important task. The core of software maintenance is to locate bugs in source files. Previous bug localization approaches mainly focus on open-source desktop software (e.g. Eclipse, Mozilla, GCC). Even though a few studies locate the bugs in the Android apps, they are dedicated to a special app named ZXing, without developing a general method to locate the bugs in Android apps by taking into account the unique characteristics of Android apps’ bug reports. Such characteristics include fewer number of historical bug reports, insufficient detailed description, etc. These characteristics hinder existing localization approaches from being directly delivered to Android apps, because lack of enough information degrades the performance of those localization approaches relying on historical bug reports. Commit messages include more informative data which can provide the details of reported bugs. Therefore, in this paper, we propose a novel information retrieval-based approach which utilizes commit messages to locate new bugs in Android apps. This approach not only considers the structured textual similarity between the given bug and the candidate source files, but also computes the unstructured textual similarities between the new bug and the commit messages linked to the corresponding source files. According to the experimental results on 10 popular open-source Android apps managed by GitHub, our approach outperforms the state-of-the-art bug localization methods that include BugLocator, BLUiR, and two-phase model.

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