Rosetta Code is a programming chrestomathy wiki, that is, it is a site with lots of examples of tasks completed in multiple programming languages. The site has been around since 2007 and now has 1,100+ tasks and 100,000+ code submissions over 900+ languages. To help other researchers, I’m publishing an export of the code samples as a sqlite database via DBHub.io and the source code via Gitlab.
In 1986, a survey of approximate string matching algorithms found the algorithm used in the PLATO computer-aided instruction system was third place in quality (F1 score) and was an order of magnitude faster than the best performing algorithms. The PLATO algorithm used an unusual dimensional projection approach, while the competing algorithms of the day used edit distances or phonetics. However, this approach failed to catch on and the design is rarely mentioned in the literature. This video describes how the algorithm worked and some reasons why it became forgotten.
Approximate string matching algorithms (ASMA) determine if two strings are the same, “close enough”, or are distinct. Spelling error detection and correction were early applications of these algorithms, and today ASMAs (or similar techniques) are used in natural language understanding applications. Hundreds of papers have been written on the subject (1980 survey, 2001 survey), but this post is focused on the subset of algorithms that were considered commercially viable for the field of computer-assisted instruction (CAI), an early hardware/software-as-a-service business.
In 1976, Los Alamos hosted the International History of Computing Conference where the pioneering efforts of computing were discussed, often by the pioneers themselves. The Computer History Museum has posted videos from the talks, which cover important machines, languages, people, institutions, and practices invented in the first 30 years of the craft. Dag Spicer, the senior curator at CHM, has written a blog post giving an overview and background of the event.