Better code
through data

Today, software engineers and their tools almost exclusively consider source code as a collection of text files. At QuantifiedCode, we understand code as data—more specifically, a graph. This gives us a completely new perspective on code and allows us take development tools and static code analysis to the next level.

Code is a graph

At QuantifiedCode, we store vast amounts of source code in one single data structure—the world largest code-graph. This enables us to learn from billions of code changes and to identify new code quality issues through example based learning. On a project level, this allows us to better understand complex software projects, to deliver better code quality checks, and to automatically improve your code.

Code is not text

The tools we use (version control systems, IDEs, code analyzers) use text as primary storage format for code. The belief that "code is text" is so ingrained in our heads that we aren't even aware of other ways to look at code. Our vision of the future of programming is a future where we no longer interact with code, using simple text editors, but where we apply data analytics to eliminate inefficiencies in software development processes.

Learning from
others' mistakes

Static code analysis is a useful tool to detect bugs early in the software development lifecycle. Learn how we take static code analyis to the next level, by combining the analysis of publicly available source code with sample-based learning, to detect new types of errors.

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