The article discusses technical debt, its various types and effective management strategies. It also outlines methods for measuring technical debt, including the use of code quality tools, maintaining a technical debt backlog, and employing metrics: Top Types of Technical Debt and Effective Solutions

This guide will help a programmer understand how to setup a simple load balancer to demonstrate the basic principal whilst coding.

System Design Part 1: Setup a Simple Load Balancer using Python

The technologies to demonstrate are:

• Docker
• NGINX
• Python

The guide below explores end-to-end (E2E) software testing, emphasizing its importance in validating the complete code functionality and integration - how E2E testing simulates real-world user scenarios, contrasting it with unit and integration testing, which focus on isolated parts of the code: End-to-End Software Testing: Overcoming Challenges

The testing pyramid emphasizes the balance between unit tests, integration tests, and end-to-end tests. The guide below explores how this structure helps teams focus their testing efforts on the most impactful areas: Implementing the Testing Pyramid in Your Development Workflows

• UI tests
• E2E tests
• API tests
• Integration tests
• Component tests

The article discusses prominent software testing communities to enhance tester's professional journey: 15 Online Communities for Testers You Must Join

• Ministry of Testing
• The Test Tribe
• Selenium Community
• AST (Association for Software Testing)
• EuroSTAR Huddle
• LambdaTest Community
• Cucumber Community
• Test Masters Academy
• Automation Testing Community
• TechWell Hub
• New Relic
• Cypress Gitter Community
• Telerik Testing Community
• QCommunity
• Testing Tech News (TTN)

Example, Company Goal: Migrate data warehouse to public cloud to enhance scalability, reduce infrastructure costs, and improve analytics capabilities

Map DevOps Goals to Company Objectives:

• Focus on improving deployment speed, system reliability, and cost efficiency during the migration.

How many people use ChatGPT, Claude.ai, and Cursor to generate boilerplate in DevOps?

Example: write a sample pipeline and then modify it; write a sample terraform module and then modify it, etc. 

How many people use ChatGPT, Claudi.ai, to write articles (at least boilerplate) and then modify them to demonstrate their ideas? 

Hey all, I’m curious about your experiences working with software agencies. What’s worked well? What hasn’t? How do you manage communication, team alignment, and project expectations? Any red flags you’ve noticed or tips for a smoother partnership?

Howdy Reddit!!

i made my spotify recommendations system which is a huggingface spaces app allowing you to generate recommendations based on the music taste you have, steps on how to use it :-

https://huggingface.co/spaces/krishnendughosh/Spotify-Recommendations-System (heres the link)

a)first you need to login to your spotify account after which you will get a callback url which you need to copy paste in the interface to initiate the app

b)you get 5 songs on which u can base the generations off, minimum songs you can add is 1 maximum is 5

c)after this step you can choose on how many songs generated playlist you want, the default or minimum is set to 5 songs

c)then you click the generate recommendations button creating the playlist which will be shown first to you where you can overview all the songs (generated+added) in the form of spotify preview letting you listen to all the songs for a amount of time.

d) you can name it a designated playlist name you want which will form a spotify playlist whose link will be provided after all the above steps

e) enjoy your musical adventure

i have also provided a video demo which you can view on youtube the link is given on this (ps: the choosing number of recommendations feature is yet not added in the video meanwhile it is present now)

https://youtu.be/OAxsvKLg0BM?si=QnznFqE8dIGyjUUn

drop down suggestions and queries in comments

hmu if you guys are interested in my newsletter containing weekly updates about this and more stuff

here's my github profile if you wanna see it
https://github.com/6069krish

The guide below provides a software testing podcast collection, providing expert insights to stay up to date on the latest trends on different aspects of testing: Best 10 Software Testing Podcasts in 2024

• Functional Testing Podcasts (Test & Code, The Testing Show)
• Automation Testing Podcasts (Automation Awesomeness, TestGuild)
• Performance Testing Podcasts (PerfBytes, STP Radio)
• Quality Assurance and Best Practices Podcasts (The QA Lead, Testing Peers)
• Security Testing Podcasts (Application Security, Security Weekly)

The comparison below discusses the best coding AI copilots for 2024 - as advanced tools that assist developers throughout the software development lifecycle by providing real-time code suggestions and completions (which distinguishes them from regular coding AI assistants that may only offer task-specific support): 4 Best Coding AI Copilots for 2024

It explains the key benefits of these copilots as increased efficiency, error reduction, consistent code quality, and natural language processing.

