Testing resources for developers

A nine-stage path for securing LLM apps and AI agents, or testing them as a red-teamer, with one path for each: security foundations, how LLM apps break, the OWASP LLM and agentic lists and MITRE ATLAS, layered defences against prompt injection, agent, tool and MCP security, the data and model supply chain, red-teaming and security evals, monitoring and incidents, and a route into the work. It suits developers and security learners who can already build. By the end you have a practice app defended or assessed end to end.

• AI
• Security
• Testing
• Career

A browser-based simulator for Arduino, ESP32, STM32 and Raspberry Pi Pico projects: wire parts on a virtual breadboard, run your firmware and even connect a simulated ESP32 to Wi-Fi. Great for learning before your board arrives and for sharing a reproducible project when you ask for help. Free plan available.

• Testing

The largest community built around software testing: a free forum called The Club, articles, local meetups, conferences and a job board, plus paid on-demand courses and certificates. A free Basic account is enough to ask questions, read discussions and find events, and it is where many testers learn how the craft works in real teams.

• Career
• Testing

A seven-stage plan from how the web works to a shipped product: HTML and CSS, JavaScript and the browser, Git and build tooling, your framework (React with Next.js, Vue with Nuxt, or Angular), TypeScript and testing, performance, accessibility and security, then a real product with real users. It suits beginners, career switchers and backend developers filling in the browser side. By the end you can ship a typed, tested, accessible and fast app, deployed with CI and real people using it.

• Web
• Frontend
• Programming
• Testing

An O'Reilly book from 2020 by Titus Winters, Tom Manshreck and Hyrum Wright on how Google keeps an enormous codebase healthy over time: team culture, code review, documentation, testing at scale, deprecation, dependency management, large-scale changes and continuous delivery. The full text is free to read online. Most rewarding after a year or two of professional work, when the problems it describes start to look familiar.

• Career
• Programming
• Testing
• Leadership

A practical guide to writing tests that catch real bugs and stay cheap to maintain. It covers choosing the right level for each test, unit test design, mocks and other test doubles, integration and end-to-end tests, flaky tests, coverage and mutation testing, and keeping the suite fast in CI. The advice is language agnostic, with examples in TypeScript and Python.

• Web
• Testing
• Programming

A checklist for evaluating LLM features and agents before and after launch. It covers success criteria, building the eval dataset, choosing and calibrating graders, running evals reproducibly, agent and multi-step evals, safety and security tests, and production monitoring, with a severity and a concrete verification step for each check.

• AI
• Testing

A checklist for keeping warehouse and lakehouse tables trustworthy. It covers ownership and expectations, freshness, volume, schema, nulls, uniqueness and valid values, referential and reconciliation checks, anomaly monitoring and handling data incidents, with a severity and a way to verify each check.

• Data
• Testing

A practical guide to CI/CD best practices for teams that ship code through a pipeline. It covers integrating small changes often, keeping the build fast and green, securing workflows and their credentials, building artifacts once with provenance, deploying gradually with canaries and fast rollback, and measuring delivery with the DORA metrics.

• DevOps
• Testing

A revision reference for securing and testing LLM apps and AI agents, in 9 chapters and two editions (app and agent security, red-teaming): security foundations, how LLM apps break, the OWASP LLM and agentic lists, MITRE ATLAS, prompt injection and guard layers, agent, tool and MCP security, the data and model supply chain, red-teaming tools and evals, monitoring and incidents, and career routes. It follows the Sefism AI security roadmap chapter by chapter, with no attack payloads.

• AI
• Security
• Testing

A standalone revision book on evaluating LLM apps and agents, in 10 chapters and 67 concepts: golden datasets, metrics by task type, LLM-as-judge and its biases, RAG and agent metrics, offline, online and CI evals, human review, the main tools as of October 2026 and a starter plan for your first week. It suits developers who change prompts and models and need to know whether things got better. Use it to pick a metric, check a judge and set a CI gate.

• AI
• Testing
• AI agents

A quick-revision reference for ASP.NET Core developers in 10 chapters and 78 to 79 concepts: modern C#, LINQ, async, the dotnet CLI, dependency injection, the middleware pipeline, EF Core pitfalls, auth and the front end, testing and shipping to Azure, and a production checklist with the Program.cs code for each item. It follows the Sefism .NET developer roadmap. Use it to revise after each stage and to check your own API before you call it finished.

