Distributed Systems Testing

建议的研究重点是基于模型的测试框架，称为“假设-保证-推断”。与基于模型的测试一样，在框架中，起点是被测系统（SUT）的预期行为模型。然而，与大多数现有的方法不同，本研究的目标是考虑不一定完整和精确的模型。一个模型的不完整性是指对被测系统的预期行为缺乏了解;而不精确性可能来自可选行为或对实际行为的过度抽象，其中包括不可行的执行，通常是不确定的。测试人员假设的实现故障在SUT在手，然后正式的形式，一些故障模型。如果检测到故障，测试执行结果可能导致测试人员修改初始SUT模型或SUT本身。一旦修正的SUT通过了所有执行的测试，后者可以帮助改进SUT的模型，即，推断出更完整和精确的模型。需要一个完善的模型来更好地记录测试系统，并在需要时生成额外的测试，以提高系统质量的置信度。这一步完成了假设-保证-推断测试框架。 所提出的研究的意义在于提高水平的自动化测试活动，可以实现基于假设-保证-推断测试框架和更广泛的接受正式的方法来测试，因为在他们的应用程序的主要障碍，一个完整的和精确的SUT模型的可用性可以显着减少允许不完整和不精确的模型。

The proposed research focuses on a model-based testing framework, called "Assume-Guarantee-Infer". As usual for model-based testing, in the framework, the starting point is a model of the expected behaviour of a system under test (SUT). However, differently from the most of the existing approaches, the goal of this research is to consider models which are not necessarily complete and precise. Incompleteness of a model is implied by partiality of knowledge about the expected behaviour of a system under test; while impreciseness may come from optional behaviours or over-abstraction of the actual behaviour which includes infeasible executions and is usually nondeterministic. The tester assumptions about implementation faults in an SUT at hand are then formalized in the form of some fault model. Test execution results may lead the tester to modify either the initial SUT model or the SUT itself if faults are detected. Once the rectified SUT passes all the executed tests the latter can help refine the model of the SUT, i.e., infer a more complete and precise model. A refined model is needed to better document the tested system and to generate if required additional tests increasing the level of the confidence in the quality of the system. This step completes the Assume-Guarantee-Infer testing framework. The significance of the proposed research lies in an increased level of automation of testing activities which can be achieved based on the Assume-Guarantee-Infer testing framework and in a wider acceptance of formal approaches to testing, since the main hurdle in their application, the availability of a complete and precise SUT model can significantly be reduced by allowing incomplete and imprecise models.