The article discusses best practices and various aspects of software testing, to provide a comprehensive checklist to ensure effective testing processes: Software Testing Best Practices Checklist

• Test Planning
• Test Design
• Test Execution
• Defect Management
• Continuous Improvement

Join the Pujo Atlas Project: Calling Flutter, Django, and Web Developers!

At r/kolkata, we’re building Pujo Atlas—an app that will be a go-to resource for Pujo enthusiasts and pandal hoppers. This app will guide users to notable Durga Puja pandals across the city, helping them explore Kolkata's rich cultural heritage during the festivities.

Current Challenge

While we’ve made significant progress on the UI/UX front, our frontend and backend development is lagging due to a lack of dedicated developers. We need contributors with expertise in Flutter (frontend) and Django (backend) to help push the project forward.

What We’re Looking For

Backend (Django, Python):

• Strong knowledge of Django and Python for backend services.

Frontend (Flutter/Dart):

• Experience building cross-platform mobile apps using Flutter.

DevOps (AWS):

• Familiarity with setting up and maintaining services on AWS.

UI/UX:

• Experience working with Figma, Material 3 Design, and optionally Apple Human Interface Guidelines.

Web Development (React & TypeScript):

• Tech stack: React, TypeScript
• Nice-to-have: Familiarity with Git, Astro, Tailwind, and Leaflet
• Level: Beginner in React & TypeScript, but with a solid understanding of JavaScript. Should have experience building mobile-responsive web apps with React.

Incentives

Pujo Atlas is an FOSS project, so while we cannot provide monetary compensation, we will offer recognition and credits for your contributions. In the future, we hope to distribute physical tokens to contributors, which can be showcased in various social settings to acknowledge your affiliation with the project.

GitHub Repo: Pujo Atlas Frontend

Interested?

If this project resonates with you and you’d like to be part of this journey, feel free to DM me for an invite link! Also, if you have any questions, don’t hesitate to ask in the comments.

Signing off,
u/suspicious-tooth-93

Hey everyone!

I’m excited to introduce FetchPHP, a lightweight and open source HTTP library for PHP, directly inspired by JavaScript’s fetch API. It simplifies making HTTP requests in PHP while providing both synchronous and asynchronous support, making it perfect for API requests, file uploads, and more.

Key Features:

• Synchronous and Asynchronous Support
• Simple API, inspired by JavaScript’s fetch
• Handles JSON, Multipart, Form Data with ease
• Status Helpers like ok(), isClientError(), and isServerError()

Check it out on GitHub! I’d love your feedback and suggestions. If you find it useful, consider giving the project a ⭐️ to support further development. 🙌

🔗 GitHub Repository: Link to the project

Thanks for reading 😊

This article provides an overview of various tools that can help developers improve their testing processes - it covers eight different automation tools, each with its own strengths and use cases: Python Automation Tools for Testing Compared - Guide

• Pytest
• Selenium WebDriver
• Robot Framework
• Behave
• TestComplete
• PyAutoGUI
• Locust
• Faker

The article discusses strategies to improve software testing methodologies by adopting modern testing practices, integrating automation, and utilizing advanced tools to enhance efficiency and accuracy in the testing process. It also highlights the ways for collaboration among development and testing teams, as well as the significance of continuous testing in agile environments: Enhancing Software Testing Methodologies for Optimal Results

The functional and non-functional testing methods analysed include the following:

• Unit testing
• Integration testing
• System testing
• Acceptance testing
• Performance testing
• Security testing
• Usability testing
• Compatibility testing

The article below discusses the differences between alpha testing and beta testing - the goals, processes, and importance of both testing phases in ensuring software quality. It explains how alpha testing is typically conducted by internal teams to identify bugs before the product is released to external users, while beta testing involves a limited release to external users to gather feedback and identify any remaining issues: Alpha Testing vs. Beta Testing: Understanding Key Differences and Benefits

It's pretty simple actually. You can basically transform any website into a Progressive Web App that can later be distributed on App Store and Google Play. It's awesome, you can send push notifications, pre cache assets, fetch data in the background and hook into native APIs of the devices. Here is a Laravel tutorial that can be applied in any stack: https://youtu.be/xA9B2hwA1-w?si=qv8rmQDUGtiN8Dtt

The article discusses various testing tools that are commonly used in DevOps workflows. It provides an overview of the following popular tools for different types of testing (unit, integration, performance, security, monitoring) to help choose the right testing tools for their specific needs and integrate them: 9 Best DevOps Testing Tools For 2024

• QA Wolf
• k6
• Opkey
• Parasoft
• Typemock
• EMMA
• SimpleTest
• Tricentis Tosca
• AppVerify

This article discusses various strategies and best practices for reducing test automation execution times: Best Ways to Reduce Test Automation Execution Times

It covers techniques such as parallel test execution, test prioritization, and optimizing test environments to improve the overall speed and effectiveness of automated testing workflows, etc.

