Under the hood

I’m thrilled to announce the launch of two products: CodiumAI IDE Extensions [beta], and CodiumAI the company 🚀🚀 As the CEO and...

The software development industry places significant importance on testing software products due to the potential negative consequences of releasing untested software. This...

Introduction Software has become the critical driver of development as it helps us to automate processes, solve complex problems and improve our...

Unit testing is an important aspect of software development that helps developers ensure that their code is working as expected. It’s a...

As software development continues to evolve, so does the need for efficient and effective testing. One of the most critical types of...

A digest of CodiumAI version releases, IDE support, engine versions, programming language support and links to download

6 technologies are in the works and will very likely mature within the next 3 years, further increasing the (justifiable?) hype around Generative AI and large-language-models (LLMs) specifically. Once any of these technologies are integrated into a product, it will be perceived as a breakthrough. Soon enough AI-empowered products will be accurate, informative, up-to-date, and efficient. These technology breakthroughs consist of ...

Many people believe that having an open-source strategy is essential for PLG (Product Led Growth) companies developing developer tools. It fosters a supportive community while at the same time creating validity amongst developers. Though, what is the purpose of Open Source? Is it simply to create buzz by earning GitHub stars? Does it build validity amongst potential users? Or does it create a qualified funnel?

Large language models (LLMs) like ChatGPT and GPT-3 excel at analyzing both natural languages, such as English, and programming languages, such as Python. This dual ability makes LLMs very useful for day-to-day work, as they accept, process, and produce both text and code. In this blog, we present simple and efficient methods for reducing the number of tokens required by GPT-3 to represent a typical Python code.

The 0/1 knapsack problem is a well-known problem in computer science that involves maximizing the value of items that can be placed in a knapsack with limited capacity. In the context of code generation, the greedy 0/1 knapsack algorithm can be used to optimize the selection of code context tokens to include in a prompt, given a maximum limit on the number of tokens that can be used. code context can be, for example, calling and called functions or classes, imports, corresponding test functions, etc.

Autonomous code integrity (ACI) is the ability to automatically generate tests and measure correctness. In this post, we present the 6 levels of the Autonomous Code Integrity (ACI) Levels model. It is inspired by the parallel effort to build autonomous vehicles (AV) and designed to set the framework for building systems that autonomously take care of code integrity.

Tl;dr – code testing is just one way out of many to achieve code integrity. The Wikipedia term for code integrity states “With code integrity, the developer can be sure that his/her code is written correctly when passed on to QA”. In other words, this is about developers’ confidence in the correctness of their code. How can we help increase confidence and what exactly is code integrity?