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Chunked codes are efficient random linear network coding (RLNC) schemes with low computational cost, where the input packets are encoded into small chunks (i.e., subsets of the coded packets). During the network transmission, RLNC is…

Information Theory · Computer Science 2015-03-27 Bin Tang , Shenghao Yang , Baoliu Ye , Yitong Yin , Sanglu Lu

Product codes (PCs) protect a two-dimensional array of bits using short component codes. Assuming transmission over the binary symmetric channel, the decoding is commonly performed by iteratively applying bounded-distance decoding to the…

Information Theory · Computer Science 2017-11-22 Christian Häger , Henry D. Pfister

By extending the traditional store-and-forward mechanism, network coding has the capability to improve a network's throughput, robustness, and security. Given the fundamentally different packet processing required by this new paradigm and…

Networking and Internet Architecture · Computer Science 2019-09-06 Diogo Gonçalves , Salvatore Signorello , Fernando M. V. Ramos , Muriel Médard

We propose a new coding scheme, called the delayed coding (DC) scheme, for channels with insertion, deletion, and substitution (IDS) errors. The proposed scheme employs delayed encoding and non-iterative detection and decoding strategies to…

Information Theory · Computer Science 2022-05-25 Ryo Shibata , Hiroyuki Yashima

The fourth industrial revolution creates ubiquitous sensor data in production plants. To generate maximum value out of these data, reliable and precise time series-based machine learning methods like temporal neural networks are needed.…

Machine Learning · Computer Science 2023-05-22 Stefan Gaugel , Manfred Reichert

In this paper, we introduce Continuation Passing C (CPC), a programming language for concurrent systems in which native and cooperative threads are unified and presented to the programmer as a single abstraction. The CPC compiler uses a…

Programming Languages · Computer Science 2012-11-15 Gabriel Kerneis , Juliusz Chroboczek

Generative Pre-trained Transformer (GPT) is a state-of-the-art machine learning model capable of generating human-like text through natural language processing (NLP). GPT is trained on massive amounts of text data and uses deep learning…

In this paper we introduce Neural Network Coding(NNC), a data-driven approach to joint source and network coding. In NNC, the encoders at each source and intermediate node, as well as the decoder at each destination node, are neural…

Information Theory · Computer Science 2021-01-12 Litian Liu , Amit Solomon , Salman Salamatian , Muriel Medard

Testing is one of the most indispensable tasks in software engineering. The role of testing in software development has grown significantly because testing is able to reveal defects in the code in an early stage of development. Many unit…

Software Engineering · Computer Science 2010-12-07 Norbert Pataki

Preserving invariants while designing distributed applications under weak consistency models is difficult. The CEC (Correct Eventual Consistency Tool) is meant to aid the application designer in this task. It provides information about the…

Distributed, Parallel, and Cluster Computing · Computer Science 2018-07-18 Sreeja Nair , Marc Shapiro

Lockstep processing is a recognized technique for helping to secure functional-safety relevant processing against, for instance, single upset errors that might cause faulty execution of code. Lockstepping processors does however bind…

Hardware Architecture · Computer Science 2021-07-20 Hans Dermot Doran , Timo Lang

We present new algorithms for the problem of multiple string matching of gapped patterns, where a gapped pattern is a sequence of strings such that there is a gap of fixed length between each two consecutive strings. The problem has…

Data Structures and Algorithms · Computer Science 2014-07-08 Emanuele Giaquinta , Kimmo Fredriksson , Szymon Grabowski , Alexandru I. Tomescu , Esko Ukkonen

OpenACC lowers the barrier to GPU offloading, but writing high-performing pragma remains complex, requiring deep domain expertise in memory hierarchies, data movement, and parallelization strategies. Large Language Models (LLMs) present a…

Software Engineering · Computer Science 2026-01-15 Samyak Jhaveri , Cristina V. Lopes

Stencil computations, involving operations over the elements of an array, are a common programming pattern in scientific computing, games, and image processing. As a programming pattern, stencil computations are highly regular and amenable…

Programming Languages · Computer Science 2011-09-06 Dominic Orchard , Alan Mycroft

Product codes are a concatenated error-correction scheme that has been often considered for applications requiring very low bit-error rates, which demand that the error floor be decreased as much as possible. In this work, we consider…

Information Theory · Computer Science 2017-09-26 Carlo Condo , Francois Leduc-Primeau , Gabi Sarkis , Pascal Giard , Warren Gross

Recurrent neural networks are nowadays successfully used in an abundance of applications, going from text, speech and image processing to recommender systems. Backpropagation through time is the algorithm that is commonly used to train…

Machine Learning · Computer Science 2018-01-10 Cedric De Boom , Thomas Demeester , Bart Dhoedt

Modern dense Flash memory devices operate at very low error rates, which require powerful error correcting coding (ECC) techniques. An emerging class of graph-based ECC techniques that has broad applications is the class of…

Information Theory · Computer Science 2019-09-25 Ahmed Hareedy , Homa Esfahanizadeh , Lara Dolecek

Formal methods for verification of programs are extended to testing of programs. Their combination is intended to lead to benefits in reliable program development, testing, and evolution. Our geometric theory of testing is intended to serve…

Software Engineering · Computer Science 2022-06-07 Bernhard Moller , Tony Hoare , Zhe Hou , Jin Song Dong

We give the easily recognizable name "cinnamon" and "cinnamon programming" to a new computation model intended to form a theoretical foundation for Control Network Programming (CNP). CNP has established itself as a programming paradigm…

Programming Languages · Computer Science 2017-10-18 Kostadin Kratchanov

A wide range of code intelligence (CI) tools, powered by deep neural networks, have been developed recently to improve programming productivity and perform program analysis. To reliably use such tools, developers often need to reason about…

Software Engineering · Computer Science 2021-09-10 Md Rafiqul Islam Rabin , Vincent J. Hellendoorn , Mohammad Amin Alipour
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