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TEST CASE PRIORITIZATION USING HYPERLINK RANKING - A GRAPH THEORY BASED APPROACH

Authors: Krithika L. B; Selvakumar R; Anand Mahendran;

TEST CASE PRIORITIZATION USING HYPERLINK RANKING - A GRAPH THEORY BASED APPROACH

Abstract

Era of cloud computing where majority of the applic ation is becoming web based enterprise computing. U ser prefer online web application for easy of use and business continuity [1]. Software companies have come up in huge numbe rs for developing web based enterprise application. Testing is an integral part of any software company which requires more effort . Enterprise applications are complex and navigation is largely based on hyperlin k connecting the web pages. Testing phase mostly as sociated with time constrain to accomplish the task associated in this phase. Ma in activity of testing phase is execution of test case to test the application. Exhaustive testing is not possible and release a so ftware system without testing the entire applicatio n is risk [2]. This paper demonstrates how graph theory can be used to priori tize the test case execution.

  • BIP!
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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    3
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
gold