Improving the Precision of Fowler's Definitions of Bad Smells

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/SEW.2008.26Current approaches to detecting bad smells in code are mainly based on software metrics. We suggest that these methods lack precision in detecting bad smells, and we propose a code pattern-based approach to detecting bad smells. However before such a pattern-based approach can be implemented, Fowler's original definitions of bad smells need to be made more precise. Currently Fowler's definitions are too informal to implement in a pattern-searching tool. In this paper we use an expert panel to evaluate our enhanced definitions for five of Fowler's bad smells. We use a questionnaire to survey four experts' opinions of our bad smell definitions. Our results show that the experts basically agree with our enhanced definitions of the message chains, middle man and speculative generality bad smells. However, there are strong disagreements on our definitions of the data clumps and switch statements bad smells. We present enhanced definitions on the basis of these expert opinions.Peer reviewe