• Web
• Backend
• Programming
• Testing

An open source framework for evaluating large language models, built by the UK AI Security Institute. Datasets, solvers, agents, tools and scorers compose into repeatable evals, with sandboxed tool execution, a log viewer and a collection of 200+ ready-made evaluations. A serious tool for safety and security evals of models and agents.

• AI
• Programming
• Testing

A ten-stage roadmap in Java, Python, TypeScript or C#: OOP used properly, SOLID with before and after code, clean code, all 23 classic design patterns, the UML you actually draw, refactoring behind tests, designing small systems such as a parking lot or rate limiter end to end, and code review. For students and early-career engineers whose code works and now needs to stay easy to read, test and change.

• System design
• Programming
• Web
• Testing

A ten-stage roadmap for using Claude Code, Cursor or GitHub Copilot well: what the tools are good and bad at, project context and instructions files, prompting with specs, reviewing every diff, tests first, debugging with evidence, agent permissions and safety, security and licences, keeping your own skills, and shipping a real project with an honest write-up. For students and developers who want the speed without losing the engineering.

• AI
• Programming
• Testing

An 8-stage path from careful manual testing to an automated suite that runs in CI, with Playwright, Selenium or API testing as your chosen tool. It suits students and early-career engineers who want a first role in software quality, and it covers test design, bug reports, HTTP and SQL, programming for testers, maintainable suites, non-functional basics and the QA job search. By the end you have a public portfolio of suites and bug reports and a clear path towards SDET.

• Programming
• Testing
• Career
• Web

Official docs for Testcontainers for .NET, the library that starts real databases, caches and brokers in Docker for your tests and removes them afterwards. Ready-made modules for SQL Server, PostgreSQL, Redis and more. Free and open source under MIT.

• Web
• Programming
• Testing

The companion to the Software design and clean code roadmap in Java, Python, TypeScript and C# editions: OOP used properly, SOLID, clean code, all 23 Gang of Four patterns, the UML you actually draw, refactoring and code smells, small designs end to end, and code review. Each of its 73 concepts is a line or two with a sketch in your language and the classic mistake to avoid.

• System design
• Programming
• Web
• Testing

A quick-revision companion to the Sefism mobile roadmap, from your platform language to shipping in the stores: language essentials, UI and layout, state and navigation, networking and local data, device features and notifications, testing, performance and accessibility, and publishing and releases. It comes in Flutter, React Native, Android (Kotlin and Compose) and iOS (Swift and SwiftUI) editions, each concept with a short snippet and the classic mistake. Read a chapter to refresh a stage, or jump to one concept when you need it.

• Web
• Mobile
• Testing

The companion to the Coding with AI tools roadmap in Claude Code, Cursor and GitHub Copilot editions: what the tools are good and bad at, instructions files and context, prompting with specs, reviewing AI code, tests first, debugging, agent permissions and safety, security and licences, keeping your skills, and shipping a project with an agent. Use it to look up a setting and check your habits before trusting a change.

• AI
• Programming
• Testing

Luca Palmieri's book on backend development in Rust: you build a real email newsletter API from scratch with integration tests, structured logging, error handling, authentication, CI and deployment. The best end-to-end picture of a production Rust service.

• Web
• Backend
• Testing
• DevOps

Kent Beck's short classic on test-driven development: the red, green, refactor loop worked through step by step on real examples, plus the patterns behind it. The best way to learn to write the test first, which is how you keep AI-written code honest.

• Testing

PulseView is the free, open source graphical interface of the sigrok project for logic analysers and oscilloscopes. Paired with a low-cost USB logic analyser, it captures digital signals and decodes UART, I2C, SPI and over a hundred other protocols, so you can see what really happened on the wire.

• Testing

Microsoft's open source framework for red teaming generative AI systems. It helps security engineers organise test runs against a target, transform inputs, score the answers and keep a record of everything, so manual AI red teaming becomes repeatable.

• AI
• Programming
• Testing