On Wednesday, February 10, 2021, Konrad A. Fögen presented his doctoral thesis on the topic “Combinatorial Robustness Testing based on Error-Constraints” and successfully passed the doctoral examination!
In this talk, we present an extension to combinatorial testing (CT) which is an effective specification-based test method that is based on an input parameter model (IPM). We argue that robustness is an important property of a software, which must be tested in addition to a software’s functionality. This requires invalid values and invalid value combinations to be able to observe a software’s reaction to them. However, the effectiveness of CT deteriorates in the presence of invalid values or invalid value combinations. This phenomenon is called invalid input masking effect and is already acknowledged in some research. It led to extensions of CT that we call combinatorial robustness testing (CRT). The objective of CRT is to improve the fault detection by avoiding invalid input masking. This is achieved by separating the testing of valid values and valid value combinations from the testing of invalid values and invalid value combinations. While CRT is a promising extension of CT, it is still insufficiently researched. For instance, in related work, IPMs are extended with additional semantic information to specify invalid values. However, invalid value combinations cannot be specified directly. Therefore, the objective of this work is to further expand the idea of CRT. The aim is to develop a new CRT test method with a modeling approach to specify invalid values and invalid value combinations equally well. This modeling approach should also be incorporated into explicit test adequate criteria and test selection strategies. Furthermore, this modeling approach shall be supported by automated techniques. First, we conduct a controlled experiment to check if CRT is necessary at all or if CT is already appropriate to test robustness. Based on the result, we continue and develop a refined t-factor fault model that incorporates robustness faults and the inherent invalid input masking effect. Next, we develop a new test method for CRT and introduce a new structure that extends the structure of IPMs. It is called robustness input parameter model (RIPM) and contains the concept of error-constraints which is an additional set of logical expressions to describe the validity of values and value combinations. With the refined t-factor fault model and the new RIPM structure, new test adequacy criteria that incorporate the additional semantic information and new test selection strategies that satisfy the test adequacy criteria are developed. The new concept of error-constraints requires additional effort in modeling. Therefore, we develop two techniques to support the modeling of them. First, we develop a technique to identify and repair inconsistencies among error-constraints. Second, we develop a technique to automatically generate error-constraints based on the conformance to another system. Last but not least, all aforementioned concepts and techniques are operationalized and integrated in a test automation framework which includes a process, an architecture, and a Java-based reference implementation.