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9/27/2017  |   10:25 AM - 11:10 AM   |  Track 3 - Metrics

Comparing JIRA and Bugzilla for Software Project Tracking and Data Collection

JIRA has become an industry standard for tracking defects and project progress. Though many project managers and developers reported how JIRA improved productivity and progress visibility, many open source software development environments still use Bugzilla. Very few discussions exist on how easily data can be extracted from these tools for data analysis. Masters-level students taking a Software Engineering course at the University of Southern California (USC) have used both JIRA and Bugzilla for task distribution and management. Three of the authors of this paper collected data from both tools for analyses. This paper will evaluate the pros and cons of using JIRA and Bugzilla for defect and project tracking, and how easily data can be collected from both tools. Additionally, the authors asked developers and project managers from a software company to share their experiences with JIRA and Bugzilla to complement the findings from the academic environment.

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Barry Boehm (Co-Author), USC, boehm@usc.edu;
Dr. Barry Boehm is the TRW Professor in the USC Computer Sciences, Industrial and Systems Engineering, and Astronautics Departments. He is also the Director of Research of the DoD-Stevens-USC Systems Engineering Research Center, and the founding Director of the USC Center for Systems and Software Engineering. He was director of DARPA-ISTO 1989-92, at TRW 1973-89, at Rand Corporation 1959-73, and at General Dynamics 1955-59. His contributions include the COCOMO family of cost models and the Spiral family of process models. He is a Fellow of the primary professional societies in computing (ACM), aerospace (AIAA), electronics (IEEE), and systems engineering (INCOSE), and a member of the U.S. National Academy of Engineering.

Anandi Hira (Primary Presenter,Author), University of Southern California, a.hira@usc.edu;
Anandi Hira is currently a PhD student under Dr. Barry Boehm at University of Southern California’s (USC) Computer Science Department. Her research interests lie in cost estimation and models. She has been a part of the Unified Code Count (UCC) development effort at USC's Center for Systems and Software Engineering (CSSE) for the past 6 years, and has been collecting and analyzing the data to improve the development processes and the product’s quality. Anandi has also joined the effort within USC's CSSE to develop COCOMO® III (COnstructive COst MOdel) as an update from COCOMO® II.

Alexey Tregubov (Co-Presenter,Author,Co-Author), University of Southern California, tregubov@usc.edu;
Alexey Tregubov is currently a Ph.D. candidate at the University of Southern California, Department of Computer Science. His primary area of research is system and software engineering. Alexey holds a Master Degree in Engineering and Technology from Novosibirsk State University (Russia), and a Master Degree in Computer Science from University of Southern California. For more than two years, Alexey has worked as a software engineer in MSS-Holding Inc. (Russia). Alexey’s recent research projects include the Kanban-based Scheduling System Simulator – evaluation of Kanban-based Scheduling in SoS; and the DATASEM – an agent-based simulation framework for modeling software and system engineering processes.

Shreya Sharma (Co-Author), University of Southern California, shreyas;
Shreya Sharma is a software engineer with a deep interest in the principles of software engineering. She completed her Masters’ degree in Computer Science at University of Southern California (USC). During that time, she worked with Anandi and Professor Boehm in collecting data and analyzing the effort trends for Unified Code Count (UCC)’s tasks, resulting in a paper titled Calibrating COCOMO® II for Projects with High Personnel Turnover. She currently works as a Software Development Engineer using Java, Rails, Javascript, and social media.

Sultan Alsarra (Co-Author), University of Southern California, alsarra@usc.edu;
Sultan Alsarra recently attained his Masters’ degree from the University of Southern California (USC), in Computer Science with a specialty in Software Engineering. While attaining his Master’s degree, Sultan worked on gathering data from the Software Engineering course tools taught at USC. This paper reflects some of the work from this effort. Currently, he is planning to pursue his PhD in Software Engineering from the University of Texas in Dallas. His research interests are: software development methodologies, software life cycle models, requirements engineering, and software design.

2017 Sponsors: IEEE and IEEE Computer Society