Paper Title
A STUDY ON LEAK DETECTION OF LOW-OVERHEAD MEMORY THROUGH ADAPTIVE STATISTICAL PROFILING
Article Identifiers
Authors
Kambapu Sai Srinivasa Reddy , Gourav Katoch , Rahul Kaushal
Keywords
Low-overhead monitoring, Memory leaks. Performance, Reliability, Runtime analysis, Verification.
Abstract
Sampling has been effectively used to find chances for performance enhancement. We want to use comparable methods to ensure that the software is proper. Sadly, sampling covers little of the seldom-run code, where problems are most likely to hide. To address this, researcher provide an adaptive profiling system that samples code segment executions at “a rate inversely proportionate to the execution frequency.” Our innovative “memory leak detection program, SWAT,” has been put into action to verify our concepts. Using our adaptive profiling architecture, SWAT creates a heap model by tracking program allocations and frees. It then utilizes this model to monitor loads and store these objects with minimal cost. "Stale" items that haven't been used in a "long" period is reported as leaks by SWAT. This enables it to identify any leak that appears while the application is running. The minimal space cost (< 10% in most circumstances, and often less than 5%) and low runtime overhead (< 5%) of SWAT make it useful for tracking production code leaks that take days to appear. Apart from pinpointing the memory leak allocations, SWAT also reveals the last place the application accessed the compromised data, hence aiding in the debugging and leak repair process. Over the last 18 months, “SWAT has been deployed by several Microsoft product groups and has shown to be successful at discovering leaks with a low false positive rate (<10%).”
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How To Cite
"A STUDY ON LEAK DETECTION OF LOW-OVERHEAD MEMORY THROUGH ADAPTIVE STATISTICAL PROFILING", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 4, page no.b740-b760, April-2024, Available :https://ijnrd.org/papers/IJNRD2404192.pdf
Issue
Volume 9 Issue 4, April-2024
Pages : b740-b760
Other Publication Details
Paper Reg. ID: IJNRD_217724
Published Paper Id: IJNRD2404192
Downloads: 000121157
Research Area: Computer Science & TechnologyÂ
Country: Srikakulam, Andhra Pradesh, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2404192.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404192
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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