scholarly journals Study of Various Bug Tracking Tools

2020 ◽  
Vol 1 (2) ◽  
Keyword(s):  
Bug Tracking

scholarly journals Analysing installation scenarios of Debian packages

2020 ◽  
pp. 235-253
Author(s):  
Benedikt Becker ◽  
Nicolas Jeannerod ◽  
Claude Marché ◽  
Yann Régis-Gianas ◽  
Mihaela Sighireanu ◽  
...  
Keyword(s):  
Formal Verification ◽  
Tracking System ◽  
Symbolic Execution ◽  
Large Set ◽  
System Maintenance ◽  
Bug Tracking ◽  
Almost All

Abstract The Debian distribution includes more than 28 thousand maintainer scripts, almost all of them are written in Posix shell. These scripts are executed with root privileges at installation, update, and removal of a package, which make them critical for system maintenance. While Debian policy provides guidance for package maintainers producing the scripts, few tools exist to check the compliance of a script to it. We report on the application of a formal verification approach based on symbolic execution to find violations of some non-trivial properties required by Debian policy in maintainer scripts. We present our methodology and give an overview of our toolchain. We obtained promising results: our toolchain is effective in analysing a large set of Debian maintainer scripts and it pointed out over 150 policy violations that lead to reports (more than half already fixed) on the Debian Bug Tracking system.

Tools and Datasets for Mining Libre Software Repositories

2011 ◽  
pp. 24-42 ◽  
Author(s):  
Gregorio Robles ◽  
Jesús M. González-Barahona ◽  
Daniel Izquierdo-Cortazar ◽  
Israel Herraiz
Keyword(s):  
Source Code ◽  
Data Sources ◽  
The Internet ◽  
Software Projects ◽  
Free Open Source Software ◽  
Mailing Lists ◽  
Bug Tracking ◽  
Libre Software ◽  
Free Open Source ◽  
Open Nature

Thanks to the open nature of libre (free, open source) software projects, researchers have gained access to a rich set of data related to various aspects of software development. Although it is usually publicly available on the Internet, obtaining and analyzing the data in a convenient way is not an easy task, and many considerations have to be taken into account. In this chapter we introduce the most relevant data sources that can be found in libre software projects and that are commonly studied by scholars: source code releases, source code management systems, mailing lists and issue (bug) tracking systems. The chapter also provides some advice on the problems that can be found when retrieving and preparing the data sources for a later analysis, as well as information about the tools and datasets that support these tasks.

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.

The social structure of free and open source software development

First Monday ◽  
2005 ◽  
Author(s):  
Kevin Crowston ◽  
James Howison
Keyword(s):  
Social Structure ◽  
Open Source Software ◽  
Tracking System ◽  
Communication Patterns ◽  
Project Teams ◽  
Development Teams ◽  
The Social ◽  
Wide Range ◽  
Bug Tracking ◽  
The Relationship

Metaphors, such as the Cathedral and Bazaar, used to describe the organization of FLOSS projects typically place them in sharp contrast to proprietary development by emphasizing FLOSS’s distinctive social and communications structures. But what do we really know about the communication patterns of FLOSS projects? How generalizable are the projects that have been studied? Is there consistency across FLOSS projects? Questioning the assumption of distinctiveness is important because practitioner–advocates from within the FLOSS community rely on features of social structure to describe and account for some of the advantages of FLOSS production. To address this question, we examined 120 project teams from SourceForge, representing a wide range of FLOSS project types, for their communications centralization as revealed in the interactions in the bug tracking system. We found that FLOSS development teams vary widely in their communications centralization, from projects completely centered on one developer to projects that are highly decentralized and exhibit a distributed pattern of conversation between developers and active users. We suggest, therefore, that it is wrong to assume that FLOSS projects are distinguished by a particular social structure merely because they are FLOSS. Our findings suggest that FLOSS projects might have to work hard to achieve the expected development advantages which have been assumed to flow from "going open." In addition, the variation in communications structure across projects means that communications centralization is useful for comparisons between FLOSS teams. We found that larger FLOSS teams tend to have more decentralized communication patterns, a finding that suggests interesting avenues for further research examining, for example, the relationship between communications structure and code modularity.

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