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Implementing Bug Severity Prediction through Information Mining Using KNN Classifier


Author(s):

Pankaj Rana , SRI SAI UNIVERSITY PALAMPUR; Saurabh Sharma, sri sai university palampur

Keywords:

Bug Severity, Bug Repositories, Bug Priority, Severity Prediction, Natural Language Processing, Machine Learning

Abstract:

The severity of a according bug may be crucial think about deciding however presently it has to be fastened. Correct severity assessment is crucial for acceptable resource allocation and coming up with for fixing activities and extra testing. Severity assessment is powerfully influenced by the expertise of the take a look at engineers and by the time they pay on every issue. Code bug coverage is an integral a part of code development method. Once the bug is according on bug following system, their attributes analyzed and later on allocated to numerous fixers for his or her resolution. Bug severity, an attribute of a code bug report is that the degree of impact that a defect has on the event or operation of a element or system. Bug severity is classified into totally different levels supported their impact on the system. Prioritization of bugs decides the bug fix sequence. Incorrect prioritization of bugs leads to delay of break down the necessary bugs, that leads delay in unharness of the code. Prediction of bug priority wants historical knowledge on that we will train the classifiers. With the increasing dependence on code systems, importance of code quality is turning into additional crucial. There are other ways to make sure quality in code like code reviews and accurate testing in order that bugs is removed as early as attainable to stop the loss it should cause. “Every code program is rarely excellent, there’s forever a minimum of one bug in it which may be encountered at any time.” Software bug is usually wont to describe the prevalence of a fault in an exceedingly package which ends up it to act otherwise from its specification. Its encountered whereas operative the products either below take a look at or whereas in use.


Other Details:

Manuscript Id :IJSTEV2I4014
Published in :Volume : 2, Issue : 4
Publication Date: 01/11/2015
Page(s): 333-340
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