Abstract
Software Bug Localization (SBL) is a task of locating the buggy source code. There are various ways of doing SBL and one of them is static SBL which utilizes the power of Text Mining (TM) in association with software repositories. Most of static SBL models are based on Information Retrieval (IR) methodology in which bug report works as a query and source code as database. In this paper we review state of the art SBL models which uses text mining techniques as their back bone in conjunction with other techniques. Essential features are extracted and summarized with the help of tabular representation. Aim of doing this study is to find the gaps in previous SBL models for proposing a novel SBL model in future.
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