Related papers: Automatic Linear Resource Bound Analysis for Rust …

When programs feature a complex control flow, existing techniques for resource analysis produce cost relation systems (CRS) whose cost functions retain the complex flow of the program and, consequently, might not be solvable into…

Iteration is a programming operation that traditionally refers to visiting the elements of a data structure in sequence. However, modern programming systems such as Rust, Java, and C# generalise iteration far beyond the traditional use…

Rust, a popular systems-level programming language, has garnered widespread attention due to its features of achieving run-time efficiency and memory safety. With an increasing number of real-world projects adopting Rust, understanding how…

Agentic Retrieval-Augmented Generation (RAG) systems combine iterative search, planning prompts, and retrieval backends, but deployed settings impose explicit budgets on tool calls and completion tokens. We present a controlled measurement…

Language models (LMs) now excel at many tasks such as few-shot learning, question answering, reasoning, and dialog. However, they sometimes generate unsupported or misleading content. A user cannot easily determine whether their outputs are…

R is a popular language and programming environment for data scientists. It is increasingly co-packaged with both relational and Hadoop-based data platforms and can often be the most dominant computational component in data analytics…

Existing automated verification techniques for safe Rust code rely on the strong type-system properties to reason about programs, especially to deduce which memory locations do not change (i.e., are framed) across function calls. However,…

Machine learning (ML)-assisted outage-based resource allocation has recently emerged as an effective alternative to conventional scheduling methods in reliability-critical wireless systems. However, existing approaches are fundamentally…

Rust is a modern programming language that guarantees memory safety and the absence of data races with a strong type system. We present RustyDL, a program logic for Rust, as a foundation for an auto-interactive, deductive verification tool…

Developers rely on the static safety guarantees of the Rust programming language to write secure and performant applications. However, Rust is frequently used to interoperate with other languages which allow design patterns that conflict…

Large reasoning models improve accuracy by producing long reasoning traces, but this inflates latency and cost, motivating inference-time efficiency. We propose Retrieval-of-Thought (RoT), which reuses prior reasoning as composable…

Automatic speech recognition for low-resource languages remains fundamentally constrained by the scarcity of labeled data and computational resources required by state-of-the-art models. We present a systematic investigation into…

Dubbed a safer C, Rust is a modern programming language that combines memory safety and low-level control. This interesting combination has made Rust very popular among developers and there is a growing trend of migrating legacy codebases…

Nowadays, data-centers are largely under-utilized because resource allocation is based on reservation mechanisms which ignore actual resource utilization. Indeed, it is common to reserve resources for peak demand, which may occur only for a…

Rust is a low-level programming language known for its unique approach to memory-safe systems programming and for its steep learning curve. To understand what makes Rust difficult to adopt, we surveyed the top Reddit and Hacker News posts…

We propose an approach for modular verification of programs that use relaxed-consistency atomic memory access primitives and fences. The approach is sufficient for verifying the core of Rust's Atomic Reference Counting (ARC) algorithm. We…

Retrieval-augmented generation (RAG) enhances language models by integrating external knowledge, but its effectiveness is highly dependent on system configuration. Improper retrieval settings can degrade performance, making RAG less…

Performance analysis of all kinds of randomised search heuristics is a rapidly growing and developing field. Run time and solution quality are two popular measures of the performance of these algorithms. The focus of this paper is on the…

Detecting buffer overruns from a source code is one of the most common and yet challenging tasks in program analysis. Current approaches have mainly relied on rigid rules and handcrafted features devised by a few experts, limiting…

Robust optimization is a very popular means to address decision-making problems affected by uncertainty. Its success has been fueled by its attractive robustness and scalability properties, by ease of modeling, and by the limited…