PARADIGM-COV A Multimensional Test Coverage Analysis Tool

Abstract

Currently, software tends to assume increasingly critical roles in our society so assuring its quality becomes ever more crucial. There are several tools and processes of software testing to help increase quality in virtually any type of software. One example is the so called Model-Based Testing (MBT) tools, that generate test cases from models. However, most of these tools have a configuration phase, where test input data is provided manually by the tester, which influences the quality of the test suite generated. By adding coverage analysis to MBT tools it is possible to give feedback and help the tester to define the configuration data needed to achieve the most valuable test suite as possible. This paper presents a tool, PARADIGM-COV, that produces coverage information both over the PARADIGM model elements (to assess if input data is adequate to cover the test goals and assess if preconditions are achievable), and during test case execution (to identify the parts of the model/code that were actually exercised).