Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/27601
Title: Novel approach for software reliability based on immune technique filters
Researcher: Chitra, S
Guide(s): Rajaram, M
Keywords: Data mining
Immune filters
Information and communication engineering
Neural network classification method
Software reliability
Software reliability based on immune technique
Upload Date: 7-Nov-2014
University: Anna University
Completed Date: 01/06/2009
Abstract: In this thesis an innovative model Software Reliability Based on Immune Technique SRBIT and Neural Network Classification Methods NNCM is proposed to ensure the software reliability with High Efficiency Immune Filters HEIF and Data Normalization of software metrics With the newlineavailability of cost effective technology about 80 of software systems are running on legacy platforms Reliability assessment of upgraded legacy systems is an important problem in any company s IT infrastructure Some parts of the code used in the original design of such systems might be currently being discontinued Trustworthy reliability assurance after an upgrade with a new software component is needed which combines the evidence about the reliability of the new component with the knowledge about the old system accumulated to date In these circumstances machine learning approach to reliability assessment is invaluable It is proposed to study data preprocessing on tupules to improve the classification of legacy modules using various data newlinemining techniques for practical reliability assessment Irregularities are widespread if the software has a large number of modules and often lead to erroneous conclusions with respect to data mining and statistical analysis newline
Pagination: xiv, 113p.
URI: http://hdl.handle.net/10603/27601
Appears in Departments:Faculty of Information and Communication Engineering

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01_title.pdfAttached File60.76 kBAdobe PDFView/Open
02_certificate.pdf6.04 kBAdobe PDFView/Open
03_abstract.pdf10.01 kBAdobe PDFView/Open
04_acknowledgement.pdf6.74 kBAdobe PDFView/Open
05_contents.pdf25.26 kBAdobe PDFView/Open
06_chapter1.pdf257.67 kBAdobe PDFView/Open
07_chapter2.pdf79.68 kBAdobe PDFView/Open
08_chapter3.pdf47.87 kBAdobe PDFView/Open
09_chapter4.pdf60 kBAdobe PDFView/Open
10_chapter5.pdf24.88 kBAdobe PDFView/Open
11_chapter6.pdf10.4 kBAdobe PDFView/Open
12_appendix.pdf329.54 kBAdobe PDFView/Open
13_references.pdf30.02 kBAdobe PDFView/Open
14_publications.pdf13.75 kBAdobe PDFView/Open
15_vitae.pdf8.58 kBAdobe PDFView/Open


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