Related papers: Data-centric Dynamic Partial Order Reduction
A dynamic partial order reduction (DPOR) algorithm is optimal when it always explores at most one representative per Mazurkiewicz trace. Existing literature suggests that the reduction obtained by the non-optimal, state-of-the-art…
The verification of concurrent programs remains an open challenge, as thread interaction has to be accounted for, which leads to state-space explosion. Stateless model checking battles this problem by exploring traces rather than states of…
Program executions under relaxed memory model (rmm) semantics are significantly more difficult to analyze; the rmm semantics result in out of order execution of program events leading to an explosion of state-space. Dynamic partial order…
Stateless model checking is a fully automatic verification technique for concurrent programs that checks for safety violations by exploring all possible thread schedulings. It becomes effective when coupled with Dynamic Partial Order…
Event-driven architectures are broadly used for systems that must respond to events in the real world. Event-driven applications are prone to concurrency bugs that involve subtle errors in reasoning about the ordering of events.…
Partial order reduction (POR) and net unfoldings are two alternative methods to tackle state-space explosion caused by concurrency. In this paper, we propose the combination of both approaches in an effort to combine their strengths. We…
Assessing the correctness of distributed and parallel applications is notoriously difficult due to the complexity of the concurrent behaviors and the difficulty to reproduce bugs. In this context, Dynamic Partial Order Reduction (DPOR)…
We study the estimation problem for concurrent programs: given a bounded program $P$, estimate the number of Mazurkiewicz trace-equivalence classes induced by its interleavings. This quantity informs two practical questions for…
Event-driven multi-threaded programming is an important idiom for structuring concurrent computations. Stateless Model Checking (SMC) is an effective verification technique for multi-threaded programs, especially when coupled with Dynamic…
Event-driven multi-threaded programming is fast becoming a preferred style of developing efficient and responsive applications. In this concurrency model, multiple threads execute concurrently, communicating through shared objects as well…
Partial order reduction (POR) is a classic technique for dealing with the state explosion problem in model checking of concurrent programs. Theoretical optimality, i.e., avoiding enumerating equivalent interleavings, does not necessarily…
Formal methods have proved effective to automatically analyze protocols. Over the past years, much research has focused on verifying trace equivalence on protocols, which is notably used to model many interesting privacy properties, e.g.,…
Stateless Model Checking (SMC) is a verification technique for concurrent programs that checks for safety violations by exploring all possible thread schedulings. It is highly effective when coupled with Dynamic Partial Order Reduction…
State-space reduction techniques, used primarily in model-checkers, all rely on the idea that some actions are independent, hence could be taken in any (respective) order while put in parallel, without changing the semantics. It is thus not…
Deadlocks are a major source of bugs in concurrent programs. They are hard to predict, because they may only occur under specific scheduling conditions. Dynamic analysis attempts to identify potential deadlocks by examining a single…
Modern applications, such as social networking systems and e-commerce platforms are centered around using large-scale databases for storing and retrieving data. Accesses to the database are typically enclosed in transactions that allow…
Piecewise-linear nonlinear systems appear in many engineering disciplines. Prediction of the dynamic behavior of such systems is of great importance from practical and theoretical viewpoint. In this paper, a data-driven model order…
Runtime predictive analyses enhance coverage of traditional dynamic analyses based bug detection techniques by identifying a space of feasible reorderings of the observed execution and determining if any of these witnesses the violation of…
Deep Reinforcement Learning (DRL) has made considerable advances in simulated and physical robot control tasks, especially when problems admit a fully observed Markov Decision Process (MDP) formulation. When observations only partially…
We address the problem of reasoning about interleavings in safety verification of concurrent programs. In the literature, there are two prominent techniques for pruning the search space. First, there are well-investigated trace-based…