Studying bugs in the Salt Configuration Management System

Bachelor thesis (2022)

Authors

B.Y. He Electrical Engineering, Mathematics and Computer Science

Contributors

D. Spinellis Software Engineering - EEMCS (mentor)
Thodoris Sotiropoulos Athens University of Economics and Business (mentor)
F. Broz Interactive Intelligence - EEMCS (graduation committee member)
Faculty
Electrical Engineering, Mathematics and Computer Science, Electrical Engineering, Mathematics and Computer Science
Copyright: © 2022 Bryan He
More Info
expand_more

Published Date

22-06-2022

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Configuration management systems are a class of software used to automate system administrative tasks, one of which is the configuration of software systems. Although the automation is less error-prone than manual configuration done by a human, bugs in the source code can still cause configuration errors. This can result into unwanted consequences for the managed software system, some examples are performance degradation, downtime and security breaches.

Bug studies are conducted on previously reported bugs to find out their characteristics. Such findings help with preventing, detecting and fixing bugs, which ultimately causes software to become more reliable. This paper aims to fill in a research gap in the literature surrounding bug studies conducted on configuration management systems. From Salt, a widely used open-source configuration management system, a data-set of 5,896 bugs with fixes was collected. The main research question answered by this paper is ``What are the common patterns can be extracted from bugs found in Salt?'' To answer this, 100 bugs were randomly sampled from this data-set to analyze their symptoms, root causes, impact, fixes, system-dependence and triggers.