University Blockchain Research Initiative

Annibale Panichella, Mitchell Olsthoorn
Last updated on Aug 15, 2021
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Ripple - University Blockchain Research Initiative (UBRI)

UBRI is a partnership between Ripple and top universities around the world to support academic research, technical development and innovation in blockchain, cryptocurrency, and digital payments. Ripple is providing both financial and technical resources to university partners and collaborates with faculty and students on research and technical projects.

Mitchell Olsthoorn
Mitchell Olsthoorn
Assistant Professor

Mitchell Olsthoorn is an Assistant Professor researcher in the Software Engineering Research Group (SERG) at Delft University of Technology. He is also a member of the Computational Intelligence for Software Engineering lab (CISELab) and the Blockchain lab. Mitchell holds an Ph.D. degree in Computer Science – with a specialization in Computational Intelligence.

Publications

Guess What: Test Case Generation for Javascript with Unsupervised Probabilistic Type Inference
Search-based test case generation approaches make use of static type information to determine which data types should be used for the …
Dimitri Stallenberg, Mitchell Olsthoorn, Annibale Panichella
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Guiding Automated Test Case Generation for Transaction-Reverting Statements in Smart Contracts
Transaction-reverting statements are key constructs within Solidity that are extensively used for authority and validity checks. …
Mitchell Olsthoorn, Arie van Deursen, Annibale Panichella
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SynTest-Solidity: Automated Test Case Generation and Fuzzing for Smart Contracts
Ethereum is the largest and most prominent smart contract platform. One key property of Ethereum is that once a contract is deployed, …
Mitchell Olsthoorn, Dimitri Stallenberg, Arie van Deursen, Annibale Panichella
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More Effective Test Case Generation with Multiple Tribes of AI
Software testing is a critical activity in the software development life cycle for quality assurance. Automated Test Case Generation …
Mitchell Olsthoorn
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Hybrid Multi-level Crossover for Unit Test Case Generation
State-of-the-art search-based approaches for test case generation work at test case level, where tests are represented as sequences of …
Mitchell Olsthoorn, Pouria Derakhshanfar, Annibale Panichella
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Improving Test Case Generation for REST APIs Through Hierarchical Clustering
With the ever-increasing use of web APIs in modernday applications, it is becoming more important to test the system as a whole. In the …
Dimitri Stallenberg, Mitchell Olsthoorn, Annibale Panichella
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Multi-objective Test Case Selection Through Linkage Learning-driven Crossover
Test case selection (TCS) aims to select a subset of the test suite to run for regression testing. The selection is typically based on …
Mitchell Olsthoorn, Annibale Panichella
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Generating Highly-structured Input Data by Combining Search-based Testing and Grammar-based Fuzzing
Software testing is an important and time-consuming task that is often done manually. In the last decades, researchers have come up …
Mitchell Olsthoorn, Arie van Deursen, Annibale Panichella
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An Application of Model Seeding to Search-Based Unit Test Generation for Gson
Model seeding is a strategy for injecting additional information in a search-based test generation process in the form of models, …
Mitchell Olsthoorn, Pouria Derakhshanfar, Xavier Devroey
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