Search Results for "code coverage" - Page 4
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172 projects for "code coverage" with 1 filter applied:
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Your monitoring isn't a stack. It's a pile. Fix that.Replace Datadog, New Relic, and Sentry without adding three more dashboards.
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JavaScript & Node.js Testing
Comprehensive and exhaustive JavaScript & Node.js testing
This project compiles practical advice for testing JavaScript applications across the stack, emphasizing clarity, speed, and reliability over dogma. It distinguishes between different kinds of tests—unit, integration, end-to-end—and shows when each is appropriate given time and risk constraints. The guide focuses on removing flakiness by isolating side effects, controlling randomness, and stabilizing async code paths. It also demonstrates test design techniques like arranging test data,... -
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EclEmma is a free Java code coverage tool for Eclipse, available under the Eclipse Public License. It brings code coverage analysis directly into the Eclipse workbench. The EclEmma project is also the home of the JaCoCo code coverage library which is the technical back-end for EclEmma and also has integrations with many other build and software quality tools.
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Chess-Coding-Adventure
A work-in-progress chess bot written in C#
Chess Coding Adventure is an educational project that walks developers through the process of building a chess engine from scratch, focusing on understanding the underlying algorithms and logic. It is structured as a series of lessons or stages, each introducing key concepts such as move generation, board representation, and search algorithms. The project emphasizes learning by doing, encouraging users to implement features step by step rather than relying on prebuilt solutions. It also... -
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CS Notes
Essential knowledge for technical interviews, Leetcode, and OS
CS-Notes is a comprehensive, community-driven collection of study materials and technical notes for computer science students and professionals. Created by CyC2018, the repository consolidates essential computer science topics, algorithm solutions, and interview preparation materials in one well-organized resource. It covers a broad range of subjects, including data structures, algorithms, operating systems, networks, databases, and Java development. The repository also includes sections on... -
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XUI
A simple and elegant Android native UI framework
XUI is a lightweight Android native UI framework that provides a comprehensive set of components and design styles to simplify mobile interface development. It aims to reduce the complexity of building Android UIs by offering a unified and consistent design system with ready-to-use components. The library includes a wide range of UI elements such as buttons, text inputs, dialogs, pickers, navigation bars, and more, covering most common development needs. It is designed to be easy to... -
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CSS Refresher Notes
Refresher of CSS concepts
CSS Refresher Notes is a comprehensive set of notes intended to help web developers revisit and solidify their understanding of core and advanced CSS concepts, organized as an approachable reference guide rather than a full textbook. The content spans foundational topics like positioning, display types, selectors, layout techniques, and box model intricacies, to more modern CSS capabilities such as media queries, responsive design principles, transitions, animations, and scalable vector... -
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Front-end development blog
Front-end Development Thoughts
Front-end development blog is a front-end development article repository focused on JavaScript, ES6, React, Redux, and related web engineering topics. It works as a curated index of essays rather than a traditional software package. The repository collects technical thinking on subjects such as AI in development, VS Code history, React Conf, JavaScript number behavior, server-side versus client-side rendering, and React best practices. It also includes articles about CSS Modules, Immutable... -
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Lisp Koans
Common Lisp Koans is a language learning exercise
Lisp Koans is a self-guided learning path for Common Lisp that teaches the language’s idioms through a series of failing tests you progressively make pass. Each koan introduces a concept—symbols, lists, macros, multiple dispatch, reader syntax—then asks you to fill in the blanks and run the suite again. The feedback loop is intentionally tight: fail, reflect, fix, and rerun until the tests become a form of living documentation. Because koans are organized from fundamentals to... -
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Git Tips
Compact knowledge base of Git command tips and workflows
git-tips is a compact knowledge base of Git command tips and workflows designed to be quickly searchable and easy to memorize. It favors short, actionable examples that solve common problems like amending commits, cleaning branches, rewriting history, bisecting, stashing, or recovering lost work. Each tip shows the exact command and a brief explanation, reducing time spent digging through manual pages. The collection is useful for daily development, code reviews, and release management where... -
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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learn-machine-learning-in-two-months
Essential Knowledge for learning Machine Learning in two months
The learn-machine-learning-in-two-months repository is an educational open-source project designed to guide beginners through the process of learning machine learning and deep learning concepts within a structured two-month study plan. The project compiles curated resources, tutorials, and practical notebooks that introduce fundamental topics such as mathematics for machine learning, Python programming, and essential libraries like NumPy and TensorFlow. It progressively moves from... -
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Pattern Recognition and Machine Learning
Repository of notes, code and notebooks in Python
Pattern Recognition and Machine Learning is an open-source repository that provides Python implementations and interactive notebooks for algorithms presented in the book Pattern Recognition and Machine Learning by Christopher Bishop. The project recreates many of the mathematical concepts and diagrams from the book using executable Jupyter notebooks, allowing readers to experiment directly with the algorithms described in the text. Each section of the repository corresponds to chapters in... -
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ISLR-python
An Introduction to Statistical Learning
ISLR-python is an educational repository that provides Python implementations and notebooks corresponding to examples and exercises from the book An Introduction to Statistical Learning. The project recreates tables, figures, and laboratory exercises originally presented in the book so that readers can explore the concepts using Python rather than the original R environment. The repository includes Jupyter notebooks demonstrating statistical learning methods such as linear regression,... -
