Title: A fuzzy-based approach for bug report categorisation

Authors: Indu Chawla; Sandeep Kumar Singh

Addresses: Computer Science and Information Technology Department, Jaypee Institute of Information Technology, A-10, Sector-62, Noida 201 309, Uttar Pradesh, India ' Computer Science and Information Technology Department, Jaypee Institute of Information Technology, A-10, Sector-62, Noida 201 309, Uttar Pradesh, India

Abstract: Various studies conducted on bug repositories utilise issue reports labelled as 'bug'. Research conducted on a number of bug repositories have shown that not all issue reports labelled as 'bug' are actually bugs but can also be a request for additional feature, improvement or documentation. This not only threatens the validity of studies that have used mislabelled data but may also give wrong prediction results in future. This has necessitated need for correct labelling of issue reports. The proposed work using fuzzy logic classifier suggests improvement and also reduces the complexity. Validation of this work is done using five open source projects. Experimental results have shown that our approach gives better F-measure scores. The study also elaborated on use of issue reports from other similar projects for training a model; the impact of frequent terms from the training data and applicability of our approach to fine grained categorisation of issues.

Keywords: ITSs; issue tracking system; automated issue labelling; fuzzy similarity; open source systems; software maintenance; issue reports; bug repositories.

DOI: 10.1504/IJISTA.2017.088056

International Journal of Intelligent Systems Technologies and Applications, 2017 Vol.16 No.4, pp.319 - 341

Received: 29 Sep 2016
Accepted: 02 Mar 2017
Published online: 20 Nov 2017 *

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