Escher is a functional logic programming language designed with the aim of providing in a simple computation mechanism the best features of functional programming and logic programming. Escher is described in more details in these articles:
The theoretical foundations for Escher is provided in the book `Logic for Learning’ by John Lloyd.
Escher is implemented in Noweb-C++, with fairly extensive documentation. It is being actively supported.
- Here’s the literate program An Implementation of Escher.
- The source files are hosted on Github: https://github.com/keesiong/escher
MADlib is a scalable in-database machine learning algorithm. It is recently accepted as an incubator project by ASF after 5 years of development and it is available here: http://madlib.net
MADlib’s design philosophy and implementation details can be found in these two VLDB papers: