Hadi Hemmati

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Metaheuristic search techniques have been extensively used to automate the process of generating test cases, and thus providing solutions for a more cost-effective testing process. This approach to test automation, often coined “Search-based Software Testing” (SBST), has been used for a wide variety of test case generation purposes. Since SBST(More)
The increase in size and complexity of modern software systems requires scalable, systematic, and automated testing approaches. Model-based testing (MBT), as a systematic and automated test case generation technique, is being successfully applied to verify industrial-scale systems and is supported by commercial tools. However, scalability is still an open(More)
Model-based robustness testing requires precise and complete behavioral, robustness modeling. For example, state machines can be used to model software behavior when hardware (e.g., sensors) breaks down and be fed to a tool to automate test case generation. But robustness behavior is a crosscutting behavior and, if modeled directly, often results in large,(More)
Model-based testing (MBT) suffers from two main problems which in many real world systems make MBT impractical: scalability and automatic oracle generation. When no automated oracle is available, or when testing must be performed on actual hardware or a restricted-access network, for example, only a small set of test cases can be executed and evaluated.(More)
Big data analytics is the process of examining large amounts of data (big data) in an effort to uncover hidden patterns or unknown correlations. Big Data Analytics Applications (BDA Apps) are a new type of software applications, which analyze big data using massive parallel processing frameworks (e.g., Hadoop). Developers of such applications typically(More)
In recent years, Model-Based Testing (MBT) has attracted an increasingly wide interest from industry and academia. MBT allows automatic generation of a large and comprehensive set of test cases from system models (e.g., state machines), which leads to the systematic testing of the system. However, even when using simple test strategies, applying MBT in(More)
Software development teams use test suites to test changes to their source code. In many situations, the test suites are so large that executing every test for every source code change is infeasible, due to time and resource constraints. Development teams need to prioritize their test suite so that as many distinct faults as possible are detected early in(More)
Applying model-based testing (MBT) in practice requires practical solutions for scaling up to large industrial systems. One challenge that we have faced while applying MBT was the generation of test suites that were too large to be practical, even for simple coverage criteria. The goal of test case selection techniques is to select a subset of the generated(More)
Our experience with applying model-based testing on industrial systems showed that the generated test suites are often too large and costly to execute given project deadlines and the limited resources for system testing on real platforms. In such industrial contexts, it is often the case that only a small subset of test cases can be run. In previous work,(More)
The Mining Software Repositories (MSR) research community has grown significantly since the first MSR workshop was held in 2004. As the community continues to broaden its scope and deepens its expertise, it is worthwhile to reflect on the best practices that our community has developed over the past decade of research. We identify these best practices by(More)