26,098 papers · page 60 of 1,305
Recently, dynamic concurrency bug predictions have kept making notable progress in improving concurrency coverage while ensuring soundness. Most of them rely solely on dynamic information in traces and overlook the static semantics of the program when predicting bugs. To ensure s…
Julia is a dynamically-typed garbage-collected language designed for high performance. Julia has a non-moving tracing collector, which, while performant, is subject to the same unavoidable fragmentation and lack of locality as all other non-moving collectors. In this work, we ref…
The effectiveness of generational garbage collection is usually explained through the generational hypothesis, that “most objects die young”. Despite its simplicity, the generational hypothesis leaves some things to be desired: it is not obvious how it can be measured as a prope…
Recent processors rely on huge pages to reduce the cost of virtual-to-physical address translation. However, huge pages are notorious for creating memory bloat – a phenomenon wherein the OS ends up allocating more physical memory to an application than its actual requirement. Thi…
Reclaiming cyclic garbage has been a long-standing challenge in automatic memory management. Common approaches to this problem often involve extending reference counting with an asynchronous background task to reclaim cycles. While this ensures that cycles are eventually collecte…
Processing-in-memory (PIM) is a promising approach to overcome the performance bottleneck caused by the gap between CPU speed and memory speed, known as the memory wall problem. The UPMEM PIM-enabled memory is the first commercialized general-purpose PIM accelerator, to which the…
Memory errors continue to be a critical concern for programs written in low-level programming languages such as C and C++. Many different memory error defenses have been proposed, each with varying trade-offs in terms of overhead, compatibility, and attack resistance. Some defens…
Writing crash-consistent programs for memory-semantic storage such as persistent memory (PMEM) is error-prone and cumbersome. Programmers must implement both the main logic and the recovery logic to ensure data consistency after unexpected power failures. Prior work has reduced t…
Deep neural networks (DNNs) are one of the popular models for learning relationships between complex data. Training a DNN model is a compute- and memory-intensive operation. The size of modern DNN models spans into the terabyte region, requiring multiple accelerators to train -- …
Ruby is a dynamic programming language that was first released in 1995 and remains heavily used today. Ruby underpins Ruby on Rails, one of the most widely deployed web application frameworks. The scale at which Rails is deployed has placed increasing pressure on the underlying C…
Large language models (LLMs) hold great promise for automating software vulnerability detection and repair, but ensuring their correctness remains a challenge. While recent work has developed benchmarks for evaluating LLMs in bug detection and repair, existing studies rely on han…
Frequent changes in application requirements demand not only schema and query adaptation but also migration and optimization of the object-relational mapping (ORM) code. While database and query migration are well-studied, application-level translation across ORM frameworks remai…
Designing algorithms for complex problems as certifying algorithms is an important approach to ensure correctness of computational results. Instead of producing an output y for an input x, a certifying algorithm produces as output for x not only y but also a witness w. The witnes…
Code comprehension and analysis of open-source project codebases is a task frequently performed by developers and researchers. However, existing tools that practitioners use for assistance with such tasks often require prior project setup, lack context-awareness, and involve sign…
The stakeholders involved in software development are becoming increasingly diverse, with both human contributors from varied backgrounds and AI-powered agents collaborating together in the process. This situation presents unique governance challenges, particularly in Open-Source…
Fairness in algorithmic decision-making is often framed in terms of individual fairness, which requires that similar individuals receive similar outcomes. A system violates individual fairness if there exists a pair of inputs differing only in protected attributes (such as race o…
Patch overfitting remains a persistent challenge in automated program repair (APR), especially when validation depends on incomplete test suites. We argue that this problem is significantly exacerbated by the overlooked presence of multiple interacting faults, a common yet under-…
Multi-fault programs, which contain more than one bug simultaneously, are notoriously difficult to debug and repair. This is largely because faults can interact in subtle ways: one might hide the effects of another, or even cause new failures to appear when combined. In this pape…
REST API test case generation tools are evolving rapidly, with growing capabilities for the automated generation of complex tests. However, despite their strengths in test data generation, these tools are constrained by the types of test oracles they support, often limited to cra…
Lower bounds provide essential insights into the minimal computational resources required for algorithm execution. This paper focuses on logical theories, a domain where estimating resources is particularly difficult, and provides a novel, fully-automated method for computing low…