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A Review on Search-Based Tools and Techniques to Identify Bad Code Smells in Object-Oriented Systems

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Harmony Search and Nature Inspired Optimization Algorithms

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 741))

Abstract

Researchers have provided various techniques and tools in the past few years for identification of code smells. Due to their changing outcomes and features, the classification, comparison, and evaluation of this existing code smell detection techniques and tool are imperative. This paper presents the current state of the art in the area of approaches that use search-based techniques to identify code smell from the source code of object-oriented systems. The classification of code bad smells approaches is done on the basis of their detection and analysis method. The results of selected techniques were analyzed. The observations and recommendations were presented after critical analysis of existing code smell detection approaches. These observations and recommendations can help the researchers and practitioners working in the area of designing a tool/technique for code smell detection.

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Notes

  1. 1.

    http://ganttproject.biz/index.php

  2. 2.

    http://ptolemy.cs.iastate.edu/design-study/#healthwatcher

  3. 3.

    http://jhotdraw.org

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Thapar University, Patiala, Punjab, India

    Amandeep Kaur & Gaurav Dhiman

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  1. Amandeep Kaur
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  2. Gaurav Dhiman
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Corresponding author

Correspondence to Gaurav Dhiman .

Editor information

Editors and Affiliations

  1. School of Engineering and Technology, BML Munjal University, Gurgaon, Haryana, India

    Neha Yadav

  2. Department of Sciences and Humanities, National Institute of Technology, Srinagar, Uttarakhand, India

    Anupam Yadav

  3. Department of Mathematics, South Asian University, New Delhi, India

    Jagdish Chand Bansal

  4. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  5. School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, Korea (Republic of)

    Joong Hoon Kim

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Kaur, A., Dhiman, G. (2019). A Review on Search-Based Tools and Techniques to Identify Bad Code Smells in Object-Oriented Systems. In: Yadav, N., Yadav, A., Bansal, J., Deep, K., Kim, J. (eds) Harmony Search and Nature Inspired Optimization Algorithms. Advances in Intelligent Systems and Computing, vol 741. Springer, Singapore. https://doi.org/10.1007/978-981-13-0761-4_86

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