Development of a scalable parser for extracting artifacts during model-based test case generation process

Abstract

The foundation of any software testing process is test case generation. If test cases are poorly generated, model-based software testing results becomes unreliable or misleading. In model-based software testing, test cases are generated from any modeling tool that contains user’s requirements. To generate test cases from modeling tools, a parser is required to read, extract, interpret and display parsed requirements or artifacts which are executed to generate test cases. Existing model-based testing techniques lacks parsers that are capable of reading, extracting and interpreting all diagrams contained in a modeling tool at runtime. This has caused flexibility problems during test case generation. Consequently, this research aims to develop a scalable parser that can aid automatic test case generation from all UML diagrams at runtime.