Results 41 to 50 of about 12,796,570 (330)

Meta-Heuristic Guided Feature Optimization for Enhanced Authorship Attribution in Java Source Code

open access: yesIEEE Access, 2023
Source code authorship attribution is the task of identifying who develops the code based on learning based on the programmer style. It is one of the critical activities which used extensively in different aspects such as computer security, computer law,
Bilal Al-Ahmad   +8 more
doaj   +1 more source

Deep Learning for Source Code Modeling and Generation [PDF]

open access: yesACM Computing Surveys, 2020
Deep Learning (DL) techniques for Natural Language Processing have been evolving remarkably fast. Recently, the DL advances in language modeling, machine translation, and paragraph understanding are so prominent that the potential of DL in Software ...
T. H. Le, Hao Chen, M. A. Babar
semanticscholar   +1 more source

DETECTION OF SOURCE CODE IN INTERNET TEXTS USING AUTOMATICALLY GENERATED MACHINE LEARNING MODELS [PDF]

open access: yesApplied Computer Science, 2022
In the paper, the authors are presenting the outcome of web scraping software allowing for the automated classification of source code. The software system was prepared for a discussion forum for software developers to find fragments of source code ...
Marcin BADUROWICZ
doaj   +1 more source

Implementation of an Arduino controller for temporary traffic regulation in one lane with semaphores [PDF]

open access: yesИкономика и компютърни науки, 2021
The purpose of this article is to present the use of an Arduino controller for a road semaphore to regulate traffic in directions in one lane. An Arduino starter kit is used.
Julian Vasilev   +4 more
doaj  

Diagnosing Errors in DbC Programs Using Constraint Programming [PDF]

open access: yes, 2005
Model-Based Diagnosis allows to determine why a correctly designed system does not work as it was expected. In this paper, we propose a methodology for software diagnosis which is based on the combination of Design by Contract, Model-Based Diagnosis ...
Borrego Núñez, Diana   +3 more
core   +1 more source

LDGM Codes for Channel Coding and Joint Source-Channel Coding of Correlated Sources

open access: yesEURASIP Journal on Advances in Signal Processing, 2005
Summary: We propose a coding scheme based on the use of systematic linear codes with low-density generator matrix (LDGM codes) for channel coding and joint source-channel coding of multiterminal correlated binary sources. In both cases, the structures of the LDGM encoder and decoder are shown, and a concatenated scheme aimed at reducing the error floor
Wei Zhong, Javier Garcia-Frías
openaire   +3 more sources

Semantic Robustness of Models of Source Code [PDF]

open access: yesIEEE International Conference on Software Analysis, Evolution, and Reengineering, 2020
Deep neural networks are vulnerable to adversarial examples-small input perturbations that result in incorrect predictions. We study this problem for models of source code, where we want the neural network to be robust to source-code modifications that ...
Goutham Ramakrishnan   +5 more
semanticscholar   +1 more source

Deep Code-Comment Understanding and Assessment

open access: yesIEEE Access, 2019
Code comments are a key software component for program comprehension and software maintainability. High-quality code and comments are urgently needed by data-driven models widely used in tasks like code summarization.
Deze Wang   +5 more
doaj   +1 more source

Resilient Source Coding

open access: yesCoRR, 2011
This paper provides a source coding theorem for multi-dimensional information signals when, at a given instant, the distribution associated with one arbitrary component of the signal to be compressed is not known and a side information is available at the destination. This new framework appears to be both of information-theoretical and game-theoretical
Le Treust, Mael, Lasaulce, Samson
openaire   +4 more sources

Automated Vulnerability Detection in Source Code Using Deep Representation Learning [PDF]

open access: yesInternational Conference on Machine Learning and Applications, 2018
Increasing numbers of software vulnerabilities are discovered every year whether they are reported publicly or discovered internally in proprietary code.
Rebecca L. Russell   +7 more
semanticscholar   +1 more source

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