Will Applications of AI replace Developers?
Applications of artificial intelligence are growing to industrialize test phases and semi-automate code writing. But some providers go further.
Applications of AI lend themselves to programming applications.
Short-term promise: Improve coding productivity, or even automate certain steps, particularly affecting software testing.
“AI companies with large application projects are looking to AI machine learning enhanced development tools as an opportunity to accelerate the speed and improve the quality of deliverables,” said David Shatsky, managing director of Deloitte. Ought to.” With a drawn-out vision, some examination research facilities are now dealing with AIs that permit us to go significantly further.
- The first area of AI in business in software development: is help writing code. Similar to entering a question into Google play dev, it consists of offering personalized suggestions as you type.
- Today, the feature is well known to developers. A pioneer in the field, Microsoft has been integrating the device into the Visual Studio IDE since 2018, as well as VSCode, its open-source version.
- Taking the form of an extension called IntelliCode, this natural language processing (NLP) brick will draw its knowledge from hundreds of open source projects with over a hundred stars on GitHubdisplaying ranking levels.
- Enough to raise the standard by guiding the user to best practices in the sector.
At the same time, IntelliCode makes it possible to build ad hoc learning models to take advantage of personal suggestions based not only on public open source code, but also on private source repositories.
Startups are growing Applications of Artificial Intelligence .
- In Microsoft’s shadow, startups are pushing the alternative. Among the most prominent: Israeli Kodota. Like IntelliCode, its solution is built around NLP models fed by both public code and private repositories.
- AI replace developers team from big names in Silicon Valley, such as Amazon, Airbnb, Atlassian, Google or Netflix, use it. In December 2019, the company joined hands with one of its main competitors, fellow citizen TabNine.
- Founded a year after Codota, in 2014, and with $21 million raised to its credit, California Kite takes a similar position in every respect. To round out its entry-level Artificial intelligence is about based on open-source datasets, in July 2020 it launched an offering designed to train models based on internal projects.
- Logic like Microsoft and Kodota. Called Team Server, it’s based on a much more advanced deep learning infrastructure. It takes into account 100 million parameters, compared to 4 million for the entry-level service.
- A technological leap that allows Kite to carry two to four consecutive keyword completions, compared to just one for Intellicode. To date, the San Francisco company claims 400,000 users.
“Instead of replacing the programmer, our goal is to save him mundane and repetitive work.”
- There is one point on which Microsoft Codeta and Kite have no competition. The solution is limited to Visual Studio. Unlike the two startups, whose offerings are agnostic in terms of the development environment.
- Both support Android Studio mac, Jupiter, PHP Storm, Pcharm, RubyMine, Vim or Sublime. Not forgetting Visual Studio Code which is one of the most used IDEs. In the integration game, Codota, in addition, stands out by supporting the very popular Eclipse infrastructure.
- In the software test, two American startups stand out quite clearly: Functionize and Mabl. Founded back-to-back in 2015 and 2017, they raised $19.2 and $36.1 million, respectively. As its name suggests, the first automates functional testing. Its presentation again revolves around the NLP engine.
- An algorithmic model designed to translate test specifications written in natural language (in this case English) into machine-executable scripts. As for Mabel, he hits the same target, but with a very different approach.
- Its tool generates test scripts by analyzing the graphical interface and scenarios run on the screen by the developer.Apptools. Founded like Codota in Israel (in 2013), this publisher, which claims $41.8 million in funding, automates the creation of functional tests by analyzing application screens, identifying variations or regressions, and from there. Relies on image recognition to create In March 2021, Applitools was acquired by the Thomas Bravo Fund for $300 million.
Following in the footsteps of these players.
The French company Ponicodeis took a position in the automation of unit tests. Installed at Station F, it was designed by Patrick Joubert. The serial entrepreneur has already distinguished himself by launching consulting company Beamap and notably Recast.ai, a chatbot platform that he sold to SAP in 2018.
With Ponicode, Patrick Joubert now brings NLP to the service of developers. The company completed its first fundraising of 3 million euros in July 2020. The principle of its solution? After analyzing the code, its deep learning engine, currently
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