Linear-time temporal logic guided greybox fuzzing

R Meng, Z Dong, J Li, I Beschastnikh… - Proceedings of the 44th …, 2022 - dl.acm.org
Software model checking as well as runtime verification are verification techniques which
are widely used for checking temporal properties of software systems. Even though they are …

An interview study of how developers use execution logs in embedded software engineering

N Yang, P Cuijpers, R Schiffelers… - 2021 IEEE/ACM …, 2021 - ieeexplore.ieee.org
Execution logs capture the run-time behavior of software systems. To assist developers in
their maintenance tasks, many studies have proposed tools to analyze execution information …

An interview study about the use of logs in embedded software engineering

N Yang, P Cuijpers, D Hendriks, R Schiffelers… - Empirical Software …, 2023 - Springer
Context Execution logs capture the run-time behavior of software systems. To assist
developers in their maintenance tasks, many studies have proposed tools to analyze …

Model-driven system-performance engineering for cyber-physical systems

B Van der Sanden, Y Li, J van den Aker… - Proceedings of the …, 2021 - dl.acm.org
System-Performance Engineering (SysPE) encompasses modeling formalisms, methods,
techniques, and industrial practices to design systems for performance, where performance …

Adaptive behavioral model learning for software product lines

S Tavassoli, CDN Damasceno, R Khosravi… - Proceedings of the 26th …, 2022 - dl.acm.org
Behavioral models enable the analysis of the functionality of software product lines (SPL),
eg, model checking and model-based testing. Model learning aims to construct behavioral …

[图书][B] RERS 2019: combining synthesis with real-world models

M Jasper, M Mues, A Murtovi, M Schlüter, F Howar… - 2019 - Springer
This paper covers the Rigorous Examination of Reactive Systems (RERS) Challenge 2019.
For the first time in the history of RERS, the challenge features industrial tracks where …

[PDF][PDF] Constructive Model Inference: Model Learning for Component-based Software Architectures.

B Hooimeijer, M Geilen, JF Groote, D Hendriks… - ICSOFT, 2022 - publications.tno.nl
Model learning, learning a state machine from software, can be an effective model-based
engineering technique, especially to understand legacy software. However, so far the …

[HTML][HTML] Interface protocol inference to aid understanding legacy software components

K Aslam, L Cleophas, R Schiffelers… - Software and Systems …, 2020 - Springer
High-tech companies are struggling today with the maintenance of legacy software. Legacy
software is vital to many organizations as it contains the important business logic. To …

A systematic approach for interfacing component-based software with an active automata learning tool

D Hendriks, K Aslam - … Symposium on Leveraging Applications of Formal …, 2022 - Springer
Abstract Applying Model-Driven Engineering can improve development efficiency. But
gaining such benefits for legacy software requires models, and creating them manually is …

[HTML][HTML] Small test suites for active automata learning

L Kruger, S Junges, J Rot - … Conference on Tools and Algorithms for the …, 2024 - Springer
A bottleneck in modern active automata learning is to test whether a hypothesized Mealy
machine correctly describes the system under learning. The search space for possible …