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Model-Based Systems Engineering (MBSE) is a development approach aiming to build correct-by-construction systems, provided the use of clear, unambiguous and complete models to describe them along the design process. The approach is…

Software Engineering · Computer Science 2021-11-22 I Dragomir , M Bozga , Iulian Ober , D Silveira , T Jorge , E Alaña , M Perrotin

The C Bounded Model Checker (CBMC) demonstrates the violation of assertions in C programs, or proves safety of the assertions under a given bound. CBMC implements a bit-precise translation of an input C program, annotated with assertions…

Software Engineering · Computer Science 2023-02-07 Daniel Kroening , Peter Schrammel , Michael Tautschnig

Bayesian optimization is a powerful method for automating tuning of compilers. The complex landscape of autotuning provides a myriad of rarely considered structural challenges for black-box optimizers, and the lack of standardized…

Machine Learning · Computer Science 2025-04-09 Jacob O. Tørring , Carl Hvarfner , Luigi Nardi , Magnus Själander

Through international regulations (most prominently the latest UNECE regulation) and standards, the already widely perceived higher need for cybersecurity in automotive systems has been recognized and will mandate higher efforts for…

Cryptography and Security · Computer Science 2021-09-07 Stefan Marksteiner , Peter Priller

Black-box tuning has attracted recent attention due to that the structure or inner parameters of advanced proprietary models are not accessible. Proxy-tuning provides a test-time output adjustment for tuning black-box language models. It…

Machine Learning · Computer Science 2024-07-02 Yuanyang He , Zitong Huang , Xinxing Xu , Rick Siow Mong Goh , Salman Khan , Wangmeng Zuo , Yong Liu , Chun-Mei Feng

Self-testing refers to the fact that, in some quantum devices, both states and measurements can be assessed in a black-box scenario, on the sole basis of the observed statistics, i.e. without reference to any prior device calibration. Only…

This article proposes a test procedure that can be used to test ML models and ML-based systems independently of the actual training process. In this way, the typical quality statements such as accuracy and precision of these models and…

Machine Learning · Computer Science 2024-06-21 Hans-Werner Wiesbrock , Jürgen Großmann

We introduce a model-checking tool intended specially for the analysis of quantum information protocols. The tool incorporates an efficient representation of a certain class of quantum circuits, namely those expressible in the so-called…

Quantum Physics · Physics 2008-04-21 Simon Gay , Rajagopal Nagarajan , Nikolaos Papanikolaou

Cyber-physical systems (CPSs) are widespread in critical domains, and significant damage can be caused if an attacker is able to modify the code of their programmable logic controllers (PLCs). Unfortunately, traditional techniques for…

Cryptography and Security · Computer Science 2021-08-24 Yuqi Chen , Christopher M. Poskitt , Jun Sun

Prediction systems are successfully deployed in applications ranging from disease diagnosis, to predicting credit worthiness, to image recognition. Even when the overall accuracy is high, these systems may exhibit systematic biases that…

Machine Learning · Computer Science 2018-08-30 Michael P. Kim , Amirata Ghorbani , James Zou

We propose a novel methodology for validating software product line (PL) models by integrating Statistical Model Checking (SMC) with Process Mining (PM). Our approach focuses on the feature-oriented language QFLan in the PL engineering…

Software Engineering · Computer Science 2024-01-25 Roberto Casaluce , Andrea Burattin , Francesca Chiaromonte , Alberto Lluch Lafuente , Andrea Vandin

Background: Explainability in phishing detection model can support a further solution of phishing attack mitigation by increasing trust and understanding how phishing can be detected. Objective: The aims of this study to determine and best…

Cryptography and Security · Computer Science 2024-12-04 Abdullah Fajar , Setiadi Yazid , Indra Budi

Model checking and testing are two areas with a similar goal: to verify that a system satisfies a property. They start with different hypothesis on the systems and develop many techniques with different notions of approximation, when an…

Logic in Computer Science · Computer Science 2013-04-19 M. C. Gaudel , R. Lassaigne , F. Magniez , M. de Rougemont

The widespread adoption of complex machine learning models in high-stakes domains has brought the "black-box" problem to the forefront of responsible AI research. This paper aims at addressing this issue by improving the Explainable…

Machine Learning · Computer Science 2025-12-02 Isara Liyanage , Uthayasanker Thayasivam

The quality and correct functioning of software components embedded in electronic systems are of utmost concern especially for safety and mission-critical systems. Model-based testing and formal verification techniques can be employed to…

Formal Languages and Automata Theory · Computer Science 2019-01-08 Shahbaz Ali , Hailong Sun , Yongwang Zhao

Computer models are widely used to study complex real world physical systems. However, there are major limitations to their direct use including: their complex structure; large numbers of inputs and outputs; and long evaluation times.…

Methodology · Statistics 2025-05-05 Jonathan Owen , Ian Vernon

Conformance checking is a set of process mining functions that compare process instances with a given process model. It identifies deviations between the process instances' actual behaviour ("as-is") and its modelled behaviour ("to-be").…

Software Engineering · Computer Science 2020-07-22 Sebastian Dunzer , Matthias Stierle , Martin Matzner , Stephan Baier

The public collider phenomenology computing tool CheckMATE (Check Models at Terascale Energies) was originally designed to allow theorists to quickly test their favourite BSM models against various existing LHC analyses performed by ATLAS…

High Energy Physics - Phenomenology · Physics 2018-01-25 Daniel Dercks , Gudrid Moortgat-Pick

Simulation-based calibration checking (SBC) is a practical method to validate computationally-derived posterior distributions or their approximations. In this paper, we introduce a new variant of SBC to alleviate several known problems. Our…

Benchmarking is essential for developing and evaluating black-box optimization algorithms, providing a structured means to analyze their search behavior. Its effectiveness relies on carefully selected problem sets used for evaluation. To…

Neural and Evolutionary Computing · Computer Science 2025-11-17 Iván Olarte Rodríguez , Maria Laura Santoni , Fabian Duddeck , Carola Doerr , Thomas Bäck , Elena Raponi