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Related papers: Machines are benchmarked by code, not algorithms

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Code style is an aesthetic choice exhibited in source code that reflects programmers individual coding habits. This study is the first to investigate whether code style can be used as an indicator to identify good programmers. Data from…

Software Engineering · Computer Science 2024-09-02 Rafed Muhammad Yasir , Ahmedul Kabir

Application-based benchmarks are increasingly used to quantify and compare quantum computers' performance. However, because contemporary quantum computers cannot run utility-scale computations, these benchmarks currently test this…

Context: In the realm of software development, maintaining high software quality is a persistent challenge. However, this challenge is often impeded by the lack of comprehensive understanding of how specific code modifications influence…

Software Engineering · Computer Science 2024-04-08 Thomas Karanikiotis , Andreas L. Symeonidis

Reinforcement learning has recently experienced increased prominence in the machine learning community. There are many approaches to solving reinforcement learning problems with new techniques developed constantly. When solving problems…

Machine Learning · Computer Science 2020-12-14 Belinda Stapelberg , Katherine M. Malan

Grids include heterogeneous resources, which are based on different hardware and software architectures or components. In correspondence with this diversity of the infrastructure, the execution time of any single job, as well as the total…

Performance · Computer Science 2007-06-13 John Kouvakis , Fotis Georgatos

The measurable properties of the artifacts or objects in the computer, management, or finance disciplines are extrinsic, not inherent -- dependent on their problem definitions and solution instantiations. Only after the instantiation can…

Emerging Technologies · Computer Science 2022-05-17 Jianfeng Zhan

Hypergraph partitioning is a central component of distributed quantum computing (DQC) compilers. However, due to the limited size of available quantum benchmark suites, many partitioning studies rely on random quantum circuits as evaluation…

Quantum Physics · Physics 2026-05-12 Maria Gragera Garces

The human brain has inspired novel concepts complementary to classical and quantum computing architectures, such as artificial neural networks and neuromorphic computers, but it is not clear how their performances compare. Here we report a…

Neurons and Cognition · Quantitative Biology 2023-05-25 Céline van Valkenhoef , Catherine Schuman , Philip Walther

Requirements and code, in conventional software engineering wisdom, belong to entirely different worlds. Is it possible to unify these two worlds? A unified framework could help make software easier to change and reuse. To explore the…

Software Engineering · Computer Science 2016-02-18 Alexandr Naumchev , Bertrand Meyer , Victor Rivera

Code review is considered a key process in the software industry for minimizing bugs and improving code quality. Inspection of review process effectiveness and continuous improvement can boost development productivity. Such inspection is a…

Software Engineering · Computer Science 2023-07-11 Saifullah Mahbub , Md. Easin Arafat , Chowdhury Rafeed Rahman , Zannatul Ferdows , Masum Hasan

Algorithm selection, aiming to identify the best algorithm for a given problem, plays a pivotal role in continuous black-box optimization. A common approach involves representing optimization functions using a set of features, which are…

Machine Learning · Computer Science 2025-05-13 Gašper Petelin , Gjorgjina Cenikj

A computer code or simulator is a mathematical representation of a physical system, for example a set of differential equations. Running the code with given values of the vector of inputs, x, leads to an output y(x) or several such outputs.…

Methodology · Statistics 2016-01-25 Derek Bingham , Pritam Ranjan , William Welch

Benchmark experiments are required to test, compare, tune, and understand optimization algorithms. Ideally, benchmark problems closely reflect real-world problem behavior. Yet, real-world problems are not always readily available for…

Neural and Evolutionary Computing · Computer Science 2020-08-17 Martin Zaefferer , Frederik Rehbach

Quantum Computing (QC) is undergoing a high rate of development, investment and research devoted to its improvement.However, there is little consensus in the industry and wider literature as to what improvement might consist of beyond…

Quantum Physics · Physics 2024-05-15 Jessica Park , Susan Stepney , Irene D'Amico

Reliable resource estimation and benchmarking of quantum algorithms is a critical component of the development cycle of viable quantum applications for quantum computers of all sizes. Determining critical resource bottlenecks in algorithms,…

Quantum Physics · Physics 2019-02-22 Alexandru Paler , Daniel Herr , Simon J. Devitt

Achieving fault-tolerance will require a strong relationship between the hardware and the protocols used. Different approaches will therefore naturally have tailored proof-of-principle experiments to benchmark progress. Nevertheless,…

Quantum Physics · Physics 2024-05-28 Milan Liepelt , Tommaso Peduzzi , James R. Wootton

Context: Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective: To reduce the inconsistency amongst validation study results and provide a more formal…

Software Engineering · Computer Science 2021-01-15 Martin Shepperd , Stephen G. MacDonell

Code-related benchmarks play a critical role in evaluating large language models (LLMs), yet their quality fundamentally shapes how the community interprets model capabilities. In the past few years, awareness of benchmark quality has…

Decolorization is the process to convert a color image or video to its grayscale version, and it has received great attention in recent years. An ideal decolorization algorithm should preserve the original color contrast as much as…

Graphics · Computer Science 2014-04-23 Wei Hu , Wei Li , Fan Zhang , Qian Du

Empirical and LLM-based research in model-driven engineering increasingly relies on datasets of software models, for instance, to train or evaluate machine learning techniques for modeling support. These datasets have a significant impact…

Software Engineering · Computer Science 2026-03-06 Philipp-Lorenz Glaser , Lola Burgueño , Dominik Bork
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