Search Results for "source code plagiarism detection" - Page 3
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Showing 119 open source projects for "source code plagiarism detection"
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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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libcxc
library for handling exceptions and signals in C
The main purpose of this library is to provide uniform interface for seamless handling of signals and exceptions. This project is focused on simplicity and flexibility - it does not even try to mimic C++ exceptions system - instead, it offers only few simple functions and macros which can be easily combined with custom user code to tune the functionality for particular use cases. -
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Monokle
Better create, understand, and deploy YAML manifests
Monokle's integrated open-source tools and cloud platform make it easy to define, manage, and enforce Kubernetes YAML configuration policies in minutes. Deploy, manage and audit policies for your teams across the entire configuration lifecycle from a centralized Dashboard. Define polices using 100+ pre-existing rules for Security, Resource Usage, and Compliance. Create your own Validation Extensions for your organization's compliance and conventions. Assess policy enforcement impact by... -
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GIXY
Nginx configuration static analyzer
Gixy is a tool to analyze Nginx configuration. The main goal of Gixy is to prevent security misconfiguration and automate flaw detection. Currently supported Python versions are 2.7, 3.5, 3.6 and 3.7. Gixy is well tested only on GNU/Linux, other OSs may have some issues. You can find things that Gixy is learning to detect at Issues labeled with "new plugin". By default Gixy will try to analyze Nginx configuration placed in /etc/nginx/nginx.conf. Or something else, you can find all other gixy... -
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Primus
An abstraction layer for real-time to prevent module lock-in
Primus, the creator god of transformers but now also known as universal wrapper for real-time frameworks. There are a lot of real-time frameworks available for Node.js and they all have different opinions on how real-time should be done. Primus provides a common low level interface to communicate in real-time using various real-time frameworks. Effortless switching between real-time frameworks by changing one single line of code. No more API rewrites needed when your project requirements... -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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apiDoc
RESTful web API documentation Generator
apiDoc creates a documentation from API annotations in your source code. apiDoc gives you the ability to attach a version number to an API so you can easily track changes between versions. Creates an apiDoc of all files within dir myapp/, uses template from dir mytemplate/ and put all output to dir apidoc/. Without any parameter, apiDoc generate a documentation from all .cs .dart .erl .go .java .js .php .py .rb .ts files in current dir (incl. subdirs) and writes the output to ./doc/. apiDoc... -
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wxMEdit
wxMEdit, Cross-platform Text/Hex Editor, Improved Version of MadEdit
•Added automatically checking for updates •Added bookmark support •Added right-click context menu for each tab •Added purging histories support •Added selecting a line by triple click •Added FreeBASIC syntax file •Added an option to place configuration files into %APPDATA% directory under Windows •Improved support for Find/Replace •Improved Mac OS X support •Improved system integration under Windows •Improved encoding detection result •Improved Hex editing support •Added more... -
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Code Maat
A command line tool to mine and analyze data from version-control
Code Maat is a command-line tool for analyzing version-control systems (Git, SVN, etc.) to uncover code health insights—development hotspots, author coupling, and temporal change metrics. Created by Adam Tornhill, it supports research in behavioral code analysis and is often paired with his books like Code as a Crime Scene and Software Design X‑Rays. -
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Axel-DICE
Axel-DICE Code Editor For Windows,Linux
🌈 Axel-DICE The Ultimate Code Editor for Effortless Coding! 💻🎲Axel-DICE revolutionizes coding with Dynamic Integrated Code Editor(DICE), allowing you to run code instantly without saving or compiling. With its user-friendly interface, you can write and execute code effortlessly with a single click. Save time, eliminate manual processes, and unleash your coding potential! ⚡️🔥 🚀 Lightweight and fast: No complex setup required. Install Axel-DICE and start coding right away! 🕵️♀️ Auto... -
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RedtDec
RetDec is a retargetable machine-code decompiler based on LLVM
The decompiler is not limited to any particular target architecture, operating system, or executable file format. ELF, PE, Mach-O, COFF, AR (archive), Intel HEX, and raw machine code supported. 32-bit: Intel x86, ARM, MIPS, PIC32, and PowerPC 64-bit: x86-64 supported. Demangling of symbols from C++ binaries (GCC, MSVC, Borland). Reconstruction of functions, types, and high-level constructs. Output in two high-level languages: C and a Python-like language. Generation of call graphs,... -
Fully Managed MySQL, PostgreSQL, and SQL ServerCloud SQL handles your database ops end to end, so you can focus on your app.
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rust.vim
Vim configuration for Rust
rust.vim is the official Vim plugin from the Rust Lang Foundation team that adds support for Rust files in Vim and Neovim. It provides file-detection (so .rs files are recognised), syntax highlighting tuned for Rust’s syntax and macros, and supports formatting via rustfmt and other language-specific tooling. The plugin also integrates with other Vim tools and linters, helping you build a full Rust-editing workflow in Vim. Because Rust’s macro system and language features are more complex... -
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PyTorch Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.
TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please... -
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YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
YOLOV4 Pytorch is a PyTorch implementation of the YOLOv4 object detection model for training and running custom detection systems. The repository is structured around practical workflows, including training, prediction, evaluation, anchor generation, model configuration, and dataset annotation utilities. It supports VOC-style datasets and includes scripts for prediction, mAP evaluation, FPS testing, video prediction, batch prediction, and heatmap generation. The project added multi-GPU... -
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Angular Performance Checklist
Cheatsheet for developing lightning fast progressive Angular apps
Angular Performance Checklist is a practical resource and “cheatsheet” aimed at helping Angular (or AngularJS/Angular-related) developers optimize web application performance, covering both network/load-time optimizations and runtime performance improvements. It outlines actionable recommendations — from bundling and minification, tree-shaking, lazy loading, ahead-of-time (AoT) compilation, resource prefetching, caching and compression, to runtime strategies like change-detection... -
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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
YOLOV3 Pytorch is a PyTorch implementation of the YOLOv3 object detection model built for training, prediction, and evaluation. The repository provides a complete workflow for users who want to train their own object detector with VOC-style data or use pretrained weights. It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. The project added multi-GPU training, target... -
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Google Cloud Vision API examples
Sample code for Google Cloud Vision
The cloud-vision repository is a sample code collection for the Google Cloud Vision API that shows developers how to implement image analysis tasks across a wide range of languages and platforms. It contains examples organized by language and environment, including Go, Java, Node.js, PHP, Python, Ruby, .NET, Android, iOS, and even a Chrome extension, which makes it especially valuable as a cross-platform learning resource. The repository demonstrates concrete image understanding use cases,... -
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libfacedetection
Library for face detection in images
This is an open source library for CNN-based face detection in images. The CNN model has been converted to static variables in C source files. The source code does not depend on any other libraries. What you need is just a C++ compiler. You can compile the source code under Windows, Linux, ARM and any platform with a C++ compiler. SIMD instructions are used to speed up the detection. -
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YOLOR
implementation of paper - You Only Learn One Representation
YOLOR is the implementation of “You Only Learn One Representation,” a unified network approach for learning explicit and implicit knowledge together. The project focuses on object detection while exploring how a shared representation can support multiple tasks. It builds on the YOLO family and related PyTorch detection work, combining practical detector training with a research idea about unified representations. YOLOR includes model configurations, training code, evaluation scripts,... -
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CameraVoyeur
Windows-oriented utility to log frames from a connected camera devices
CameraVoyeur is a small Windows-oriented utility that demonstrates how to capture, preview, and possibly log frames from a connected camera device in a lightweight way. It’s set up more like an experiment or proof-of-concept than a polished end-user app, focusing on the plumbing for grabbing images from the webcam. The project shows how to access the camera stream, keep it running, and expose the captured output for later use or display. Because it’s in a regular GitHub repo and not a closed... -
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WBBlades
WBBlades is a tool set based on Mach-O file parsing
WBBlades is a toolset based on Mach-O file parsing, including one-click detection for the app (supports OC and Swift), package size analysis (supports a single static library/dynamic library), point-to-point crash analysis (analyze system crash log, based on symbol file and without symbol files), Class automatic extraction and Hook capability based on Mach-O file. It mainly uses __Text assembly code analysis, architecture extraction, DYSM file stripping, symbol table stripping, and crash... -
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TNN
Uniform deep learning inference framework for mobile
TNN, a high-performance, lightweight neural network inference framework open sourced by Tencent Youtu Lab. It also has many outstanding advantages such as cross-platform, high performance, model compression, and code tailoring. The TNN framework further strengthens the support and performance optimization of mobile devices on the basis of the original Rapidnet and ncnn frameworks. At the same time, it refers to the high performance and good scalability characteristics of the industry's... -
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CodeQL
Libraries and queries that power security researchers
CodeQL is a semantic code analysis engine that treats programs as queryable databases, enabling users to write expressive queries that identify security vulnerabilities, logic bugs, and code quality issues across large codebases. Instead of just pattern matching text, CodeQL ingests source code, builds rich representations of structure and data flow, and allows queries that reason about control flow, type systems, and interprocedural relationships. -
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PulledPork
Pulled Pork for Snort and Suricata rule management (from Google code)
PulledPork is a Perl-based script that automates the management of Snort and Suricata IDS/IPS rulesets. It streamlines the process of downloading, parsing, and updating rules, ensuring that intrusion detection systems remain current and effective. -
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DETR
End-to-end object detection with transformers
PyTorch training code and pretrained models for DETR (DEtection TRansformer). We replace the full complex hand-crafted object detection pipeline with a Transformer, and match Faster R-CNN with a ResNet-50, obtaining 42 AP on COCO using half the computation power (FLOPs) and the same number of parameters. Inference in 50 lines of PyTorch. What it is. Unlike traditional computer vision techniques, DETR approaches object detection as a direct set prediction problem. It consists of a set-based... -
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Computer Vision
Best Practices, code samples, and documentation for Computer Vision
In recent years, we've see an extra-ordinary growth in Computer Vision, with applications in face recognition, image understanding, search, drones, mapping, semi-autonomous and autonomous vehicles. A key part to many of these applications are visual recognition tasks such as image classification, object detection and image similarity. This repository provides examples and best practice guidelines for building computer vision systems. The goal of this repository is to build a comprehensive... -
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Tensor2Tensor
Library of deep learning models and datasets
Deep Learning (DL) has enabled the rapid advancement of many useful technologies, such as machine translation, speech recognition and object detection. In the research community, one can find code open-sourced by the authors to help in replicating their results and further advancing deep learning. However, most of these DL systems use unique setups that require significant engineering effort and may only work for a specific problem or architecture, making it hard to run new experiments and...