A STUDY ON LEAK DETECTION OF LOW-OVERHEAD MEMORY THROUGH ADAPTIVE STATISTICAL PROFILING

Registration ID: IJNRD_217724

Published ID: IJNRD2404192

DOI: Click Here to Get

Kambapu Sai Srinivasa Reddy , Gourav Katoch , Rahul Kaushal

Low-overhead monitoring, Memory leaks. Performance, Reliability, Runtime analysis, Verification.

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%).”

Published Paper   E-Certificate

Kambapu Sai Srinivasa Reddy , Gourav Katoch, & Rahul Kaushal (April-2024). A STUDY ON LEAK DETECTION OF LOW-OVERHEAD MEMORY THROUGH ADAPTIVE STATISTICAL PROFILING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), b740-b760. https://ijnrd.org/papers/IJNRD2404192.pdf

Volume 9 Issue 4, April-2024

Pages : b740-b760

Paper Reg. ID: IJNRD_217724

Published Paper Id: IJNRD2404192

Downloads: 000121987

Research Area: Computer Science & Technology 

Country: Srikakulam, Andhra Pradesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404192.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404192

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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