Michael Mlynarski

From design models to test models by means of test ideas

Model-Based Testing is slowly becoming the next level of software testing. It promises higher quality, better coverage and efficient change management. MBT shows two main problems of modeling the test behavior. While modeling test cases test designers rewrite most of the system specification. Further, the number of test cases generated by modern tools is often not feasible. In practice, both problems are not solved. Assuming that the functional design is based on models, we show how to use them for software testing. With so-called test ideas, we propose a way to manually select and automatically transform the relevant parts of the design model into a basic test model that can be used for test case generation. We give an example and discuss the potentials for tool support.

Model-Based System Testing Using Visual Contracts

In system testing the system under test (SUT) is tested against high-level requirements which are captured at early phases of the development process. Logical test cases developed from these requirements must be translated to executable test cases by augmenting them with implementation details. If manually done these activities are error-prone and tedious. In this paper we introduce a model-based approach for system testing where we generate first logical test cases from use case diagrams which are partially formalized by visual contracts, and then we transform these to executable test cases using model transformation. We derive model transformation rules from the design decisions of developers.

Holistic Model-Based Testing for Business Information Systems

Growing complexity of today’s software development requires new and better techniques in software testing. A promising one seems to be model-based testing. The goal is to automatically generate test artefacts from models, improve test coverage and guarantee traceability. Typical problems are missing reuse of design models and test case explosion. Our research work aims to find a solution for the mentioned problems in the area of UML and Business Information Systems. We use model transformations to automatically generate test models from manually annotated design models using a holistic view. In this paper we define and justify the research problem and present first results.

KnowledgeBus: an architecture to support intelligent and flexible knowledge management

MoKEx (Mobile Knowledge Experience) is an international project series focusing on actual challenges in knowledge management and e-learning. The project series is in cooperation with universities and industrial partners in Germany and Switzerland and links communities of practice with the innovative approaches of learning communities. As a result of the recent execution of the project, an architecture was developed that supports the flexible connection of various independent knowledge systems via the so-called KnowledgeBus. This paper introduces the concept of Single Point of Information (SPI) and the KnowledgeBus itself.

Effort Comparison for Model-Based Testing Scenarios

In the literature of model-based testing (MBT), different testing scenarios are introduced. These scenarios mainly differ in the origin and content of test models which has an impact on testing activities. For example, if developers models are directly used as test models, the efforts for test model creation will be low, however the evaluation of test results will need more efforts [2]. We investigated the differences of MBT scenarios from a test managers point of view trying to answer the following questions: Which efforts must be calculated when applying the different MBT scenarios? Can we systematically analyze and compare the different scenarios in the literature? For answering these questions we propose a GQM-based approach where we systematically define metrics for characterizing and comparing MBT scenarios.