private static boolean greedySwitch(
ArrayList<TestResult> testSuite, ArrayList<TestResult> unused) {
TestResult max = unused.get(0);
TestResult min = testSuite.get(0);
for (TestResult i : testSuite) {
if (i.getUniqueMutants().size() < min.getUniqueMutants().size()) {
min = i;
}
}
for (TestResult i : unused) {
if (i.getUniqueMutants().size() > max.getUniqueMutants().size()) {
max = i;
}
}
if (min.getUniqueMutants().equals(0) && !(max.getUniqueMutants().equals(0))) {
int testSuiteLoc = testSuite.indexOf(min);
testSuite.remove(testSuiteLoc);
testSuite.add(testSuiteLoc, max);
int unusedLoc = unused.indexOf(max);
unused.remove(unusedLoc);
unused.add(unusedLoc, min);
return true;
}
return false;
}
// Fitness function that gives higher score based on best time while maintining minimum mutant
// score
// Higher scores are better
private static double fitnessOnTime(ArrayList<TestResult> solution, int targetScore) {
double time = 0.0;
int score = 0;
for (TestResult i : solution) {
score += i.getUniqueMutants().size();
time += i.getTime();
}
if (score < targetScore) {
return Double.MIN_VALUE;
} else {
return 1 / time;
}
}
// Fitness function that gives higher score based on better mutantscore without going over target
// time
// Higher scores are better
private static int fitnessOnScore(ArrayList<TestResult> solution, double targetTime) {
double time = 0.0;
int score = 0;
for (TestResult i : solution) {
score += i.getUniqueMutants().size();
time += i.getTime();
}
if (time > targetTime) {
return 0;
} else {
return score;
}
}