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Done #4

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aafbd17
time complexity answer done, need to work on rewrite
Dani-DEV28 Feb 6, 2025
01321ac
change the default return
Dani-DEV28 Feb 6, 2025
1e13913
eLE logic done
Dani-DEV28 Feb 6, 2025
1c6f5a9
Added time complexity to emailLookupEfficient
xavierb117 Feb 6, 2025
884a402
update answer
Dani-DEV28 Feb 6, 2025
40ef9ef
Solved hasCommonEfficient
xavierb117 Feb 6, 2025
0119ac2
Merge branch 'main' of https://github.com/Dani-DEV28/complexity-practice
xavierb117 Feb 6, 2025
a17ebae
answer done
Dani-DEV28 Feb 6, 2025
651a0ce
Fixed HashSet to HashMap
xavierb117 Feb 6, 2025
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45 changes: 32 additions & 13 deletions src/Main.java
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Original file line number Diff line number Diff line change
Expand Up @@ -5,7 +5,7 @@

public class Main {

// The time complexity is:
// The time complexity is: n^2
// YOUR ANSWER HERE
public static void timesTable(int x) {
for(int i = 1; i <= x; i++) {
Expand All @@ -16,7 +16,7 @@ public static void timesTable(int x) {
}
}

// The time complexity is:
// The time complexity is: n
// YOUR ANSWER HERE
public static void printLetters(String word) {
char[] letters = word.toCharArray();
Expand All @@ -26,7 +26,7 @@ public static void printLetters(String word) {
}
}

// The time complexity is:
// The time complexity is: n
// YOUR ANSWER HERE
public static boolean isBanned(String password) {
String[] bannedPasswords = {"password", "hello", "qwerty"};
Expand All @@ -40,7 +40,7 @@ public static boolean isBanned(String password) {
}


// The time complexity is:
// The time complexity is: n
// YOUR ANSWER HERE
public static int computeProduct(int[] nums) {
int total = 1;
Expand All @@ -50,7 +50,7 @@ public static int computeProduct(int[] nums) {
return total;
}

// The time complexity is:
// The time complexity is: n
// YOUR ANSWER HERE
public static void describeProduct(int[] nums) {
System.out.println("About to compute the product of the array...");
Expand All @@ -59,7 +59,7 @@ public static void describeProduct(int[] nums) {
}


// The time complexity is:
// The time complexity is: n
// YOUR ANSWER HERE
public static int computeFactorial(int n) {
int result = 1;
Expand All @@ -71,6 +71,7 @@ public static int computeFactorial(int n) {

// Assume that the largest number is no bigger than the length
// of the array
// The time complexity is: n^2
public static void computeAllFactorials(int[] nums) {
for(int num : nums) {
int result = computeFactorial(num);
Expand All @@ -80,7 +81,7 @@ public static void computeAllFactorials(int[] nums) {


// assume that each String is bounded by a constant length
// The time complexity is:
// The time complexity is: n
// YOUR ANSWER HERE
public static void checkIfContainedArrayList(ArrayList<String> arr, String target) {
if (arr.contains(target)) {
Expand All @@ -93,7 +94,7 @@ public static void checkIfContainedArrayList(ArrayList<String> arr, String targe

// assume n = wordsA.length = wordsB.length
// assume that each String is bounded by a constant length
// The time complexity is:
// The time complexity is: n^2
// YOUR ANSWER HERE
public static boolean containsOverlap(String[] wordsA, String[] wordsB) {
for(String wordA : wordsA) {
Expand All @@ -107,7 +108,7 @@ public static boolean containsOverlap(String[] wordsA, String[] wordsB) {
}

// assume that each String is bounded by a constant length
// The time complexity is:
// The time complexity is: n
// YOUR ANSWER HERE
public static boolean containsOverlap2(String[] wordsA, String[] wordsB) {
Set<String> wordsSet = new HashSet<>();
Expand All @@ -124,22 +125,22 @@ public static boolean containsOverlap2(String[] wordsA, String[] wordsB) {
return false;
}

// The time complexity is:
// The time complexity is: n
// YOUR ANSWER HERE
public static void printCharacters(char[] chars) {
for (int i = 0; i < chars.length; i++) {
char character = chars[i];
System.out.println("The character at index " + i + " is " + character);
}
}
// The time complexity is:
// The time complexity is: 1
// YOUR ANSWER HERE
public static double computeAverage(double a, double b) {
return (a + b) / 2.0;
}

// assume that each String is bounded by a constant length
// The time complexity is:
// The time complexity is: 1
// YOUR ANSWER HERE
public static void checkIfContainedHashSet(HashSet<String> set, String target)
{
Expand All @@ -157,6 +158,7 @@ public static void checkIfContainedHashSet(HashSet<String> set, String target)
// assume that each String is bounded by a constant length
// What is the time complexity of this method?
// YOUR ANSWER HERE
// The time complexity is: n
public static String emailLookup(String[] names, String[] emails, String queryName) {
for(int i = 0; i < names.length; i++) {
if (names[i].equals(queryName)) {
Expand All @@ -173,14 +175,19 @@ public static String emailLookup(String[] names, String[] emails, String queryNa
// assume that each String is bounded by a constant length
// What is the time complexity of your solution?
// YOUR ANSWER HERE
// The time complexity is: O(1)
public static String emailLookupEfficient(HashMap<String, String> namesToEmails, String queryName) {
return null;
if(namesToEmails.containsKey(queryName)){
return namesToEmails.get(queryName);
}
return "Person not found";
}

// What is the time complexity of this method?
// assume that each String is bounded by a constant length
// (assume the set and list have the same number of elements)
// YOUR ANSWER HERE
// The time complexity is: n^2
public static boolean hasCommon(HashSet<String> wordSet, ArrayList<String> wordList) {
for(String word : wordSet) {
if(wordList.contains(word)) {
Expand All @@ -194,7 +201,13 @@ public static boolean hasCommon(HashSet<String> wordSet, ArrayList<String> wordL
// assume that each String is bounded by a constant length
// What is the time complexity of your new solution?
// YOUR ANSWER HERE
// The time complexity is: O(n)
public static boolean hasCommonEfficient(HashSet<String> wordSet, ArrayList<String> wordList) {
for (String word : wordList) {
if (wordSet.contains(word)) {
return true;
}
}
return false;
}

Expand All @@ -205,18 +218,24 @@ public static boolean hasCommonEfficient(HashSet<String> wordSet, ArrayList<Stri
// What would be a good choice of data structure?
// YOUR ANSWER HERE

//HashMap

// Suppose you are building a music player application where users can create playlists.
// Songs can be added to the end of the playlist in the order the user chooses, and the user can
// skip to the next or previous song. Most operations involve adding songs and accessing them by
// their position in the playlist.
// What would be a good choice of data structure?
// YOUR ANSWER HERE

//List, since we are indexing the position

// Suppose you are developing a search feature that keeps track of the user's
// recent search queries. You want to store the queries in the order they were made,
// so you can display them to the user for quick access. The number of recent searches is
// relatively small, and it is more important to preserve the order of the searches than
// to optimize for fast lookups or deletions.
// What would be a good choice of data structure?
// YOUR ANSWER HERE

//List, assuming doing a loop using length to get index last added
}