Alternatives to GitHub Copilot: Tabnine, AWS CodeWhisperer, and Bito to Increase Developers’ Productivity by 20%
January 3, 2024
Author:
Into
GitHub Copilot
was developed collaboratively by GitHub and OpenAI and utilizes OpenAI’s Codex, a transformer trained on vast amounts of code from GitHub repositories. This tool automatically creates code snippets, functions, tests, and documentation by analyzing existing code and your cursor position. It leverages the shared knowledge of the coding community for an incredibly insightful coding experience.
Before diving into the distinctive features of each tool, here’s a quick look at what each one brings to the table:
Tabnine
AWS Codewhisperer
Bito
Trained on
Open-source code
Amazon and open-source code
Open-source text and code
Self-hosting
Possible
Not possible
Not possible
Personalized AI model
Yes
No
Yes
Special features
Generate unit tests, Translate code, Offline access Complete code
Tabnine was an early player in terms of code completion tools, and it provides a practical plugin compatible with your preferred code editor. It offers suggestions for whole lines of code and full-function completions across various languages, libraries, and frameworks. And it does so based on natural-language comments.
One noteworthy aspect of Tabnine is its efficiency with minimal context compared to
Copilot
. It suggests code midline as you type, without waiting for one line to be finished before moving to the next.
For teams and organizations, Tabnine offers the capability to host and train their own
AI models
. This feature facilitates collaborative autocompletion across IDEs, which enhances teamwork and contributes to code security.
Beyond code completion, Tabnine tackles unit test support. Using advanced AI, it automatically generates unit tests for your code, a helpful feature for ensuring thorough testing and code stability, especially on larger projects.
Amazon CodeWhisperer understands natural language comments in English and offers suggestions ranging from snippets to entire functions—up to 10–15 lines—in various IDEs. Similar to Tabnine, CodeWhisperer adapts to your coding style and ensures a personalized coding experience. It also extends its capabilities to the command line with inline documentation and AI-driven natural-language-to-code translation.
For those leveraging AWS services, CodeWhisperer analyzes code in real time, with suggestions tailored to AWS APIs like Amazon EC2 and AWS Lambda and aligned with best practices for cloud-based projects.
To ensure responsible coding, the tool introduces a reference tracker for open-source code. This feature flags suggestions resembling public code with detailed annotations for review. The goal here is to actively avoid biases in code suggestions.
If you’re choosing between AWS CodeWhisperer and Tabnine, consider what you prioritize. Let’s say you value versatility and broad language support across various editors; then Tabnine is your pick. CodeWhisperer, on the other hand, is for those who focus on precision — the tool learns from in-house code and tailors suggestions to an organization’s practices.
Bito allows users to generate code in any language, create comprehensive test cases, and gain insights into selected code snippets with the Explain Code feature. For documentation, Bito offers a Comment Method tool, while the Improve Performance feature provides tips for enhancing code efficiency. Security concerns are addressed through the Check Security function, which lets you inquire about potential issues.
What sets Bito apart from GitHub Copilot is its integration with Visual Studio Code — it leverages embeddings and a vector database to understand your local codebase. This ensures context-aware suggestions, a distinctive advantage over Copilot.
Another noteworthy feature is the Generate Unit Test Shortcut:
On the level of software development organizations, it’s a best practice to regulate AI tools usage in processes. Many
responsible engineering companies
already create and implement AI tools usage policies for employees on how to be safe and secure when using generative AI, especially when it involves the sharing of potentially sensitive company and customer information.
Summing Up
The implementation of AI assistants like Tabnine, AWS CodeWhisperer, and Bito has resulted in tangible time savings and enhanced productivity. And we have the numbers to back this up.
In just two weeks,
Tabnine
contributed to a nearly
13-hour timesaving
for an Intetics engineer. That month, 27% of that engineer’s code was produced by the tool.
With
AWS CodeWhisperer
, the official figures claim
a 57% acceleration in developer productivity and a 27% increase in the likelihood of project success
.
As for
Bito
, the subjective experience reveals improvements in speed, particularly in implementing new features. The initial estimate suggested a potential 27% code contribution, but real-world results prove a more conservative
productivity boost of 10-20%
. Also, Bito offers remarkable efficiency, potentially
saving up to 80% of time spent on writing unit tests
.
To wrap it up, embrace the tools that empower you to code better and faster.
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