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Monix
Asynchronous, Reactive Programming for Scala and Scala.js
Monix is a high-performance, reactive, and asynchronous programming library for Scala and Scala.js. Built as a Typelevel project, it provides advanced abstractions like Task, Observable, Iterant, and Coeval, enabling compositional, back-pressure‑aware event-driven systems that integrate cleanly with Cats Effect and Reactive Streams. -
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Tech Interview Handbook
Curated coding interview preparation materials
Tech Interview Handbook is a curated, mostly self-contained compilation of technical interview preparation resources—including algorithms, system design, resume tips, and behavioral questions—crafted for busy software engineers. The information in this repository is condensed. Ultimately, the key to succeeding in technical interviews is consistent practice and I don't want to bore you with too many words. I tell you the minimum you need to know on how to go about navigating the interview... -
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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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LeetCode
LeetCode Problems' Solutions
LeetCode is a long-running repository of solutions to LeetCode programming problems. It is organized as a study and reference collection for algorithm practice, technical interview preparation, and problem-solving review. The repository includes implementations for many classic coding challenge categories such as arrays, strings, linked lists, trees, graphs, dynamic programming, sorting, searching, and math. It is useful for comparing approaches, reviewing solution patterns, and studying how... -
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PyTorch Handbook
The pytorch handbook is an open source book
PyTorch Handbook is an open-source educational project designed to help developers and researchers quickly learn deep learning using the PyTorch framework. The repository functions as an online handbook that explains how to build, train, and evaluate neural network models using PyTorch. It includes tutorials and examples that demonstrate common deep learning tasks such as image classification, neural network design, model training workflows, and evaluation techniques. The material is written... -
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Functional-Light JavaScript
Pragmatic, balanced FP in JavaScript
Functional-Light JavaScript is an online book that teaches functional programming principles through a pragmatic JavaScript lens. Instead of insisting on strict purity, it adopts a balanced approach that keeps code practical while showing how immutability, composition, and declarative thinking improve quality. Chapters build up from values and closures to higher-order functions, list operations, transducing, and async patterns, all grounded in idiomatic JS. The writing favors intuition and... -
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Fira Code
Free monospaced font with programming ligatures
Fira Code is a free and open source monospaced font containing programming ligatures for the most commonly-used multi-character combinations in programming. Programmers use a lot of symbols that are encoded through a series of characters. Often these symbols are quickly done and overlooked, causing errors due to spacing, etc. Fira Code helps solve such problems. While all programming languages should be designed with full-fledged Unicode symbols for operators, such is not yet the case. Until... -
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go-fundamental-programming
Set of video and voice tutorials for the Go language
go-fundamental-programming is the code and notes repository for the Chinese video course, a foundational Go programming tutorial aimed at beginners. The author positions it explicitly as a way to share the knowledge and pitfalls accumulated while learning Go, so that new learners can avoid common mistakes and weird corner cases. The course is delivered as a series of lectures, and each lecture has a dedicated lectureX.md file that serves as classroom notes, listing the knowledge points... -
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Deeplearning.ai
Study notes, summaries, and auxiliary materials for deep learning
Deeplearning.ai collects study notes, summaries, and auxiliary materials aligned with the popular deep learning course series many learners take early in their AI journey. It distills core ideas such as optimization, regularization, convolutional networks, sequence models, and practical training tricks. The explanations aim to bridge theory and practice, often connecting mathematical intuition to code-level implications. By organizing the content as “books” or structured notes, it gives... -
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TensorFlow Examples
TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)
TensorFlow Examples is a comprehensive repository of example implementations, tutorials, and reference code intended to help newcomers and intermediate learners dive into TensorFlow quickly. It contains both Jupyter notebooks and raw source code, covering a broad range of tasks: from basic machine-learning and neural-network models to more advanced use cases, using both TensorFlow v1 and v2 APIs. For clarity and educational value, each example is accompanied by explanatory comments or... -
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Machine Learning & Deep Learning
machine learning and deep learning tutorials, articles
Machine Learning & Deep Learning Tutorials is an open-source repository that provides practical tutorials demonstrating how to implement machine learning and deep learning models using popular frameworks such as TensorFlow and PyTorch. The project focuses on helping learners understand machine learning through hands-on coding examples rather than purely theoretical explanations. Each tutorial walks through the process of building and training models for tasks such as image classification,... -
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Vue.js Analysis
Vue.js source code analysis
Vue.js Analysis is an open-source Chinese ebook and companion learning resource that analyzes the Vue.js source code in depth. It was created to help learners understand Vue’s implementation principles in a more systematic way than scattered blog posts. The project focuses on Vue 2.x internals, including initialization, reactivity, virtual DOM, component rendering, template compilation, lifecycle behavior, and related architectural ideas. It is connected to a paid video course but keeps the... -
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ml-design-patterns
Source code accompanying O'Reilly book: Machine Learning Design
The ml-design-patterns repository contains the source code and examples that accompany the book “Machine Learning Design Patterns,” providing practical implementations of reusable solutions for common challenges in machine learning systems. It organizes patterns into categories such as data representation, problem framing, and model training, helping practitioners understand how to structure ML pipelines effectively. The repository includes implementations of techniques like feature hashing,...
