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Neutrosophic AHP Approach for Budget Constrained Reliability Allocation Among Modules of Software System

In: Optimization Models in Software Reliability

Author

Listed:
  • Vibha Verma

    (University of Delhi)

  • Sameer Anand

    (Shaheed Sukhdev College of Business Studies)

  • Anu G. Aggarwal

    (University of Delhi)

Abstract

The planning and implementation of software development process should go hand in hand with the user expectations. It is crucial for firms to develop products catering user needs along with software engineers and programmers opinion. Many models have been developed in literature to allocate reliabilities to modules by setting system reliability goal based on hierarchy that inter-connects the attitudes of both developers and users. In this Chapter, we have proposed a hybrid reliability allocation model by integrating Analytical Hierarchical Process and reliability maximization problem for the software system based on the budget and reliability constraints. The comparison among functions, programs and modules by users, engineers and programmers respectively at different levels of hierarchy is performed under Neutrosophic environment to incorporate the vague and inconsistent information available. The relative weight obtained for each module is further used in optimization problem to finally allocate reliabilities to modules with the aim of maximizing the overall reliability of the software system considering the financial constraints associated with the project. The proposed methodology has been explained in detail and implemented through example problem.

Suggested Citation

  • Vibha Verma & Sameer Anand & Anu G. Aggarwal, 2022. "Neutrosophic AHP Approach for Budget Constrained Reliability Allocation Among Modules of Software System," Springer Series in Reliability Engineering, in: Anu G. Aggarwal & Abhishek Tandon & Hoang Pham (ed.), Optimization Models in Software Reliability, pages 193-213, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-030-78919-0_9
    DOI: 10.1007/978-3-030-78919-0_9
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