Automatic test Oracle for image processing applications using support vector machines

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Software testing has been a challenging job over the decades and possess more challenges for complex inputs such as images. While evaluating correctness of the output images, there may exist a large number of correct or incorrect images with insignificant differences. A test oracle is required to evaluate the correctness of output images which may not be available in most of the cases. Currently, output images are evaluated by domain experts such as medical experts, which involves manual inspection of output images at each step of software development. In this paper, we have proposed a mechanism to automate the test oracle using support vector machine. It requires a few correct and incorrect images for the training and is capable of classification of correct and incorrect output images. For the demonstration purpose, we used different implementations of image dilation and compared the results with statistical oracle and metamorphic testing. The results in our initial experiments are encouraging.

Original languageEnglish
Title of host publicationICSESS 2015 - Proceedings of 2015 IEEE 6th International Conference on Software Engineering and Service Science
EditorsM. Surendra Prasad Babu, Li Wenzheng
PublisherIEEE Computer Society
Pages1110-1113
Number of pages4
ISBN (Electronic)9781479983520
DOIs
StatePublished - 25 Nov 2015
Event6th IEEE International Conference on Software Engineering and Service Science, ICSESS 2015 - Beijing, China
Duration: 23 Sep 201525 Sep 2015

Publication series

NameProceedings of the IEEE International Conference on Software Engineering and Service Sciences, ICSESS
Volume2015-November
ISSN (Print)2327-0586
ISSN (Electronic)2327-0594

Conference

Conference6th IEEE International Conference on Software Engineering and Service Science, ICSESS 2015
Country/TerritoryChina
CityBeijing
Period23/09/1525/09/15

Keywords

  • Machine Learning
  • Test Oracle
  • Testing Imaging Applications

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