research-article

Nirikshan: mining bug report history for discovering process maps, inefficiencies and inconsistencies

Authors:

Monika Gupta,

Ashish SurekaAuthors Info & Claims

ISEC '14: Proceedings of the 7th India Software Engineering Conference

Article No.: 1, Pages 1 - 10

https://doi.org/10.1145/2590748.2590749

Published: 19 February 2014 Publication History

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Abstract

Issue tracking systems such as Bugzilla, Mantis and JIRA are Process Aware Information Systems to support business process of issue (defect and feature enhancement) reporting and resolution. The process of issue reporting to resolution consists of several steps or activities performed by various roles (bug reporter, bug triager, bug fixer, developers, and quality assurance manager) within the software maintenance team. Project teams define a workflow or a business process (design time process model and guidelines) to streamline and structure the issue management activities. However, the runtime process (reality) may not conform to the design time model and can have imperfections or inefficiencies. We apply business process mining tools and techniques to analyze the event log data (bug report history) generated by an issue tracking system with the objective of discovering runtime process maps, inefficiencies and inconsistencies. We conduct a case-study on data extracted from Bugzilla issue tracking system of the popular open-source Firefox browser project. We present and implement a process mining framework, Nirikshan, consisting of various steps: data extraction, data transformation, process discovery, performance analysis and conformance checking. We conduct a series of process mining experiments to study self-loops, back-and-forth, issue reopen, unique traces, event frequency, activity frequency, bottlenecks and present an algorithm and metrics to compute the degree of conformance between the design time and the runtime process.

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Lyu YCho HJung PLee S(2023)A Systematic Literature Review of Issue-Based Requirement TraceabilityIEEE Access10.1109/ACCESS.2023.324229411(13334-13348)Online publication date: 2023
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Nirikshan: mining bug report history for discovering process maps, inefficiencies and inconsistencies

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Published In

ISEC '14: Proceedings of the 7th India Software Engineering Conference

February 2014

185 pages

ISBN:9781450327763

DOI:10.1145/2590748

General Chair:
Dharanipragada Janakiram
IIT Madras, Chennai
,
Program Chairs:
Koushik Sen
University of California, Berkeley
,
Vinay Kulkarni
Tata Consultancy Services, Pune

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 19 February 2014

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Sponsor:

iSOFT
HP Labs (India)
HCL
C-DAC

ISEC '14: 7th India Software Engineering Conference, Chennai

February 19 - 21, 2014

Chennai, India

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Eren ÇŞahin KTüzün E(2023)Analyzing Bug Life Cycles to Derive Practical InsightsProceedings of the 27th International Conference on Evaluation and Assessment in Software Engineering10.1145/3593434.3593504(162-171)Online publication date: 14-Jun-2023
https://dl.acm.org/doi/10.1145/3593434.3593504
Lyu YCho HJung PLee S(2023)A Systematic Literature Review of Issue-Based Requirement TraceabilityIEEE Access10.1109/ACCESS.2023.324229411(13334-13348)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3242294
Malik PChaudhary K(2023)Mining Repository for Module Reuse: A Machine Learning-Based ApproachInternational Conference on IoT, Intelligent Computing and Security10.1007/978-981-19-8136-4_6(71-81)Online publication date: 2-Apr-2023
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Nirikshan: process mining software repositories to identify inefficiencies, imperfections, and enhance existing process capabilities

Process mining multiple repositories for software defect resolution from control and organizational perspective

SARATHI: Characterization Study on Regression Bugs and Identification of Regression Bug Inducing Changes: A Case-Study on Google Chromium Project

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