Using the feature, developers can “brush” over their code to see it update in real-time.

Several different brushes are included to achieve various aims. For example, one brush makes code more readable—especially important when coding as part of a team or contributing to open-source projects.

Here are the other included brushes:

• Add types
• Fix bug
• Debug (adds debugging statements)
• Make robust (improves compatibility)

Code Brushes also supports the creation of custom brushes. One example is a brush to make a form “more accessible” automatically.

“As we explore enhancing developers’ workflows with machine learning, we’re focused on how to empower developers instead of automating them,” explained GitHub.

“This was one of many explorations we have in the works along those lines.”

Code Brushes is powered by the controversial GitHub Copilot. Copilot uses technology from OpenAI to help generate code and speed up software development.

GitHub-owner Microsoft and OpenAI were hit with a class-action lawsuit over Copilot last year. The case aims to investigate whether Copilot infringes on the rights of developers by scraping their code and not providing due attribution.

“Users likely face growing liability that only increases as Copilot improves,” explained Bradley M. Kuhn of Software Freedom Conservancy earlier this year.

“Users currently have no methods besides serendipity and educated guesses to know whether Copilot’s output is copyrighted by someone else.”

Code Brushes has been added to the Copilot Labs Visual Studio Code extension. The extension requires a Copilot license which costs $10/month or $100/year.

(Photo by Marcus Urbenz on Unsplash)

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The paper, titled ‘Do Users Write More Insecure Code with AI Assistants?’, examines developers’ use of AI coding assistants like the controversial GitHub Copilot.

“Participants with access to an AI assistant often produced more security vulnerabilities than those without access, with particularly significant results for string encryption and SQL injection,” the authors wrote.

The paper also found that developers using AI assistants have misguided confidence in the quality of their code.

“We also found that participants [that were] provided access to an AI assistant were more likely to believe that they wrote secure code than those without access to the AI assistant,” added the authors.

47 people were asked to write code in response to several prompts as part of the study. Some participants were given AI assistance while the rest did not.

The first prompt was to “Write two functions in Python where one encrypts and the other decrypts a given string using a given symmetric key.”

For that prompt, 79 percent of the coders without AI assistance gave a correct answer. That’s compared to 67 percent of the group with assistance.

In addition, the assisted group was determined to be “significantly more likely to provide an insecure solution (p < 0.05, using Welch’s unequal variances t-test), and also significantly more likely to use trivial ciphers, such as substitution ciphers (p < 0.01), and not conduct an authenticity check on the final returned value.”

One participant allegedly quipped that they hope AI assistance gets deployed because “it’s like [developer Q&A community] Stack Overflow but better, because it never tells you that your question was dumb.”

Last month, OpenAI and Microsoft were hit with a lawsuit over their GitHub Copilot assistant. Copilot is trained on “billions of lines of public code … written by others”.

The lawsuit alleges that Copilot infringes on the rights of developers by scraping their code and not providing due attribution. Developers that use code suggested by Copilot could unwittingly be infringing copyright.

“Copilot leaves copyleft compliance as an exercise for the user. Users likely face growing liability that only increases as Copilot improves,” wrote Bradley M. Kuhn of Software Freedom Conservancy earlier this year.

To summarise: Developers using current AI assistants risk producing buggier, less secure, and potentially litigable code.

(Photo by James Wainscoat on Unsplash)

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The post Developers using AI help often produce buggier code appeared first on AI News.

Copilot draws context from the code that a developer is working on and can suggest entire lines or functions. The system, from OpenAI, claims to be “significantly more capable than GPT-3” in generating code and can help even veteran programmers to discover new APIs or ways to solve problems.

Critics claim the system is using copyrighted code that GitHub then plans to charge for:

Julia Reda, a researcher and former MEP, published a blog post arguing that “GitHub Copilot is not infringing your copyright”.

GitHub – and therefore its owner, Microsoft – is using the huge number of repositories it hosts with ‘copyleft’ licenses for its tool. Copyleft allows open-source software or documentation to be modified and distributed back to the community.

Reda argues in her post that clamping down on tools such as GitHub’s through tighter copyright laws would harm copyleft and the benefits it offers.

One commenter isn’t entirely convinced:

“Lots of people have demonstrated that it pretty much regurgitates code verbatim from codebases with abandon. Putting GPL code inside a neural network does not remove the license if the output is the same as the input.

A large portion of what Copilot outputs is already full of copyright/license violations, even without extensions.”

Because the code is machine-generated, Reda also claims that it cannot be determined to be ‘derivative work’ that would face the wrath of intellectual property laws.

“Copyright law has only ever applied to intellectual creations – where there is no creator, there is no work,” says Reda. “This means that machine-generated code like that of GitHub Copilot is not a work under copyright law at all, so it is not a derivative work either.”

There is, of course, also a debate over whether the increasing amounts of machine-generated work should be covered under IP laws. We’ll let you decide your own position on the matter.

(Photo by Markus Winkler on Unsplash)

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GitHub Copilot uses an AI system from OpenAI known as OpenAI Codex. The system claims to have a broad knowledge of how people use code and claims to be “significantly more capable than GPT-3” in generating code.

By drawing context from the code that a developer is working on, the system is able to suggest entire lines or functions.

Even veteran coders can benefit from GitHub Copilot by using the system to explore new APIs and discover alternative ways to solve problems without having to scour the web for answers.

GitHub Pilot supports a wide range of programming languages and frameworks but the company says the technical preview works best with Python, JavaScript, TypeScript, Ruby, and Go.

There are currently only a limited number of spots available for the technical preview.

Find out more about GitHub Copilot and how to get started here.

Find out more about Digital Transformation Week North America, taking place on November 9-10 2021, a virtual event and conference exploring advanced DTX strategies for a ‘digital everything’ world.

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