Related papers: Data Race Satisfiability on Array Elements
The high degree of parallelism and relatively complicated synchronization mechanisms in GPUs make writing correct kernels difficult. Data races pose one such concurrency correctness challenge, and therefore, effective methods of detecting…
Raft is a leader-based consensus algorithm that implements State Machine Replication (SMR), which replicates the service state across multiple servers to enhance fault tolerance. In Raft, the servers play one of three roles: leader,…
RacerD is a static race detector that has been proven to be effective in engineering practice: it has seen thousands of data races fixed by developers before reaching production, and has supported the migration of Facebook's Android app…
We use static object data to improve success detection for stacking objects on and nesting objects in one another. Such actions are necessary for certain robotics tasks, e.g., clearing a dining table or packing a warehouse bin. However,…
Data-flow testing (DFT) aims to detect potential data interaction anomalies by focusing on the points at which variables receive values and the points at which these values are used. Such test objectives are referred as \emph{def-use…
As concurrent programming becomes increasingly prevalent, effectively identifying and addressing concurrency issues such as data races and deadlocks is critical. This study evaluates the performance of several leading large language models…
Different parallel frameworks for implementing data analysis applications have been proposed by the HPC and Big Data communities. In this paper, we investigate three task-parallel frameworks: Spark, Dask and RADICAL-Pilot with respect to…
Programmers of distributed systems need to reason about concurrency to avoid races. However, reasoning about concurrency is difficult, and unexpected races show up as bugs. Data race detection in shared memory systems is well-studied…
With the great achievement of artificial intelligence, vehicle technologies have advanced significantly from human centric driving towards fully automated driving. An intelligent vehicle should be able to understand the driver's perception…
Service Function Chains (SFCs) are one of the key enablers in providing programmable computer networks, paving the way for network autonomy. However, this also introduces new challenges, such as resource allocation and optimisation related…
Deep Neural Network (DNN) trained object detectors are widely deployed in many mission-critical systems for real time video analytics at the edge, such as autonomous driving and video surveillance. A common performance requirement in these…
Data races are a notorious problem in parallel programming. There has been great research interest in type systems that statically prevent data races. Despite the progress in the safety and usability of these systems, lots of existing…
Diagnosing and fixing performance problems on multicore machines with deep memory hierarchies is extremely challenging. Certain problems are best addressed when we can analyze the entire trace of program execution, e.g., every memory…
We propose a novel and efficient method, that we shall call TopRank in the following paper, for detecting change-points in high-dimensional data. This issue is of growing concern to the network security community since network anomalies…
Dynamic Source Routing (DSR) is an efficient on-demand routing protocol for mobile ad-hoc networks (MANET). It depends on two main procedures: Route Discovery and Route Maintenance. Route discovery is the procedure used at the source of the…
Modern software systems become too complex to be tested and validated. Detecting software partial failures in complex systems at runtime assist to handle software unintended behaviors, avoiding catastrophic software failures and improving…
Context: Since it is well-established that developers spend a substantial portion of their time understanding source code, the ability to automatically identify algorithms within source code presents a valuable opportunity. This capability…
It is often difficult to write code that you can ensure will be executed in the right order when programing for parallel compute tasks. Due to the way that today's parallel compute hardware, primarily Graphical Processing Units (GPUs),…
This paper presents an advanced mapping system that combines drone imagery with machine learning and computer vision to overcome challenges in speed, accuracy, and adaptability across diverse terrains. By automating processes like feature…
In this paper, we propose an approach that relies on distributed traffic generation and monitoring to identify the operational data-paths in a given Software Defined Networking (SDN) driven data-plane. We show that under certain…