Date of Award
5-2022
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Computer Engineering and Sciences
First Advisor
Thomas C Eskridge
Second Advisor
Ryan White
Third Advisor
Siddartha Bhattacharyya
Fourth Advisor
Khaled Slhoub
Abstract
Safety-critical software development is a costly and time-consuming process that involves thousands of hours dedicated to test development. Tests must meet stringent developmental guidelines to verify the correct and complete implementation of their parent requirements. Further compounding any such effort is the tendency towards requirement churn or the frequent change to the software and other system requirements. This thesis presents a solution, PyTcGen, that alleviates these challenges by processing natural language requirements and programmatically generating the requisite test cases to ensure the software meets all of the conditions of that requirement. The solution uses template matching to marry requirements to the code that generates tests. This template matching approach adds a further advantage in the form of a co-evolutionary relationship between requirement authors and the system that drives the creation of more concise requirements while simultaneously increasing the usability of the system.
Recommended Citation
Costa, Brad Thomas, "A Co-Evolutionary Approach to Test Case Generation for Safety-Critical Systems" (2022). Theses and Dissertations. 657.
https://repository.fit.edu/etd/657
Comments
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