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Procedia Computer Science
Article . 2018 . Peer-reviewed
License: CC BY NC ND
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Procedia Computer Science
Article
License: CC BY NC ND
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Optimization of Software Testing

Authors: Mundita Awotar; Roopesh Kevin Sungkur;

Optimization of Software Testing

Abstract

Abstract The goal of any business is to satisfy the needs of its target customers, and IT industry is not an exception from that rule. Thus, the upgraded version of the V-model testing is supposed to deal with the weaknesses of the original version in question by combining it with the method known as agile testing. At the beginning of the report, hypothesis such as the strengths and weaknesses of the existing V-model testing via literature review and interviews with respective specialists in the sphere were analysed. Successively, the possible advantages of agile method of testing were then considered. Moreover, the report comes up with the ways in which the two models could be naturally combined to produce a much more effective one. Once the new model was presented, its strengths and weaknesses were assessed by the means of a case study analysis using metric and a data analysis through a survey were conducted to evaluate the credibility of the futurist model. Promptly, the research found that the suggested testing model provides better results than the common version of V-model testing. Firstly, a real case scenarios under metric evaluation of the models have indicated that the proposed model is better than the V-model, since it can handle the following aspects; reduced testing time, debugging, prioritization of requirements, easy mapping of roles and improved visibility of project resources. Secondly, a survey data analysis highlighted various advantages of the future model. The top priorities of the new model from the respondent’s perception were; the new model manages rapidly changing priorities, it accelerates time to market, it increases productivity and it improves quality.

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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
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!
2
Average
Average
Average
gold