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Modelling and measuring code smells in enterprise applications using TISM and two-way assessment

Author

Listed:
  • Viral Gupta

    (Amity University Uttar Pradesh)

  • P. K. Kapur

    (Amity University Uttar Pradesh)

  • Deepak Kumar

    (Amity University Uttar Pradesh)

Abstract

Code smells are the faults in design that reduces the code maintainability. It is essential to identify and control these code smells during the design and development stages of enterprise application implementation in order to achieve higher code maintainability and quality. This research paper presents a framework that engages in modelling and measuring various code smells so that practitioners can focus their efforts on most critical code smells and thus achieve higher code maintainability and quality. The framework uses Total Interpretive Structural Modelling (TISM) for modelling and structuring various code smells. TISM helps in identifying Interrelationship among these code smells. Using MICMAC analysis, these code smells are classified into four clusters based on their driving power and dependence power. Two-way assessment helps in measuring the code smells by deriving the utility measure based on the expert opinion of two set of stakeholders. An experiment is conducted on an enterprise application project and code smells are measured using two-way assessment. It is demonstrated that the code smells having high driving power are optimized which resulted in the elevation of the overall code maintainability of the enterprise applications. The proposed framework optimizes the process of enhancing the overall code maintainability by identification of most critical code smells having higher driving power and then optimizing them.

Suggested Citation

  • Viral Gupta & P. K. Kapur & Deepak Kumar, 2016. "Modelling and measuring code smells in enterprise applications using TISM and two-way assessment," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(3), pages 332-340, September.
    • Handle: RePEc:spr:ijsaem:v:7:y:2016:i:3:d:10.1007_s13198-016-0460-0
    DOI: 10.1007/s13198-016-0460-0
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    Citations

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    Cited by:

    1. Abhishek Srivastava & Deepti Mehrotra & P. K. Kapur & Anu G. Aggarwal, 2020. "Analytical evaluation of agile success factors influencing quality in software industry," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(2), pages 247-257, July.
    2. Viral Gupta & P. K. Kapur & Deepak Kumar, 2019. "Prioritizing and Optimizing Disaster Recovery Solution using Analytic Network Process and Multi Attribute Utility Theory," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 171-207, January.
    3. Madhukar Patil & M. Suresh, 2019. "Modelling the Enablers of Workforce Agility in IoT Projects: A TISM Approach," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 20(2), pages 157-175, June.

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