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  Published Paper Details:

  Paper Title

AUTOMATED THREAD ERROR DETECTION

  Authors

  Prof.Deepak Patil,  Digambar P. Patil,  Priyanka L. Gaikwad,  Miyalal Irshad Mulla,  Om Anil Rote, Tanmay khairnar

  Keywords

AUTOMATED THREAD ERROR DETECTION

  Abstract


This work proposes Automated Thread Error Detection, a system employing machine learning to examine program execution traces to discover threading issues such as data races and deadlocks. distinguishes between harmless and serious faults and has scalability and adaptability. Automated Thread Error Detection appears to be a promising solution to improve software quality and productivity through experiments and case studies, as it demonstrates superior performance in identifying threading errors the accuracy statistic shows the proportion of properly predicted labels. In this instance, the model's accuracy was 92.45%, meaning that 92.45% of the test dataset's samples were properly identified. High accuracy shows that the model can generalize well to new data and has picked up useful patterns from the training set.

  IJCRT's Publication Details

  Unique Identification Number - IJCRTAC02022

  Paper ID - 260953

  Page Number(s) - 111-114

  Pubished in - Volume 12 | Issue 5 | May 2024

  DOI (Digital Object Identifier) -   

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Prof.Deepak Patil,  Digambar P. Patil,  Priyanka L. Gaikwad,  Miyalal Irshad Mulla,  Om Anil Rote, Tanmay khairnar,   "AUTOMATED THREAD ERROR DETECTION", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 5, pp.111-114, May 2024, Available at :http://www.ijcrt.org/papers/IJCRTAC02022.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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