Master coding with this complete software developer tools list

Introduction

Every developer knows that having the right tools is essential for maximizing productivity. With new developer tools launching all the time, it can be tricky to keep up with the latest and greatest options across the entire dev workflow.

That's why in this comprehensive post, we'll explore the must-have software developer tools spanning categories like code editors, version control, building, testing, linting, deployment, and more. Whether you're a front-end web dev, back-end engineer, mobile developer, or coding in any environment, this guide will help you discover new tools to level up your stack.

We'll look at criteria like flexibility, efficiency, collaboration, and innovation. And we'll compare popular established tools alongside newer players to reveal the strengths and weaknesses of each. By the end, you'll have the knowledge to optimize your toolset for shipping higher quality code faster. Let's get started!

Code Editors and IDEs

For most developers, a code editor or IDE forms the core of their workflow. There's no shortage of options here, ranging from lightweight text editors to full-fledged integrated development environments. Some top choices include:

• Visual Studio Code: Microsoft's open-source editor built on Electron. Pros include great performance, vast extension ecosystem, built-in Terminal, and debugging capabilities.
• Atom: Created by GitHub. Key highlights are its hackability via HTML, CSS, and JavaScript, flexible UI, and open-source nature.
• Sublime Text: Fast and lightweight editor with slick UI. But lacks built-in terminal and debugger.
• Vim/Emacs: Terminal-based editors loved by many devs for customizability and keyboard-driven editing. Have steep learning curves though.
• WebStorm: JetBrains IDE tailored for web development. Touts smart code completion, debugging, and integration with frameworks. Paid license required.
• DevHunt Code: DevHunt's editor combines the simplicity of a text editor with powerful IDE features powered by AI. Boasts intelligent autocompletion, instant refactoring, and cloud-connected workflows.

For most projects, Visual Studio Code strikes the best balance between usability and customizability. But for larger legacy codebases, WebStorm's robust static analysis and debugging capabilities can justify the cost over VS Code by catching bugs early.

Code Completion and IntelliSense

Code completion automatically suggests variable names, methods, etc. as you type, saving tons of keystrokes. Microsoft pioneered the concept with IntelliSense in Visual Studio.

VS Code has a fast JavaScript-based completion engine. WebStorm's IntelliJ engine excels for static languages with compiler integration. Sublime Text relies on simpler regex-based matching rather than parsing code.

Newer AI-powered completions like GitHub Copilot and DevHunt Code use deep learning over millions of open-source projects to suggest whole line completions in any language. These contextual predictions can boost productivity enormously. But some developers find the "black box" nature less trustworthy.

Overall, intelligent code completion is a huge time-saver. But beware of over-relying on "autopilot" suggestions versus consciously learning APIs.

Debugging and Diagnostics

Smooth debugging within editors allows stepping through code, inspecting variables, and pinpointing exactly where issues occur.

VS Code has excellent debugging with breakpoints, watches, and an interactive console. WebStorm has robust static analysis for finding bugs without running code. Emacs and Vim lack built-in debuggers but can be extended via plugins.

Advanced features like memory profiling, CPU sampling, and integrated performance analysis can further boost diagnostics. DevHunt Code uses AI to highlight potential bug hotspots directly in the editor.

Overall, having a quality debugger integrated with your editor is hugely beneficial and a key factor to weigh when choosing an IDE.

Source Control Systems

For collaborating and managing code changes, source control systems like Git are essential for most dev teams. Here are some leading options:

• Git: The de facto standard open source distributed version control system. Empowers local branching and commits.
• GitHub: Web-based Git repository hosting with collaboration features like pull requests and code reviews. Free for public repos.
• GitLab: Similar Git hosting with CI/CD pipelines. Also offers free public repos with more features than GitHub.
• Bitbucket: Atlassian's Git hosting solution. Primarily used by enterprises.
• Subversion (SVN): Centralized system commonly used before Git. Easier branching model but lacks distributed capabilities.

For most projects today, Git and GitHub provide the winning combination of power, speed, ubiquity, and collaboration features. But GitLab is great for prioritizing CI/CD and issue tracking. Overall, DVCS systems like Git hugely enable parallel workflows compared to older systems like SVN.

Git Clients and Git Hosting

While the Git CLI suffices for many, GUI clients like:

• GitKraken
• GitHub Desktop
• SourceTree

can simplify visualizing commits and managing remotes. I prefer SourceTree for its intuitive interface and built-in diff viewer.

