Harsh Bhasin

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Manual Test Data Generation is an expensive, error prone and tedious task. Therefore, there is an immediate need to make the automation of this process as efficient and effective as possible. The work presented intends to automate the process of Test Data Generation with a goal of attaining maximum coverage. A Cellular Automata system is discrete in space(More)
Test Data Generation is the soul of automated testing. The dream of having efficient and robust automated testing software can be fulfilled only if the task of designing a robust automated test data generator can be accomplished. In the work we explore the gaps in the existing techniques and intend to fill these gaps by proposing new algorithms. The(More)
  • Harsh Bhasin, Shewani M Tech Scholar, A I T M, Deepika Goyal
  • 2016
Test Data Generation is an intricate process which requires intensive manual labor and thus a lot of project time. There is an immediate need of finding out an effective technique for automating the process as manual Test Data Generation escalates the project cost. The paper proposes the use of Artificial Life in generating and minimizing the Test Cases.(More)
Manual test data generation is carried out by using the ability of neurons to recognize patterns. The nervous system and the brain coordinate to generate test cases, which are capable of finding potential faults. Automated test data generators lack the ability to produce efficient test cases because they do not imitate natural processes. This paper proposes(More)
Black Box Testing is immensely important because the source code of a module is not always available. Enterprise Resource Planning systems are also tested using Black Box Testing wherein all the test cases are not equally important. The prioritization of these test cases would be helpful in case of premature termination of testing, due to lack of resources.(More)
Automated test-data generation is a convoluted task. The quality of test cases generated determines the quality of the program under test. This paper proposes two major changes in the architecture of the automated test-data generator proposed in our earlier work. The new model of artificial-life-based test-data generation uses an s-box-based component. The(More)
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