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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | A STUDY ON LEAK DETECTION OF LOW-OVERHEAD MEMORY THROUGH ADAPTIVE STATISTICAL PROFILING |
| Authors Name: | Kambapu Sai Srinivasa Reddy , Gourav Katoch , Rahul Kaushal |
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IJNRD_217724
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| Published Paper Id: | IJNRD2404192 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| 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%).” |
| Keywords: | Low-overhead monitoring, Memory leaks. Performance, Reliability, Runtime analysis, Verification. |
| Cite Article: | "A STUDY ON LEAK DETECTION OF LOW-OVERHEAD MEMORY THROUGH ADAPTIVE STATISTICAL PROFILING", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.b740-b760, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404192.pdf |
| Downloads: | 00055 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2404192 Registration ID: 217724 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: b740-b760 Country: Srikakulam, Andhra Pradesh, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404192 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404192 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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