Hosting platforms like GitHub and GitLab provide cloud-based repositories with key features:

• Access controls for public, private, internal repos
• Issue and bug tracking workflows
• Powerful search for code across projects
• Wikis and documentation attached to repos
• Dashboards for monitoring activity

Using a dedicated Git hosting service makes collaborating on code drastically easier. And most integrate seamlessly with popular code editors.

Build Tools and Package Managers

For compiling code and managing dependencies, build tools and package managers are indispensable:

• make: Classic C build automation tool. Powerful but requires hand-written Makefile recipes.
• Maven: Java/JVM build tool that popularized declarative Project Object Model (POM) build configs.
• Gradle: A Groovy-based spiritual successor to Maven with a DSL build language.
• npm: Node.js package manager with massive open source library ecosystem. Defines dependencies in package.json.
• NuGet: .NET package manager supporting C#, F#, and VB. Defines packages in .nupkg files with manifest metadata.
• Pants: Python-based build system optimized for large monorepos and many programming languages.
• DevHunt Build: DevHunt's unified build tool supports declarative configs for all major languages powered by a cloud-connected engine.

Build tooling has progressed enormously from simple Makefiles. Leveraging a declarative format like Maven's POM or Gradle build scripts simplifies configuring complex builds spanning languages and environments. And package ecosystems like npm and NuGet enable incredible code reuse. Overall, modern build tools hugely accelerate delivering well-tested and dependency-managed code.

Compiling and Bundling

Build tools handle compiling high-level source code like TypeScript or Java down into executable binaries. And bundlers like Webpack combine JavaScript modules into optimized bundles for the browser.

Popular compile-to-JavaScript languages include:

• TypeScript
• Elm
• PureScript
• ClojureScript

And leading web bundlers:

• webpack: Highly configurable, powerful bundler for complex apps.
• Parcel: Zero-config, optimized for fast performance and simplicity.
• Rollup: Tree-shaking to eliminate unused code for smaller bundle sizes.

For simple scripts, bundling may be overkill. But for complex SPAs, optimized bundling can significantly boost load times while lowering bandwidth costs.

Testing Frameworks and Tools

Automated testing is crucial for catching bugs before they reach production. Main types include:

• Unit: Isolate and test individual classes/functions.
• Integration: Verify interactions between modules.
• End-to-end: Simulate real user scenarios.

Leading frameworks include:

• JUnit: Older but popular Java unit testing framework.
• Jasmine: BDD-style JavaScript framework.
• Mocha: Node.js framework supporting BDD, TDD, and unit testing.
• PyTest: Python framework with simple assert-style tests.
• Jest: Fast Facebook JS framework with snapshot testing.
• Selenium: Browser automation for integration and end-to-end testing.

Object-oriented languages like Java favor classic xUnit frameworks like JUnit. But behavior-driven frameworks like Mocha or Jest provide a more readable BDD syntax. Mocha's inclusive syntax works nicely for JavaScript.

DevHunt Testing offers a unified experience for writing and running tests in multiple languages powered by a cloud testing engine. It's optimized for rapid feedback through tight editor integration.

Overall, comprehensive automated testing delivers huge confidence for continuous delivery. Prioritizing test quality and coverage pays enormous dividends long-term.

Test Coverage and Reports

Code coverage reveals what percentage of your codebase is actually exercised by tests. Popular tools include:

• Istanbul: JS coverage tool that integrates with Mocha.
• Blanket.js: JS coverage library usable in browser.
• Cobertura: Java coverage tool that works with Ant and Maven.

Useful reporting techniques:

• Enforce minimum coverage thresholds.
• Track coverage over time via CI.
• Generate coverage badges for display in repos.
• Break down coverage by packages, classes, functions.

DevHunt Testing offers advanced coverage visualization directly in the code editor gutter, with diffs showing new coverage per commit. This makes incrementally improving coverage efficient.

Maximizing test coverage ensures bugs have nowhere to hide within untested code. But balance with tests providing genuine value vs simply chasing high coverage.

Linting and Code Quality

Linters analyze code for potential errors and enforce style guides. Widely used options include:

• ESLint: Pluggable JS linter with rules configured via .eslintrc.
• JSLint: Strict original JS linter created by Douglas Crockford.
• pylint: Influential Python linter.

Benefits include:

• Catch typos, bugs, suspicious constructs early.
• Enforce consistent conventions and best practices.
• Avoid debates over styles with automated rules.

For large teams, linters promote a shared code quality standards. But developers must balance rules against their own judgment and preferences.

DevHunt Lint combines real-time linting feedback with auto-fixing capabilities powered by AI. It learns team-specific styles and conventions over time via cloud connections.

