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Detecting semantic interference remains a challenge in collaborative software development. Recent lightweight static analysis techniques improve efficiency over SDG-based methods, but they still suffer from a high rate of false positives. A…
Anomaly detection is crucial in industrial product quality inspection. Failing to detect tiny defects often leads to serious consequences. Existing methods face a structure-semantics trade-off: structure-oriented models (such as…
Software development industries are increasingly adopting containers to enhance the scalability and flexibility of software applications. Security in containerized projects is a critical challenge that can lead to data breaches and…
Exploiting the performance of today's processors requires intimate knowledge of the microarchitecture as well as an awareness of the ever-growing complexity in thread and cache topology. LIKWID is a set of command-line utilities that…
Computational social science lacks a scalable and reliable mechanism to assure quality for AI-assisted qualitative coding when tasks demand domain expertise and long-text reasoning, and traditional double-coding is prohibitively costly at…
Microarchitectural code analyzers, i.e., tools that estimate the throughput of machine code basic blocks, are important utensils in the tool belt of performance engineers. Recent tools like llvm-mca, uiCA, and Ithemal use a variety of…
The test pyramid is a conceptual model that describes how quality checks can be organized to ensure coverage of all components of a system, at all scales. Originally conceived to help aerospace engineers plan tests to determine how material…
With the richness of present-day hardware architectures, tightening the synergy between hardware and software has attracted a great attention. The interest in unified approaches paved the way for newborn frameworks that target hardware and…
In various provers and deductive verification tools, logical transformations are used extensively in order to reduce a proof task into a number of simpler tasks. Logical transformations are often part of the trusted base of such tools. In…
Diffusion models have emerged as powerful generative priors for solving inverse imaging problems. However, their practical deployment is hindered by the substantial computational cost of slow, multi-step sampling. Although Consistency…
In multi-view clustering, different views may have different confidence levels when learning a consensus representation. Existing methods usually address this by assigning distinctive weights to different views. However, due to noisy nature…
Recently, we introduced a new class of finite alphabet iterative decoders (FAIDs) for low-density parity-check (LDPC) codes. These decoders are capable of surpassing belief propagation in the error floor region on the Binary Symmetric…
This work focuses on a specific front of the malware detection arms-race, namely the detection of persistent, disk-resident malware. We exploit normalised compression distance (NCD), an information theoretic measure, applied directly to…
We introduce the Fusion algorithm for local refinement type inference, yielding a new SMT-based method for verifying programs with polymorphic data types and higher-order functions. Fusion is concise as the programmer need only write…
Error slice discovery is crucial to diagnose and mitigate model errors. Current clustering or discrete attribute-based slice discovery methods face key limitations: 1) clustering results in incoherent slices, while assigning discrete…
Accurate segmentation and classification of nuclei in histology images is critical but challenging due to nuclei heterogeneity, staining variations, and tissue complexity. Existing methods often struggle with limited dataset variability,…
SystemC-based virtual prototypes have emerged as widely adopted tools to test software ahead of hardware availability, reducing the time-to-market and improving software reliability. Recently, fuzzing has become a popular method for…
With the increasing popularity of continuous integration, algorithms for selecting the minimal test-suite to cover a given set of changes are in order. This paper reports on how polymorphism can handle false negatives in a previous…
Camouflaged Object Detection (COD), the task of identifying objects concealed within their environments, has seen rapid growth due to its wide range of practical applications. A key step toward developing trustworthy COD systems is the…
Modern software systems complexity challenges efficient testing, as traditional machine learning (ML) struggles with large test suites. This research presents a hybrid framework integrating Quantum Annealing with ML to optimize test case…