Neural Network-Based Automated Priority Assigner

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 381)

Abstract

The testing of a system starts with the crafting of test cases. Not all the test cases are, however, equally important. The test cases can be prioritized using policies discussed in the work. The work proposes a neural network model to prioritize the test cases. The work has been validated using backpropagation neural network. 200 test cases were crafted and the experiment was carried out using 2, 5, 10, 15, and 20 layers neural network. The results have been reported and lead to the conclusion that neural network-based priority analyzer can predict the priority of a test.

Keywords

Algorithms Reliability Verification Neural networks Black-box testing Automated test case generation 

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Copyright information

© Springer India 2016

Authors and Affiliations

  1. 1.Department of Computer ScienceJamia HamdardNew DelhiIndia
  2. 2.Department of Computer ScienceAITMFaridabadIndia
  3. 3.Department of Computer ScienceDelhi Technological UniversityNew DelhiIndia

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