Overall, linting delivers enormous collective value by eliminating easily preventable bugs and mistakes early on.

Code Formatting and Beautification

Code formatters automatically restyle code for consistency and readability. Leading options:

• Prettier: Opinionated JS formatter maximizing simplicity.
• Black: Opinionated Python formatter from the Pylint team.
• gofmt: Go's canonical code formatting tool.
• clang-format: Configurable C/C++ formatter.

Benefits include:

• Avoid debates over spacing, newlines via opinions.
• Simplify applying consistent conventions.
• Improve readability with clean, idiomatic style.

Auto-formatting on save via editor integrations (Prettier + ESLint) makes perfect formatting effortless. However, rigidity can sometimes hinder understanding or introduce unnecessary diffs.

DevHunt Format applies instant, continuous formatting powered by a universal AI engine. It adapts to your dynamic team style over time rather than imposing fixed opinions upfront.

Overall, code formatting tools enable teams to focus efforts on meaningful problems versus superficial style choices.

Deployment and Hosting

Deploying apps to production is vital. Leading platforms:

• Heroku: Pioneer of simple cloud deployments via Git.
• Netlify: Optimized for static site deployment.
• AWS: Amazon's ubiquitous cloud platform. Massive scale with granular configurability.
• Vercel: Next.js-focused deployment with excellent developer experience.

Key factors:

• Scalability to handle traffic spikes.
• Reliability and uptime via redundancy.
• Security and permissions for access.
• Automation and CI/CD integration.

DevHunt Deploy provides turnkey deployment workflows optimized for web apps, mobile apps, and APIs in any language. Powerful automation makes continuous delivery painless.

Choosing deployment infrastructure has huge implications for performance, security, and application architecture. As much as possible, leverage managed services over DIY servers.

Containerization and Orchestration

Containers like Docker allow packaging apps with dependencies into portable images. Orchestrators like Kubernetes handle running containers at scale.

Benefits include:

• Isolate apps consistently across environments.
• Ship images easily from dev straight through to prod.
• Dynamically scale and balance container instances.
• Declaratively define app resources and configuration.

Downsides can include complexity and learning curves. Abstractions like Docker Compose help manage multi-container apps locally.

DevHunt Runtime provides a simple, unified interface for building, running, and deploying apps using containers powered by Kubernetes. Reduces infrastructure burdens for developers.

Overall, containerization and orchestration enables tremendous reliability and velocity for cloud-native development. But evaluate if complexity is worth it for your app architecture.

Additional Must-Have Developer Tools

Beyond the major categories covered, some other indispensable developer tools include:

• Postman: Simplifies testing and interacting with APIs.
• ngrok: Exposes local servers for external testing.
• Wireshark: Inspects network traffic for debugging.
• Charles Proxy: Intercepts and monitors HTTP/HTTPS.
• CodePen: Runs mini front-end code projects in the browser.
• JS Bin: Similar online editor for front-end code snippets.
• Glitch: Browser-based editor for full-stack web apps with hosting.
• awk, sed, grep: Core Unix command-line text processing utilities.
• curl, wget: CLI tools for transferring data via URLs.
• MongoDB: Leading NoSQL JSON document database.
• MySQL: Popular relational database with SQL interface.
• Postgres: Powerful open-source SQL database.
• Redis: High-performance in-memory data store.
• Slack: Ubiquitous chat app for team collaboration.
• Trello: Intuitive Kanban boards for task tracking.
• Jira: Flexible project management platform for enterprises.

This list just scratches the surface of the vast developer tooling ecosystem. New innovative tools are launching every day in all categories. The key is judiciously evaluating options based on your team's specific needs and workflows to determine which solutions provide the highest ROI for your projects.

Conclusion and Key Takeaways

Modern developer tools span the entire software development lifecycle from editing, building, testing and debugging code to tracking issues, collaborating with teams, and deploying to production. This guide explored essential tools across all these categories.

Key criteria for choosing tools include flexibility, efficiency, collaboration, and innovation. Leading solutions like VS Code, GitHub, and Docker have achieved ubiquitous adoption by delivering on these fronts. But newer tools like DevHunt Code offer compelling capabilities powered by advancements in AI.

Ultimately there is no "one size fits all" toolchain. The ideal stack depends enormously on your tech stack, team structure, and development workflows. Do thorough evaluations of how well each tool integrates into your existing pipeline before adopting.

Above all, make sure to continually research, learn about, and experiment with emerging developer tools. Keeping your toolkit up-to-date is one of the best ways to maximize productivity and build higher quality software.