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Understanding Condition Coverage in Software Testing

Condition coverage is a type of code coverage that ensures every logical condition in software has been evaluated both to true and false.
Condition coverage helps detect bugs that could go unnoticed with broader metrics like statement or decision coverage.
While decision coverage ensures that the entire decision evaluates to true and false, condition coverage verifies that each individual condition within a decision is independently tested.
Condition coverage helps improve logic validation, defect detection, code confidence, and maintainability.

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Infoq

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JavaOne 2025: Function and Memory Access in Pure Java

Per-ke Minborg presented Function and Memory Access in Pure Java at JavaOne 2025, introducing JEP 454, the Foreign Function & Memory API, as a replacement for JNI.
The JNI workflow involves defining native Java methods, generating C header files, and implementing native methods in C.
Challenges with JNI include limited data support, memory constraints, and inefficient data passing.
The Foreign Memory API allows access to 64-bit addressed memory segments with strict controls on size, lifetime, and thread confinement.
The ValueLayout interface aids in accessing memory segments by specifying carrier type, endianness, and alignment.
FFM provides flexible memory allocation via different arena types like Global, Auto, Confined, and Shared, supporting multi-threaded access.
The MemoryLayout interface simplifies structured access to memory segments, reducing manual offset computation errors.
Minborg showcased examples of using FFM for memory allocation, writes, and structured access in a pure Java paradigm.
jextract, a tool introduced by Minborg, can generate Java bindings from native library headers, enhancing FFM implementation.
Benefits of FFM API include safe memory access, efficient native function calls, and support for structured memory layouts.
Developers can access early-access builds of tools like jextract to leverage the FFM API for improved memory management and function access.

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Medium

407

Coding for Beginners: A Simple Guide to Get Started

Coding is the process of giving instructions to a computer using a language it can understand.
There are many reasons to learn coding, including job opportunities, creativity, problem-solving, and freelance work.
Beginner-friendly languages include HTML/CSS, JavaScript, Python, and Scratch.
Coding might seem hard at first, but with practice and patience, anyone can become a confident coder.

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Dev

192

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AugMix in PyTorch (11)

AugMix() is a function in the torchvision.transforms.v2 module of PyTorch.
It can randomly apply AugMix transformations to an image.
The alpha argument controls the severity of the transformations.
Images with different alpha values are shown using the OxfordIIITPet dataset.

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11 Likes

Dev

210

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Teaching Code in the AI Era: Why Fundamentals Still Matter

Teaching people to code in the AI era requires a balance between fundamentals and AI tools.
The rise of AI coding assistants has made it easier for non-technical people to learn coding, but understanding core programming principles is still crucial.
New graduates have integrated AI tools into their workflow, while experienced developers may struggle to adapt.
Generative AI excels at test generation and code documentation, which traditional programming education often misses.

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Nycdatascience

188

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Machine Learning for Fraud Detection in Healthcare

Healthcare fraud costs billions of dollars annually. Fraudulent providers overcharge insurance, submit inflated claims, or game the reimbursement system.
In this project, a supervised machine learning pipeline was built to identify high-risk providers based on claim-level data, with a focus on accuracy, recall, explainability, and handling class imbalance.
Key features were engineered to reflect billing patterns, visit frequency, and reimbursement behavior, aiming to distinguish honest providers from those likely gaming the system.
XGBoost provided the best tradeoff between precision and recall, making it the recommended model for deployment in fraud detection in healthcare.

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Medium

381

Free Amazon gift card Codes Available!!

Amazon gift cards offer convenience and easy shopping, without the need for a credit card.
They are perfect for gifting, with the option to send them instantly via email or text, or as physical cards.
Most Amazon gift cards do not expire, providing flexibility on when to use them.
They are secure and fraud-proof, reducing the risk of overspending and the need to share sensitive payment details online.

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22 Likes

Medium

171

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Free Cash App Gift Card Codes — Cashapp Gift Card Generator!!

You can send money instantly to friends and family as a "gift" using Cash App.
There's no risk of losing a physical card and the recipient can use the money however they want.
Cash App funds have no expiry or usage limits, providing more flexibility.
Cash Card users can enjoy exclusive discounts and cashback at select stores.

