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Bounded model finding is a key technique for validating software designs, usually obtained by translating high-level specifications into SAT/SMT problems. Although effective, such translations introduce a semantic gap and a dependency on…

Logic in Computer Science · Computer Science 2026-03-24 Artur Boronat

Hyperproperties are system properties that require quantification over multiple execution traces of a system. Hyperproperties can express several specifications of interest for cyber-physical systems--such as opacity, robustness, and…

Systems and Control · Electrical Eng. & Systems 2021-11-24 Mahathi Anand , Vishnu Murali , Ashutosh Trivedi , Majid Zamani

The Best Estimate plus Uncertainty (BEPU) approach for nuclear systems modeling and simulation requires that the prediction uncertainty must be quantified in order to prove that the investigated design stays within acceptance criteria. A…

Computation · Statistics 2023-03-24 Ziyu Xie , Farah Alsafadi , Xu Wu

Quantum Machine Learning (QML) offers a new paradigm for addressing complex financial problems intractable for classical methods. This work specifically tackles the challenge of few-shot credit risk assessment, a critical issue in inclusive…

Automated test case generation tools help businesses to write tests and increase the safety net provided by high regression test coverage when making code changes. Test generation needs to cover as much as possible of the uncovered code…

Software Engineering · Computer Science 2023-01-02 Matthias Güdemann , Peter Schrammel

For the first time, we enable the execution of hybrid machine learning methods on real quantum computers with 100 data samples and real-device-based simulations with 5,000 data samples, thereby outperforming the current state of research of…

In the context of a large software testing company, we have deployed the model-based testing (MBT) approach to take the company's test automation practices to higher levels of maturity /and capability. We have chosen, from a set of…

Software Engineering · Computer Science 2021-04-07 Vahid Garousi , Alper Buğra Keleş , Yunus Balaman , Zeynep Özdemir Güler , Andrea Arcuri

Massive data analysis becomes increasingly prevalent, subsampling methods like BLB (Bag of Little Bootstraps) serves as powerful tools for assessing the quality of estimators for massive data. However, the performance of the subsampling…

Methodology · Statistics 2022-01-14 Yingying Ma , Hansheng Wang

When implementing model predictive control (MPC) for hybrid systems with a linear or a quadratic performance measure, a mixed-integer linear program (MILP) or a mixed-integer quadratic program (MIQP) needs to be solved, respectively, at…

Systems and Control · Electrical Eng. & Systems 2025-04-11 Shamisa Shoja , Daniel Arnström , Daniel Axehill

Superconducting circuits have demonstrated significant potential in quantum information processing and quantum sensing. Implementing novel control and measurement sequences for superconducting qubits is often a complex and time-consuming…

ML models are increasingly being used to increase the test coverage and decrease the overall testing time. This field is still in its nascent stage and up till now there were no algorithms that could match or outperform commercial tools in…

Machine Learning · Computer Science 2023-08-08 Shruti Pandey , Jayadeva , Smruti R. Sarangi

Bounded Model Checking is one the most successful techniques for finding bugs in program. However, model checkers are resource hungry and are often unable to verify programs with loops iterating over large arrays.We present a transformation…

Logic in Computer Science · Computer Science 2017-03-08 Anushri Jana , Uday P. Khedker , Advaita Datar , R Venkatesh , C Niyas

The analysis of formal models that include quantitative aspects such as timing or probabilistic choices is performed by quantitative verification tools. Broad and mature tool support is available for computing basic properties such as…

The fragmented landscape of quantum computer benchmarks, characterized by system-specific tools and inconsistent evaluation methodologies, hinders reliable cross-platform performance assessment. We introduce Metriq, an open-source…

Recent advancements in test time compute, particularly through the use of verifier models, have significantly enhanced the reasoning capabilities of Large Language Models (LLMs). This generator-verifier approach closely resembles the…

Machine Learning · Computer Science 2024-10-11 Jianing Qi , Hao Tang , Zhigang Zhu

We present a predictive feedback control method for a class of quasilinear hyperbolic systems with one boundary control input. Assuming exact model knowledge, convergence to the origin, or tracking at the uncontrolled boundary, are achieved…

Optimization and Control · Mathematics 2022-03-18 Timm Strecker , Ole Morten Aamo , Michael Cantoni

In the literature on hyper-parameter tuning, a number of recent solutions rely on low-fidelity observations (e.g., training with sub-sampled datasets) in order to efficiently identify promising configurations to be then tested via…

Machine Learning · Computer Science 2022-12-05 Pedro Mendes , Maria Casimiro , Paolo Romano , David Garlan

Checking for Non-Termination (NT) of a given program P, i.e., determining if P has at least one non-terminating run, is an undecidable problem that continues to garner significant research attention. While unintended NT is common in…

Software Engineering · Computer Science 2024-09-23 Ravindra Metta , Hrishikesh Karmarkar , Kumar Madhukar , R Venkatesh , Supratik Chakraborty , Samarjit Chakraborty

Bayesian model comparison (BMC) offers a principled approach for assessing the relative merits of competing computational models and propagating uncertainty into model selection decisions. However, BMC is often intractable for the popular…

Machine Learning · Statistics 2023-11-27 Lasse Elsemüller , Martin Schnuerch , Paul-Christian Bürkner , Stefan T. Radev

Recent work in network quantization produced state-of-the-art results using mixed precision quantization. An imperative requirement for many efficient edge device hardware implementations is that their quantizers are uniform and with…

Machine Learning · Computer Science 2020-07-21 Hai Victor Habi , Roy H. Jennings , Arnon Netzer