Software testing is one of the core fields in software engineering and is the essential technique for quality assurance in industrial software development. Surveys like a NIST study in 2002 reveal that the potential for
improvements in the testing process is still enormous and can reach up to 30% of the costs of the testing process. In the recent years, the area of unit and component testing has been target of crucial innovations. Inspired by the ideas of agile software development the ideas of regression testing and strict separation of test code and system code have found their way into practice. Moreover, the development of model-based testing approaches has been an important step towards a gain of abstraction and tight coupling of test cases and requirements. In contrast,
acceptance tests for a long time have been primarily performed manually, e.g. by the owner or user of the system under test. Acceptance or system testing is commonly understood as black-box testing performed on a system prior to its delivery. In many cases output of acceptance tests are test reports about the behaviour of the system which are produced manually by the tester.
However, in the era of incremental software development non-automated tests are expensive and error-prone.
Therefore a number of tools provide frameworks for executable acceptance tests. A critical issue for executable acceptance tests is to close the gap between the specification of test cases at a business-oriented level and the link to the code of the system under test. Acceptance test frameworks should provide concepts that enable clients to specify or at least to understand test descriptions. While there are quite many success stories in practical
applications acceptance test frameworks so far do not exploit the huge potential that is provided by the information in the requirements specification.
The major goal of the MATE project is to develop a tool-supported method for acceptance tests which on the one side are executable and support regression testing. On the other side acceptance tests shall be tightly coupled with the requirements specification and thus provide potential for automated generation of test cases and tool-supported check of consistency and coverage conditions. The MATE framework will be model-based which in our context means that the system under test is attached with a model of the requirements (called System Model) and the Test Model describes test cases in the language of the model elements of the System Model. Test cases are conceived at business level as exemplified interactions (scenarios) of the actors with the system. The major innovation of MATE is that it provides tight coupling between the requirements specification and the description of test cases and thus paves the way for specifying, checking and generating acceptance tests in a rigorous way.
