@conference {401,
	title = {Space Explanations of Neural Network Classification},
	booktitle = {37th CAV 2025},
	year = {2025},
	abstract = {We present a novel logic-based concept called Space Explanations for classifying neural networks that gives provable guarantees of the behavior of the network in continuous areas of the input feature space. To automatically generate space explanations, we leverage on a range of flexible Craig interpolation algorithms and unsatisfiable core generation.
Based on real-life case studies, ranging from small to medium to large size, we demonstrate that the generated explanations are more meaningful than those computed by the state-of-the-art},
	author = {Faezeh Labbaf and Tom{\'a}{\v s} Kol{\'a}rik and Martin Blicha and Grigory Fedyukovich and Michael Wand and Natasha Sharygina}
}
@article {379,
	title = {SMT-based verification of program changes through summary repair},
	journal = {Formal Methods in System Design},
	year = {2023},
	month = {05/2023},
	abstract = {This article provides an innovative approach for verification by model checking of programs that undergo continuous changes. To tackle the problem of repeating the entire model checking for each new version of the program, our approach verifies programs incrementally. It reuses computational history of the previous program version, namely function summaries. In particular, the summaries are over-approximations of the bounded program behaviors. Whenever reusing of summaries is not possible straight away, our algorithm repairs the summaries to maximize the chance of reusability of them for subsequent runs. We base our approach on satisfiability modulo theories (SMT) to take full advantage of lightweight modeling approach and at the same time the ability to provide concise function summarization. Our approach leverages pre-computed function summaries in SMT to localize the checks of changed functions. Furthermore, to exploit the trade-off between precision and performance, our approach relies on the use of an SMT solver, not only for underlying reasoning, but also for program modeling and the adjustment of its precision. On the benchmark suite of primarily Linux device drivers versions, we demonstrate that our algorithm achieves an order of magnitude speedup compared to prior approaches.},
	doi = {https://doi.org/10.1007/s10703-023-00423-0},
	url = {https://link.springer.com/epdf/10.1007/s10703-023-00423-0?sharing_token=irB5EyKrDQwFBGsATR5X_Pe4RwlQNchNByi7wbcMAY69DCBPoCd5OukXnJUT4hJ-i8lTSfPkBgFCDWhP5zZ6F07I66RayboKJEpVSax8y-1gkPqsTej9UbMHSNiNQ_jERujVnNQQ7kvxuZcpsB3rGMYcHJEINXClhcP3Ttz85V4=},
	author = {Sepideh Asadi and Martin Blicha and Antti E. J. Hyv{\"a}rinen and Grigory Fedyukovich and Natasha Sharygina}
}
@conference {369,
	title = {SolCMC: Solidity Compiler{\textquoteright}s Model Checker},
	booktitle = {CAV},
	year = {2022},
	address = { Haifa, Isreal},
	abstract = {<p>Formally verifying smart contracts is important due to their immutable nature, usual open source licenses, and high financial incentives for exploits. Since 2019 the Ethereum Foundation{\textquoteright}s Solidity compiler ships with a model checker. The checker, called SolCMC, has two different reasoning engines and tracks closely the development of the Solidity language. We describe SolCMC{\textquoteright}s architecture and use from the perspective of developers of both smart contracts and tools for software verification, and show how to analyze nontrivial properties of real life contracts in a fully automated manner.</p>
},
	keywords = {SolCMC},
	author = {Leonardo Alt and Martin Blicha and Antti E. J. Hyv{\"a}rinen and Natasha Sharygina}
}
@conference {372,
	title = {Split Transition Power Abstraction for Unbounded Safety},
	year = {2022},
	abstract = {<p>Transition Power Abstraction (TPA) is a recent sym- bolic model checking approach that leverages Craig interpolation to create a sequence of symbolic abstractions for transition paths that double in length with each new element. This doubling abstraction allows the approach to find bugs that require long executions much faster than traditional approaches that unfold transitions one at a time, but its ability to prove system safety is limited. This paper proposes a novel instantiation of the TPA approach capable of proving unbounded safety efficiently while preserving the unique capability to detect deep counterexamples. The idea is to split the transition over-approximations in two complementary parts. One part focuses only on reachability in fixed number of steps, the second part complements it by summarizing all shorter paths. The resulting split abstractions are suitable for discovering safe transition invariants, making the SPLIT-TPA approach much more efficient in proving safety and even improving the counterexample detection. The approach is implemented in the constrained Horn clause solver GOLEM and our experimental comparison against state-of-the-art solvers shows it to be both competitive and complementary.</p>
},
	author = {Martin Blicha and Grigory Fedyukovich and Antti E. J. Hyv{\"a}rinen and Natasha Sharygina}
}
