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Validation of Object-Oriented Metrics Against Standard Properties

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Proceedings of Fifth Doctoral Symposium on Computational Intelligence (DoSCI 2024)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 1085))

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Abstract

The field of software development has adopted object-oriented mechanism (OOM) widely. The software quality can be measured by evaluating quality measures such as reliability, reusability and maintainability. Reusability is most important attribute of software quality that helps developers produce high-quality, affordable software. Various metrics and model are available that can be utilize to evaluate the quality of object-oriented (OO) software. Here, we propose a metric set consisting of five metrics namely inherited class count, inherited attribute count, inherited method count, inheritance hierarchy, and degree of reusability to describe the effects of inheritance and reusability on the design quality of OO software. The validation of these metrics through three major validation framework has also been done.

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Authors and Affiliations

  1. Harcourt Butler Technical University, Kanpur, India

    Sumit Babu & Raghuraj Singh

Authors
  1. Sumit Babu
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  2. Raghuraj Singh
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Corresponding author

Correspondence to Sumit Babu .

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Editors and Affiliations

  1. Department of Information Technology, Bhagwan Parshuram Institute of Technology, New Delhi, Delhi, India

    Abhishek Swaroop

  2. Dr. APJ Abdul Kalam Technical University, Institute of Engineering and Technology, Lucknow, Uttar Pradesh, India

    Vineet Kansal

  3. University of Calabria, Rende (CS), Italy

    Giancarlo Fortino

  4. Faculty of Computers and Information, IT Department, Cairo University, Giza Governorate, Egypt

    Aboul Ella Hassanien

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Babu, S., Singh, R. (2024). Validation of Object-Oriented Metrics Against Standard Properties. In: Swaroop, A., Kansal, V., Fortino, G., Hassanien, A.E. (eds) Proceedings of Fifth Doctoral Symposium on Computational Intelligence. DoSCI 2024. Lecture Notes in Networks and Systems, vol 1085. Springer, Singapore. https://doi.org/10.1007/978-981-97-6726-7_17

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