Module proper_sa

This module provides simulated annealing (SA) as search strategy for targeted property-based testing.

Copyright © 2017 Andreas Löscher and Kostis Sagonas

Version: May 31 2024 10:07:10

Behaviours: proper_target.

Authors: Andreas Löscher.

Description

This module provides simulated annealing (SA) as search strategy for targeted property-based testing. SA is a local search meta-heuristic that can be used to address discrete and continuous optimization problems.

SA starts with a random initial input. It then produces a random input in the neighborhood of the previous one and compares the fitness of both. If the new input has a higher fitness than the previous one, it is accepted as new best input. SA can also accepts worse inputs with a certain probability. (more information)

Generated by EDoc