All programming languages have their proponents, but not all are equally equipped with libraries for data science and machine learning. (Image: Igor Stevanovic, Getty Images/iStockphoto) ...

Ballerina’s flexible type system brings the best of statically typed and dynamically typed languages in terms of safety, clarity, and speed of development. Ballerina treats data as a first-class ...

Gradual typing has emerged as a compelling approach to reconcile the strengths of static and dynamic type systems. By permitting programmers to incrementally annotate code, it enables early ...

Oscar Spencer recently presented Grain, a new strongly-typed, high-level language that compiles to WebAssembly. Grain includes functional programming features (e.g., type inference, pattern ...

Session Types and Concurrency in Programming Languages Publication Trend The graph below shows the total number of publications each year in Session Types and Concurrency in Programming Languages.

Programming languages Python and R are often pitted against each other over which is best for data science and analysis. Both are popular, although Python appears to be much more widely used, at ...

The R programming language is an important tool for development in the numeric analysis and machine learning spaces. With machines becoming more important as data generators, the popularity of the ...

A programming language structure wherein the data and their associated processing ("methods") are defined as self-contained entities called "objects." Becoming popular in the early 1990s and the ...

Programming languages: JavaScript top for web and cloud development while Python rules data science The future of programming languages: What to expect in this new Infrastructure as Code world ...

Python Programming Language on server room background. Programing workflow abstract algorithm concept on virtual screen.