Genetic algorithm: https://en.wikipedia.org/wiki/Genetic_algorithm :
> Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems via biologically inspired operators such as selection, crossover, and mutation.
AP®/College Biology: https://www.khanacademy.org/science/ap-biology
Justifying that genetic algorithms are CS and Biology applied, which satisfies OT's implicit yearning
AP®/College Biology > Unit 6: Gene Expression and Regulation > Lesson 6: Mutations: https://www.khanacademy.org/science/ap-biology/gene-expressi...
AP®/College Biology > Unit 7: Natural selection: https://www.khanacademy.org/science/ap-biology/natural-selec...
Rosalind.info has free CS algorithms applied bioinformatics exercises in Python; in a tree or a list; including genetic combinatorics. https://rosalind.info/problems/list-view/
FWICS there is not a "GA with code exercise" in the AP Bio or Rosalind curricula.
YouTube has videos of simulated humanoids learning to walk with mujoco and genetic algorithms that demonstrate goal-based genetic programming with Cost / Error / Fitness / Survival functions.
Mutating source code AST is a bit different from mutating to optimize a defined optimization problem with specific parameters; though the task is basically the same: minimize error between input and output, and then XAI.