0.8a1.dev25

README.md

@@ -4,13 +4,13 @@
 [![License: Apache 2.0](https://img.shields.io/badge/license-apache--2.0-green.svg)](https://opensource.org/licenses/Apache-2.0) 
 [![Status: Actrive](https://img.shields.io/badge/status-active-brightgreen.svg)](https://github.com/cad-polito-it/byron)
 ![Language: Python](https://img.shields.io/badge/language-python-blue.svg)
-![Version: 0.1.dev2](https://img.shields.io/badge/version-0.8a1.dev23-orange.svg)
+![Version: 0.1.dev2](https://img.shields.io/badge/version-0.8a1.dev25-orange.svg)
 ![Codename: Don Juan](https://img.shields.io/badge/codename-Don_Juan-pink.svg)
 [![Documentation Status](https://readthedocs.org/projects/byron/badge/?version=pre-alpha)](https://byron.readthedocs.io/en/pre-alpha/?badge=pre-alpha)
 
-Byron is an [evolutionary tool](https://en.wikipedia.org/wiki/Evolutionary_algorithm): given a problem, it first generates a set of random solutions, then iteratively refines and improves them using the results of their evaluations together with structural information. It may be used as a coverage-driven [fuzzer](https://en.wikipedia.org/wiki/Fuzzing) and a general-purpose [optimizer](https://en.wikipedia.org/wiki/Engineering_optimization).
+Byron is an [evolutionary tool](https://en.wikipedia.org/wiki/Evolutionary_algorithm): given a problem, it first generates a set of random solutions, then iteratively improves them using the results of their evaluations together with structural information. It may be used as a coverage-driven [fuzzer](https://en.wikipedia.org/wiki/Fuzzing) and a general-purpose [optimizer](https://en.wikipedia.org/wiki/Engineering_optimization).
 
-Byron internally encodes candidate solutions as [typed](https://rcor.me/papers/typed-graph-theory.pdf), [directed](https://en.wikipedia.org/wiki/Graph_(discrete_mathematics)#Directed_graph) [multigraphs](https://en.wikipedia.org/wiki/Multigraph) and can tackle problems with complex, structured constraints. For instance, it may be used to create realistic programs with loops, interrupts, and recursive subroutines. Gory detail: solutions are heterogeneous [forests](https://en.wikipedia.org/wiki/Tree_(graph_theory)#Forest) with additional edges connecting leaves to generic nodes, possibly not in the same tree.
+Byron internally encodes candidate solutions as [typed](https://rcor.me/papers/typed-graph-theory.pdf), [directed](https://en.wikipedia.org/wiki/Graph_(discrete_mathematics)#Directed_graph) [multigraphs](https://en.wikipedia.org/wiki/Multigraph) and can tackle problems with complex, structured constraints. For instance, it may be used to create realistic programs with loops, flow-control structures, and subroutines. Gory detail: solutions are heterogeneous [forests](https://en.wikipedia.org/wiki/Tree_(graph_theory)#Forest) with additional edges connecting leaves to nodes, possibly in different trees.
 
 Candidate solutions are dumped as text and then evaluated by calling a user-defined Python function or by invoking a shell script that may use external proprietary tools. Different types of parallelization are supported out of the box, from simple multithreading to the creation of temporary directories where multiple subprocesses are concurrently [spawned](https://en.wikipedia.org/wiki/Spawn_(computing)).
 

byron/global_symbols.py

@@ -63,8 +63,8 @@
 from collections import defaultdict
 import multiprocessing
 
-__version__ = "0.8a1.dev23"
-__date__ = "28-08-2023"
+__version__ = "0.8a1.dev25"
+__date__ = "30-08-2023"
 __codename__ = "Don Juan"
 __author__ = "Giovanni Squillero and Alberto Tonda"
 __copyright__ = "Copyright (c) 2023 Giovanni Squillero and Alberto Tonda"

docs/pypi.md

@@ -1,6 +1,13 @@
-Byron is an [evolutionary tool](https://en.wikipedia.org/wiki/Evolutionary_algorithm): given a problem, it first generates a set of random solutions, then iteratively refines and improves them using the results of their evaluations together with structural information. It may be used as a coverage-driven [fuzzer](https://en.wikipedia.org/wiki/Fuzzing) and a general-purpose [optimizer](https://en.wikipedia.org/wiki/Engineering_optimization).
+[![License: Apache 2.0](https://img.shields.io/badge/license-apache--2.0-green.svg)](https://opensource.org/licenses/Apache-2.0) 
+[![Status: Actrive](https://img.shields.io/badge/status-active-brightgreen.svg)](https://github.com/cad-polito-it/byron)
+![Language: Python](https://img.shields.io/badge/language-python-blue.svg)
+![Version: 0.1.dev2](https://img.shields.io/badge/version-0.8a1.dev25-orange.svg)
+![Codename: Don Juan](https://img.shields.io/badge/codename-Don_Juan-pink.svg)
+[![Documentation Status](https://readthedocs.org/projects/byron/badge/?version=pre-alpha)](https://byron.readthedocs.io/en/pre-alpha/?badge=pre-alpha)
 
-Byron internally encodes candidate solutions as [typed](https://rcor.me/papers/typed-graph-theory.pdf), [directed](https://en.wikipedia.org/wiki/Graph_(discrete_mathematics)#Directed_graph) [multigraphs](https://en.wikipedia.org/wiki/Multigraph) and can tackle problems with complex, structured constraints. For instance, it may be used to create realistic programs with loops, interrupts, and recursive subroutines. Gory detail: solutions are heterogeneous [forests](https://en.wikipedia.org/wiki/Tree_(graph_theory)#Forest) with additional edges connecting leaves to generic nodes, possibly not in the same tree.
+Byron is an [evolutionary tool](https://en.wikipedia.org/wiki/Evolutionary_algorithm): given a problem, it first generates a set of random solutions, then iteratively improves them using the results of their evaluations together with structural information. It may be used as a coverage-driven [fuzzer](https://en.wikipedia.org/wiki/Fuzzing) and a general-purpose [optimizer](https://en.wikipedia.org/wiki/Engineering_optimization).
+
+Byron internally encodes candidate solutions as [typed](https://rcor.me/papers/typed-graph-theory.pdf), [directed](https://en.wikipedia.org/wiki/Graph_(discrete_mathematics)#Directed_graph) [multigraphs](https://en.wikipedia.org/wiki/Multigraph) and can tackle problems with complex, structured constraints. For instance, it may be used to create realistic programs with loops, flow-control structures, and subroutines. Gory detail: solutions are heterogeneous [forests](https://en.wikipedia.org/wiki/Tree_(graph_theory)#Forest) with additional edges connecting leaves to nodes, possibly in different trees.
 
 Candidate solutions are dumped as text and then evaluated by calling a user-defined Python function or by invoking a shell script that may use external proprietary tools. Different types of parallelization are supported out of the box, from simple multithreading to the creation of temporary directories where multiple subprocesses are concurrently [spawned](https://en.wikipedia.org/wiki/Spawn_(computing)).
 

pyproject.toml

@@ -10,7 +10,7 @@
 
 [tool.poetry]
 name = "byron"
-version = "0.8a1.dev23"
+version = "0.8a1.dev25"
 description = "Multi-purpose extensible self-adaptive optimizer and fuzzer"
 authors = [
     "Giovanni Squillero <giovanni.squillero@polito.it>",
@@ -103,7 +103,7 @@ max-line-length = 120
 source-roots = ['src']
 
 [bumpver]
-current_version = "0.8a1.dev23"
+current_version = "0.8a1.dev25"
 version_pattern = "MAJOR.MINOR[PYTAGNUM].devINC0"
 commit_message = "Bump version to {new_version}"
 commit = false
@@ -118,6 +118,10 @@ push = false
     "\\[Version: {pep440_version}\\]",
     "version-{pep440_version}-orange"
 ]
+"docs/pypi.md" = [
+    "\\[Version: {pep440_version}\\]",
+    "version-{pep440_version}-orange"
+]
 "byron/global_symbols.py" = [
     '__version__ = "{pep440_version}"',
     '__date__ = "0D-0M-YYYY"',