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10 Likes

Dev

285

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How to Use APIs in Your Applications

APIs (Application Programming Interfaces) are the backbone of modern software development.
RESTful APIs, GraphQL APIs, and SOAP APIs are different types of APIs.
To use an API in your application, you need to find and choose an appropriate API, get an API key for authentication, make HTTP requests, and handle API responses.
Best practices for API integration include reading the documentation, securing API keys, using retry mechanisms, and monitoring API performance.

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Medium

166

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Web Scraping with AutoScraper

Web scraping involves automatically collecting data from websites by parsing the HTML structure of web pages.
AutoScraper offers a simple alternative to traditional scraping methods, making it easier for beginners to use.
AutoScraper creates rules based on examples of the data you want to extract, making it unique and efficient.
It is important to practice ethical scraping and follow responsible scraping practices to preserve the health of the web ecosystem.

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Medium

114

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Experimenting with ML: Trying out Different Algorithms for One Simple Task

To create a model for predicting heart disease, the first step is to find and download a dataset, such as the 'Heart Disease Dataset' from Kaggle.
Loading the dataset into an IDE like Google Colab can be done by mounting it from Google Drive to avoid re-uploading.
By using Pandas DataFrame, the dataset is stored and ready for manipulation in the Colab environment.
Data preparation for model training involves splitting the dataset into training and testing sets.
X is set to feature data, while y represents the target column indicating heart disease presence.
Models tested include Logistic Regression, Support Vector Machines, Random Forests, XGBoost, Naive Bayes, and Decision Trees.
Evaluation of model performance shows Random Forest as the most accurate for heart disease prediction in this case.
Different models may perform better based on data complexity and problem type, so experimenting with various algorithms is crucial.
Experimenting with different machine learning algorithms helps in determining the best fit for specific tasks and datasets.
Each machine learning model has its strengths, and the choice of algorithm depends on the problem being addressed.
The article concludes by emphasizing the importance of trying multiple models and tuning hyperparameters to find the optimal solution.

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Medium

249

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Prevent App Redirects: Mastering App Links & HTTP Redirects in React

Universal Links allow seamless transition from website to native iOS app.
Proper configuration of Apple App Site Association (AASA) file is crucial for successful Universal Link implementation.
Handling HTTP redirects is essential when managing user navigation in React and Universal Links.
Thorough testing, debugging, and seeking assistance can help resolve common integration issues.

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Medium

263

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My Winter at the Recurse Center — Return Statement

The author reflects on their experience at the Recurse Center, highlighting projects like Tiles, Yoga with Friends, and Hot Takes.
They aimed to rediscover their passion for programming, improve frontend skills, and engage in meaningful collaborations during their three-month term.
Key projects included Tiles, an app based on the Azul board game, and Hot Takes, a successful game collaboration with a fellow Recurser.
The author also automated their yoga class schedule and attendance using coding, in addition to creating a Lite-Brite-inspired app.
Organizing events like the Dev Tools Show & Tell and a cookie decoration activity showcased the author's community engagement.
At Demopalooza, the author presented projects like Tiles and a game with an AI opponent, fostering engagement among participants.
Engaging in quick three-hour game-building sessions and exploring AI with fellow Recursers were highlights of the author's experience.
Throughout their time, the author experimented with various programming languages and projects, appreciating the intellectually stimulating environment.
Despite some abandoned projects, the author feels grateful for the collaborative and creative atmosphere at the Recurse Center.
Overall, the author expresses gratitude to the Recurse Center for the enriching experience.

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Idownloadblog

416

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Nugget updated to v5.1 with support for importing video files as wallpapers & more bug fixes

Nugget version 5.1 has been released with support for importing video files as wallpapers.
Users can import .mp4 or .mov files, choose to loop videos or have them cover the clock, and videos will automatically scale to the device's resolution.
The update also includes bug fixes, such as improved labels, fixed crashes, and optimized applying PosterBoard tweaks.
Nugget is a non-jailbroken utility that offers system customization options and works on iOS 17.0-18.4 beta.

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25 Likes

Medium

Image Credit: Medium

How Much Monthly Salary Earneth a Python Developer?

The salary of a Python developer varies by region, skill, and market demands.
A junior developer can earn between $3,000 and $6,000 per month, while experienced developers can earn over $10,000 per month.
In the United States and Canada, Python developers can earn upwards of $120,000 per year, approximately $10,000 per month.
Factors such as experience, industry, location, certifications, and specializations influence Python developers' earnings.

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