Related papers: Future-based Static Analysis of Message Passing Pr…
This paper explores the potential of communicating information gained by static analysis from compilers to Out-of-Order (OoO) machines, focusing on the memory dependence predictor (MDP). The MDP enables loads to issue without all in-flight…
State of the art analyzers in the Logic Programming (LP) paradigm are nowadays mature and sophisticated. They allow inferring a wide variety of global properties including termination, bounds on resource consumption, etc. The aim of this…
As Large Language Models become integral to software development, with substantial portions of AI-suggested code entering production, understanding their internal correctness mechanisms becomes critical for safe deployment. We apply sparse…
The Message Passing Interface (MPI) is a fundamental tool for building high-performance computing (HPC) applications, enabling efficient communication across distributed systems. Despite its widespread adoption, MPI's low-level interface…
Model predictive control (MPC) is a de facto standard control algorithm across the process industries. There remain, however, applications where MPC is impractical because an optimization problem is solved at each time step. We present a…
In this paper bounded model checking of asynchronous concurrent systems is introduced as a promising application area for answer set programming. As the model of asynchronous systems a generalisation of communicating automata, 1-safe Petri…
Communication fabrics play a key role in the correctness and performance of modern multi-core processors and systems-on-chip. To enable formal verification, a recent trend is to use high-level micro-architectural models to capture…
The increasing deployment of advanced digital technologies such as Internet of Things (IoT) devices and Cyber-Physical Systems (CPS) in industrial environments is enabling the productive use of machine learning (ML) algorithms in the…
A Metric Interval Temporal Logic (MITL) verification algorithm is presented. It verifies continuous-time signals without relying on high frequency sampling. Instead, it is assumed that collections of over- and under-approximating intervals…
The use of behavioural contracts, to specify, regulate and verify systems, is particularly relevant to runtime monitoring of distributed systems. System distribution poses major challenges to contract monitoring, from monitoring-induced…
Many of today's message-passing systems not only require messages to be exchanged in a certain order but also to happen at a certain \emph{time} or within a certain \emph{time window}. Such correctness conditions are particularly prominent…
This paper consider the problem of determining the reliability of a software system which can be decomposed in a number of modules. We have derived the expression of the reliability of a system using the Markovian model for the transfer of…
Distributed systems have become increasingly prevalent in the software industry. Due to their intrinsic complexity, much research has focused on the verification of their behaviour. An active research line is around behaviour models that…
This paper systematizes knowledge on the performance of Multi-Party Computation (MPC) protocols. Despite strong privacy and correctness guarantees, MPC adoption in real-world applications remains limited by high costs (especially in the…
Runtime Verification deals with the question of whether a run of a system adheres to its specification. This paper studies runtime verification in the presence of partial knowledge about the observed run, particularly where input values may…
Machine learning (ML) systems are increasingly deployed in high-stakes domains where reliability is paramount. This thesis investigates how uncertainty estimation can enhance the safety and trustworthiness of ML, focusing on selective…
This paper presents a novel two-level control architecture for a fully autonomous vehicle in a deterministic environment, which can handle traffic rules as specifications and low-level vehicle control with real-time performance. At the top…
Machine learning (ML) models deployed in many safety- and business-critical systems are vulnerable to exploitation through adversarial examples. A large body of academic research has thoroughly explored the causes of these blind spots,…
As data-driven intelligent systems advance, the need for reliable and transparent decision-making mechanisms has become increasingly important. Therefore, it is essential to integrate uncertainty quantification and model explainability…
This paper presents a lightweight formalism (a trace) to model message-passing concurrent executions where some common common problems can be identified, like lost or delayed messages, some forms of deadlock, etc. In particular, we consider…