Update CI to Pharo12. Update README

.github/workflows/test.yml

@@ -9,7 +9,7 @@ jobs:
   build:
     strategy:
       matrix:
-        smalltalk: [ Pharo64-9.0, Pharo64-10, Pharo64-11 ]
+        smalltalk: [ Pharo64-9.0, Pharo64-10, Pharo64-11, Pharo64-12 ]
     runs-on: ubuntu-latest
     name: ${{ matrix.smalltalk }}
     steps:

README.md

@@ -2,16 +2,32 @@
 [![Coverage Status](https://coveralls.io/repos/github/pharo-ai/edit-distances/badge.svg?branch=master)](https://coveralls.io/github/pharo-ai/edit-distances?branch=master)
 [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)
 [![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active)
+[![Pharo version](https://img.shields.io/badge/Pharo-9-%23aac9ff.svg)](https://pharo.org/download)
+[![Pharo version](https://img.shields.io/badge/Pharo-10-%23aac9ff.svg)](https://pharo.org/download)
+[![Pharo version](https://img.shields.io/badge/Pharo-11-%23aac9ff.svg)](https://pharo.org/download)
+[![Pharo version](https://img.shields.io/badge/Pharo-12-%23aac9ff.svg)](https://pharo.org/download)
 [![license-badge](https://img.shields.io/badge/license-MIT-blue.svg)](https://img.shields.io/badge/license-MIT-blue.svg)
 
 ## Table of contents
 
 - [Table of contents](#table-of-contents)
+- [Description](#description)
 - [How to install it](#how-to-install-it)
 - [How to depend on it](#how-to-depend-on-it)
-- [Description](#description)
 - [Implemented distances](#implemented-distances)
 
+## Description
+
+Edit distance is a way of quantifying how dissimilar two strings are to one another by counting the minimum number of operations required to transform one string into the other. The distance between the two documents is defined as "The minimum number of insertions, deletions, and substitutions required to transform one string into the other". Edit-based distances for which such weights can be defined are usually refered to as generalized distances. These methods are independent of a searching algorithm, i.e. Levenshtein or Hamming edit distances can be applied separately to a searching algorithm.
+
+Edit distances find applications in natural language processing, where automatic spelling correction can determine candidate corrections for a misspelled word by selecting words from a dictionary that have a low distance to the word in question.
+
+This package provides methods to determine the distance between two objects, for example, between Strings. Those objects, often represent documents. Normally they are strings but also they can be arrays of numbers that represent a document.
+
+  - An edit distance does NOT count matches.
+  - Some commonly refered "edit distances" compare corresponding elements and require objects of equal length (examples: Euclidean, Manhattan, Hamming,...)
+  - To speed up computation, some distances are based in "tokens", and also referred as token-based distances (example: Cosine similarity).
+
 ## How to install it
 
 ```smalltalk
@@ -32,18 +48,6 @@ spec
 	with: [ spec repository: 'github://pharo-ai/edit-distances/src' ]
 ```
 
-## Description
-
-Edit distance is a way of quantifying how dissimilar two strings are to one another by counting the minimum number of operations required to transform one string into the other. The distance between the two documents is defined as "The minimum number of insertions, deletions, and substitutions required to transform one string into the other". Edit-based distances for which such weights can be defined are usually refered to as generalized distances. These methods are independent of a searching algorithm, i.e. Levenshtein or Hamming edit distances can be applied separately to a searching algorithm.
-
-Edit distances find applications in natural language processing, where automatic spelling correction can determine candidate corrections for a misspelled word by selecting words from a dictionary that have a low distance to the word in question.
-
-This package provides methods to determine the distance between two objects, for example, between Strings. Those objects, often represent documents. Normally they are strings but also they can be arrays of numbers that represent a document.
-
-  - An edit distance does NOT count matches.
-  - Some commonly refered "edit distances" compare corresponding elements and require objects of equal length (examples: Euclidean, Manhattan, Hamming,...)
-  - To speed up computation, some distances are based in "tokens", and also referred as token-based distances (example: Cosine similarity).
-
 ## Implemented distances
 
 These are the currently implemented distance.