The article discusses the best test management tools available for software development and quality assurance. It provides an overview of the following tools - how they help teams plan, execute, and track testing processes efficiently: 10 Best Test Management Tools For 2024

1. TestRail
2. Xray
3. Tricentis qTest
4. Tuskr
5. Testiny
6. TestMonitor
7. aqua ALM
8. Micro Focus Silk Central
9. QMetry
10. Katalon

The article below provides an in-depth overview of conformance testing for ensuring that software systems adhere to specified standards and requirements: Conformance Testing for Software

It outlines the various approaches to conformance testing, including formal methods, model-based testing, and automated testing techniques as well as discusses its best practices, such as creating a clear testing strategy, utilizing appropriate tools, and ensuring thorough documentation.

The article discusses the best CI/CD tools for DevOps, its role in automating the software development process, improving code quality, and accelerating the release cycles - their features, benefits, and use cases, providing insights into how they can enhance DevOps practices: The 11 Best CI/CD Tools For DevOps

1. Jenkins
2. GitLab
3. CircleCI
4. TravisCI
5. Bamboo
6. TeamCity
7. Azure Pipelines
8. AWS CodePipeline
9. GitHub Actions
10. ArgoCD
11. CodeShip

The guide explores common use cases for testing documentation, such as verifying API documentation, testing installation guides, and validating user manuals as well as best practices for testing documentation, including using automated tools, conducting regular reviews, and involving cross-functional teams: Testing Documentation: Benefits, Use Cases, and Best Practices

In Feb 2024, Meta published a paper introducing TestGen-LLM, a tool for automated unit test generation using LLMs, but didn’t release the TestGen-LLM code.The following blog shows how CodiumAI created the first open-source implementation - Cover-Agent, based on Meta's approach: We created the first open-source implementation of Meta’s TestGen–LLM

The tool is implemented as follows:

1. Receive the following user inputs (Source File for code under test, Existing Test Suite to enhance, Coverage Report, Build/Test Command

Code coverage target and maximum iterations to run, Additional context and prompting options) 2. Generate more tests in the same style 3. Validate those tests using your runtime environment - Do they build and pass? 4. Ensure that the tests add value by reviewing metrics such as increased code coverage 5. Update existing Test Suite and Coverage Report 6. Repeat until code reaches criteria: either code coverage threshold met, or reached the maximum number of iterations

I wrote down the story https://flakm.com/posts/phantom_leak/ of a frustrating debugging journey with a rust application that was migrated to Kubernetes.

Everything seemed fine until a suspected memory leak caused our application to scale uncontrollably. I dove deep into tracing memory usage with eBPF, heaptrack, and jemalloc profiling tools.

The real twist came when I discovered that the memory leak was a phantom menace - a misinterpretation of Kubernetes memory metrics rather than a genuine issue.

This post details the steps I took, the tools I used, and the lessons I learned about problem-solving, metric accuracy, and effective debugging in containerized environments.

The article below highlights various tools that can help ensure the functionality, performance, and security of web applications - their features, and how they can be utilized in the development process to improve software quality: 8 Best Web Apps Testing Tools

• TestComplete
• Selenium
• Katalon Studio
• Ranorex Studio
• BugBug
• Mabl
• Zed Attack Proxy
• Tricentis Testim

The article explains the importance of QA automation in the software development process as well as delves into a detailed analysis of five popular Ai-driven automation tools, highlighting their features, advantages, and potential drawbacks: 5 Best QA Automation Tools For Software Testing

• CodiumAI
• TestRigor
• Tricentis Tosca
• Avo Assure
• EndTest

The guide below presents a detailed code review checklist covering various aspects such as code functionality, readability, maintainability, security, and performance - to help developers and teams improve their code review process: Elevating Code Quality: The Ultimate Code Review Checklist

The article below highlights various tools that can help ensure the functionality, performance, and security of web applications - their features, and how they can be utilized in the development process to improve software quality: 8 Best Web Apps Testing Tools

• TestComplete
• Selenium
• Katalon Studio
• Ranorex Studio
• BugBug
• Mabl
• Zed Attack Proxy
• Tricentis Testim