AI Tools for Developers

AI Tools for Code Completion

In the same fashion that autocorrect or autocomplete works, code completion is a feature that suggests and inserts code snippets as the developer types. It uses the same methodology of anticipating certain code lines and can save time, reduce errors, and improve productivity in a variety of programming languages and environments. 

• • Codex: Codex is a deep learning system that can generate code from natural language descriptions or existing code. It is based on GPT-3, one of the most advanced language models in the world. Codex excels in Python and has remarkable mastery over other languages as well.
• • Replit: Replit is a powerful and versatile IDE that allows you to develop software with the power of AI. It supports over 50 languages and frameworks, and integrates with Codex to provide code completion suggestions. You can also collaborate with other developers in real time and deploy your apps with one click.
• •  AutoRegex: AutoRegex is a strong AI-powered application that uses Natural Language Processing to simplify the development of Regular Expressions (RegEx). RegEx are patterns that match specific strings or characters in text. AutoRegex allows you to write RegEx in plain English and generates the corresponding RegEx code for you.

AI Tools for Code Debugging

The most common frustration found in programming is repeatedly running into dead ends trying to find the cause of errors in logic syntax.  Code debugging is a process that identifies and fixes errors or bugs in software. AI can not only help developers debug their code faster and easier by finding and fixing bugs automatically, but it can also provide suggestions and explanations as to what caused the error.

• • DeepCode - DeepCode is an AI-powered code review tool that analyzes your code in real-time and provides feedback on how to improve it. It can detect bugs, security issues, performance problems, and code smells. It also provides suggestions on how to fix them using best practices and examples from open-source projects.

• • Kite - Kite is an AI-powered coding assistant that helps you write better Python code faster.  It integrates with your favorite editor and provides smart completions, documentation, examples, and error detection.  It also features Line-of-Code Completions, which suggest relevant code snippets based on your context.  Unfortunately, development for this tool has been discontinued, so its usefulness might be short-lived.

• • Bugsee - Bugsee is an AI-powered bug reporting and crash analytics tool that helps you find and fix bugs in your mobile apps faster. It captures video, network traffic, console logs, user events, device details, and more when a bug or crash occurs.  It also provides root cause analysis, issue prioritization, and integration with popular bug tracking tools.  This toolset is primarily aimed towards providing mobile developers for both iOS and Android.

AI Tools for Code Performance

Code performance refers to how well software runs in terms of speed, efficiency, reliability, scalability, etc.  Performance optimization is a process that improves the quality of software by reducing resource consumption, increasing throughput, enhancing user experience, and generally avoiding situations that result in dips in program performance.  AI can help developers optimize their code performance by analyzing data, providing insights, suggesting improvements, and applying changes automatically.

• • Optuna - Optuna is an open-source framework for automated hyperparameter optimization. Hyperparameters are parameters that control the behavior of machine learning algorithms, such as learning rate, number of layers, etc. Optuna helps you find the optimal values for your hyperparameters by using efficient search algorithms and pruning strategies.

• • CodeGuru - AWS’ dedicated service CodeGuru helps improve the performance and quality of any code provided.  It consists of two components: CodeGuru Reviewer and CodeGuru Profiler.  CodeGuru Reviewer scans your code and provides recommendations on how to improve it, such as code readability, security, best practices, etc.  CodeGuru Profiler analyzes your application’s runtime behavior and provides insights on how to optimize it, such as CPU utilization, memory allocation, latency, etc.

• • Lighthouse - Lighthouse is an open-source tool plugin for Chrome that helps improve the performance, accessibility, SEO, and best practices of your web pages. It runs audits on pages and generates reports with scores, metrics, and suggestions on how to improve them. Lighthouse can be run either in Chrome DevTools, from the command line, or as a Node module.

Other AI Tools

There are plenty of companies that produce AI tools for both development and other tasks.  Here are some of the industry leaders worth inspecting for their various tools on offer. 

DataStax

DataStax is a leading company in the development of generative AI and has largely centered itself on empowering different organizations to maximize their potential through the use of generative AI.  They provide open-source solutions and a number of AI tools for NoSQL and Vector databases at scale, generative AI apps that use real-time data, and pipelines for apps and agents. 

Speak With Me

As the name suggests, Speak With Me has designed and provided an advanced, complex conversation bot with much more dynamic capacity than typical language models.  It has a better time emulating emotional range and has the tools to construct image content as well as text.  This model does have much better preservation of context and displays greater ability to adjust and adapt. 

Milvus

Made by Zilliz, Milvus is an increasingly popular open-source vector database for developing AI-powered applications..  It’s AI native, meaning it automatically indexes for better performance, has a multi-language SDK, supports multiple models, allows for easy data migration, and is easy to integrate for AI/Machine Learning tools. 

Conclusion

AI is a powerful ally for developers who want to build apps faster and smarter. AI can help developers with various tasks, such as code completion, generation, debugging, and performance optimization. There are many AI tools and frameworks that enable developers to create and deploy AI models and applications with ease.  This can help developers both complete their projects sooner and with fewer problems over the course of development.