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kse-02/genetic.py
2023-12-09 12:13:56 +01:00

127 lines
4.1 KiB
Python

import os
from typing import Callable
import frozendict
from deap import creator, base, tools, algorithms
import fuzzer
import instrument
from fuzzer import get_test_cases, get_test_class
INDMUPROB = 0.05
MUPROB = 0.1
CXPROB = 0.5
TOURNSIZE = 3
NPOP = 300
NGEN = 200
REPS = 10
to_test: str = ""
OUT_DIR = os.path.join(os.path.dirname(__file__), "tests")
def normalize(x):
return x / (1.0 + x)
def get_test_case_generator(f_name: str, arguments: list[instrument.Arg]) -> Callable[[], list]:
return lambda: list(list(get_test_cases(f_name, arguments, 1, enable_bar=False))[0].items())
def generate(f_name: str):
global to_test
to_test = f_name
creator.create("Fitness", base.Fitness, weights=(-1.0,))
creator.create("Individual", list, fitness=creator.Fitness)
args = instrument.functions[f_name]
toolbox = base.Toolbox()
toolbox.register("attr_test_case", get_test_case_generator(to_test, instrument.functions[to_test]))
toolbox.register("individual",
tools.initIterate,
creator.Individual,
lambda: toolbox.attr_test_case())
toolbox.register("population",
tools.initRepeat,
list,
toolbox.individual)
toolbox.register("evaluate", compute_fitness)
def mate(tc1, tc2):
t1, t2 = frozendict.frozendict(tc1), frozendict.frozendict(tc2)
o1, o2 = fuzzer.crossover(t1, t2, args)
i1, i2 = creator.Individual(o1.items()), creator.Individual(o2.items())
return i1, i2
def mutate(tc):
t = frozendict.frozendict(tc)
o = fuzzer.mutate(t, args)
i1 = creator.Individual(o.items())
return i1,
toolbox.register("mate", mate)
toolbox.register("mutate", mutate)
toolbox.register("select", tools.selTournament, tournsize=TOURNSIZE)
coverage = []
for i in range(REPS):
instrument.archive_true_branches = {}
instrument.archive_false_branches = {}
population = toolbox.population(n=NPOP)
algorithms.eaSimple(population, toolbox, CXPROB, MUPROB, NGEN) # , verbose=False)
cov = len(instrument.archive_true_branches) + len(instrument.archive_false_branches)
print(cov, instrument.archive_true_branches, instrument.archive_false_branches)
coverage.append(cov)
print(coverage)
def compute_fitness(individual: list) -> tuple[float]:
x = frozendict.frozendict(individual)
range_start, range_end = instrument.n_of_branches[to_test]
# Reset any distance values from previous executions
instrument.distances_true = {}
instrument.distances_false = {}
# Run the function under test
try:
out = instrument.invoke(to_test, x)
except AssertionError:
print(to_test, x, "=", "[FAILS] fitness = 10000")
return 10000,
fitness = 0.0
# Sum up branch distances
for branch in range(range_start, range_end):
if branch in instrument.distances_true:
if instrument.distances_true[branch] == 0 and branch not in instrument.archive_true_branches:
instrument.archive_true_branches[branch] = x
if branch not in instrument.archive_true_branches:
fitness += normalize(instrument.distances_true[branch])
for branch in range(range_start, range_end):
if branch in instrument.distances_false:
if instrument.distances_false[branch] == 0 and branch not in instrument.archive_false_branches:
instrument.archive_false_branches[branch] = x
if branch not in instrument.archive_false_branches:
fitness += normalize(instrument.distances_false[branch])
print(to_test, x, "=", out, "fitness =", fitness)
return fitness,
def main():
instrument.load_benchmark(save_instrumented=False) # instrument all files in benchmark
f_name = "railencrypt_instrumented"
generate(f_name)
with open(os.path.join(OUT_DIR, f_name + ".py"), "w") as f:
cases = get_test_cases(f_name, instrument.functions[f_name], 100)
f.write(get_test_class(f_name, cases))
if __name__ == '__main__':
main()