A Machine Learning Technique for Abstraction of Modules in Legacy System and Assigning them on Multicore Machines Using and Controlling p-threads

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Forward Engineering and Reverse Engineering
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Published: Dec 31, 2022
DOI: https://doi.org/10.17762/ijritcc.v10i12.5837
Keywords:
Multicore Machines, Legacy Systems, Reverse Engineering, Multi-threads

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Vinay T R
Dept. of Artificial Intelligence and Data Science, Ramaiah Institute of Technology, Bengaluru, India
Ajeet A Chikkamannur
Dept. of Computer Science, Nagarjuna College of Engineering and Technology, Bengaluru, India

Abstract

Hardware and Software technology has undergone a sea-of-change in recent past. Hardware technology has moved from single-core to multi-core machine, thus capable of executing multi-task at the same time. But traditional software’s (Legacy system) are still in use today in business world. It is not easy to replace them with new software system as they carry loads of knowledge, business value with them. Also, to build new software system by taking the requirements afresh involves lot of resources in terms of skilled human resources, time and financial resources. At last the customer may not have confidence in this new software. Instead of building a new software, an attempt is made to develop a semi-automated methodology by learning about the program itself (machine learning about the program) to abstract the independent modules present in the same abstraction level (implementation level) and recode the legacy program (single threaded program) into multi-threaded parallel program. A case study program is considered and execution time is noted and analyzed for both the original program and reengineered program on a multi-core machine.

Article Details

How to Cite
T R, V. ., & Chikkamannur, A. A. . (2022). A Machine Learning Technique for Abstraction of Modules in Legacy System and Assigning them on Multicore Machines Using and Controlling p-threads. International Journal on Recent and Innovation Trends in Computing and Communication, 10(12), 21–25. https://doi.org/10.17762/ijritcc.v10i12.5837
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Vol. 10 No. 12 (2022): December (2022) Issue
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Articles

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