我和我的搭档正在尝试编写 LinkedList 数据结构。我们已经完成了数据结构,并且它可以使用所有必需的方法正常运行。我们需要对 LinkedList 类中的 addFirst() 方法与 Java ArrayList 结构的 add(0, item) 方法的运行时进行比较测试。我们的 LinkedList 数据结构的 addFirst() 方法的预期复杂度是 O(1) 常数。这在我们的测试中成立。在 ArrayList add() 方法的计时中,我们预计复杂度为 O(N),但我们再次收到大约 O(1) 常数的复杂度。这似乎是一个奇怪的差异,因为我们使用的是 Java 的 ArrayList。我们认为我们的时间结构可能存在问题,如果有人能帮助我们确定我们的问题,我们将不胜感激。
public class timingAnalysis {
public static void main(String[] args) {
//timeAddFirst();
timeAddArray();
}
public static void timeAddFirst()
{
long startTime, midTime, endTime;
long timesToLoop = 10000;
int inputSize = 20000;
MyLinkedList<Long> linkedList = new MyLinkedList<Long>();
for (; inputSize <= 1000000; inputSize = inputSize + 20000)
{
// Clear the collection so we can add new random
// values.
linkedList.clear();
// Let some time pass to stabilize the thread.
startTime = System.nanoTime();
while (System.nanoTime() - startTime < 1000000000)
{ }
// Start timing.
startTime = System.nanoTime();
for (long i = 0; i < timesToLoop; i++)
linkedList.addFirst(i);
midTime = System.nanoTime();
// Run an empty loop to capture the cost of running the loop.
for (long i = 0; i < timesToLoop; i++)
{} // empty block
endTime = System.nanoTime();
// Compute the time, subtract the cost of running the loop from
// the cost of running the loop and computing the removeAll method.
// Average it over the number of runs.
double averageTime = ((midTime - startTime) - (endTime - midTime)) / timesToLoop;
System.out.println(inputSize + " " + averageTime);
}
}
public static void timeAddArray()
{
long startTime, midTime, endTime;
long timesToLoop = 10000;
int inputSize = 20000;
ArrayList<Long> testList = new ArrayList<Long>();
for (; inputSize <= 1000000; inputSize = inputSize + 20000)
{
// Clear the collection so we can add new random
// values.
testList.clear();
// Let some time pass to stabilize the thread.
startTime = System.nanoTime();
while (System.nanoTime() - startTime < 1000000000)
{ }
// Start timing.
startTime = System.nanoTime();
for (long i = 0; i < timesToLoop; i++)
testList.add(0, i);
midTime = System.nanoTime();
// Run an empty loop to capture the cost of running the loop.
for (long i = 0; i < timesToLoop; i++)
{} // empty block
endTime = System.nanoTime();
// Compute the time, subtract the cost of running the loop from
// the cost of running the loop and computing the removeAll method.
// Average it over the number of runs.
double averageTime = ((midTime - startTime) - (endTime - midTime)) / timesToLoop;
System.out.println(inputSize + " " + averageTime);
}
}
}