A fuzzy-based approach for bug report categorisation Online publication date: Mon, 20-Nov-2017
by Indu Chawla; Sandeep Kumar Singh
International Journal of Intelligent Systems Technologies and Applications (IJISTA), Vol. 16, No. 4, 2017
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.
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