C++ Online Test

A gaming company is working on a platformer game. They need a method that will compute the character's final speed, given a map and a starting speed.

The terrain on which the game character moves forward is made from various pieces of land placed together. Implement the method calculateFinalSpeed which takes the initial speed of the character, and an array of degrees of inclination that represent the uneven terrain.

The speed of the character will increase or decrease proportionally to the incline of the land, as shown in the image below:

The magnitude of the angle of inclination will always be < 90°. The speed change occurs only once for each piece of land. The method should immediately return 0 as the final speed if an incline reduces the speed to 0 or below 0, which makes the character lose 1 life.

For example, the below code:

std::cout << GamePlatform::calculateFinalSpeed(60.0, { 0, 30, 0, -45, 0 });

should print:

75

A megastore offers three types of discounts, which are represented as DiscountType enum.

Implement the getDiscountedPrice method which should take the total weight of the shopping cart, the total price, and the discount type. It should return the final discounted price based on the discount schemes as shown in the promotional video below:

(Open full-size video in a new tab)

For example, the following code:

std::cout << MegaStore::getDiscountedPrice(12, 100, MegaStore::DiscountType::Weight);

should print:

82.0

A turn-based strategy game has a grid with water and land. The grid contains a true value where it's water and false where it's land.

The player controls a boat unit with a particular movement pattern. It can only move to fixed destinations from its current position as shown in the image below:

The boat can only move in a direct path through water to the possible destinations, so a destination will become unreachable if there is land in the way. 

Implement the canTravelTo function, that checks whether a destination is reachable by the boat. It should return true for destinations that are reachable according to the pattern above, and false for unreachable or out of bounds destinations which are outside the grid. 

For example, consider the following code:

vector<vector<bool>> gameMatrix = {
    {false, true,  true,  false, false, false},
    {true,  true,  true,  false, false, false},
    {true,  true,  true,  true,  true,  true},
    {false, true,  true,  false, true,  true},
    {false, true,  true,  true,  false, true},
    {false, false, false, false, false, false},
};

cout << canTravelTo(gameMatrix, 3, 2, 2, 2) << endl; // true, Valid move
cout << canTravelTo(gameMatrix, 3, 2, 3, 4) << endl; // false, Can't travel through land
cout << canTravelTo(gameMatrix, 3, 2, 6, 2) << endl; // false, Out of bounds

The following image shows valid and invalid destinations when the boat is in the position (3, 2):

Your company is analyzing malware which targets numerical record files.

The malware uses a sliding window over the array of numbers in a file, and tries to match the following pattern:

Tl, -, -, X, -, -, -, Tr

The entire window is moved so that 'X' passes through all the values and is compared to the numbers at the 'Tl' and 'Tr' locations, which are positioned at a constant offset to 'X'.

The malware has the following rules:

• If the value at the 'Tl' or 'Tr' position of the pattern is bigger or equal to the value at the 'X’ position, the malware replaces the value at 'X' with 0.
• If the value at the 'Tl' or 'Tr' offset is out of bounds, then the value at 'X' is only compared to the other existing value.
• The record is processed in two stages: first, all the positions that should be set to 0 are located, using the original values for comparison. Only after all positions have been identified do they get set to 0.

For example, if the values in a record file are the following:

{1, 2, 0, 5, 0, 2, 4, 3, 3, 3}

The expected values after the malware runs are:

{1, 0, 0, 5, 0, 0, 0, 3, 3, 0}

In this example, both '2's, the '4' and the last '3' were replaced by 0.

Implement the simulate function so that the malware behavior is replicated for further study.

A playlist is considered a repeating playlist if any of the songs contain a pointer to a previous song in the playlist. Otherwise, the playlist will end with the last song which points to NULL.

Implement a function isInRepeatingPlaylist that, efficiently with respect to time used, returns true if a playlist is repeating or false if it is not.

For example, the following code prints "true" as both songs point to each other.

Song* first = new Song("Hello");
Song* second = new Song("Eye of the tiger");
    
first->next(second);
second->next(first);

std::cout << std::boolalpha << first->isInRepeatingPlaylist();

As part of a data processing pipeline, complete the implementation of the makePipeline method:

• The makePipeline method should accept a vector of functions, and it should return a new function that accepts one parameter arg.
• The returned function should call the first function in makePipeline with the parameter arg, and call the second function with the result of the first function.
• The returned function should continue calling each function in makePipeline in order, following the same pattern, and return the value from the last function.

For example,

std::vector<std::function<int (int)>> functions;
functions.push_back([] (int x) -> int { return x * 3; });
functions.push_back([] (int x) -> int { return x + 1; });
functions.push_back([] (int x) -> int { return x / 2; });
std::function<int (int)> func = makePipeline(functions);

and then calling func(3) should return 5.

Implement function countNumbers that accepts a sorted vector of unique integers and, efficiently with respect to time used, counts the number of vector elements that are less than the parameter lessThan.

For example, for vector v containing { 1, 3, 5, 7 }, countNumbers(v, 4) should return 2 because there are two vector elements less than 4.

Implement the unique_names method. When passed two vectors of names, it will return a vector containing the names that appear in either or both vectors. The returned vector should have no duplicates.

For example, calling unique_names(std::vector<std::string>{"Ava", "Emma", "Olivia"}, std::vector<std::string>{"Olivia", "Sophia", "Emma"}) should return a vector containing Ava, Emma, Olivia, and Sophia in any order.

Multiple choice test has several multiple choice questions. Each question can have only one correct answer. Additionally, timed multiple choice test can specify the time allowed for solving each question in the test.

The code below satisfies this specification, but the customer complained that the memory usage of the program constantly increases. Fix this problem.

User interface contains two types of user input controls: TextInput, which accepts all characters and NumericInput, which accepts only digits.

Implement the following methods:

• add on class TextInput - adds the given character to the current value
• getValue on class TextInput - returns the current value
• add on class NumericInput - overrides the base class method so that each non-numeric character is ignored

For example, the following code should output "10":

TextInput* input = new NumericInput();
input->add('1');
input->add('a');
input->add('0');
std::cout << input->getValue();

As a part of the route planner, the routeExists function is used as a quick filter if the destination is reachable, before using more computationally intensive procedures for finding the optimal route.

The roads on the map are rasterized and produce a matrix of boolean values - true if the road is present or false if it is not. The roads in the matrix are connected only if the road is immediately left, right, below or above it.

Finish the routeExists function so that it returns true if the destination is reachable or false if it is not. The fromRow and fromColumn parameters are the starting row and column in the mapMatrix. The toRow and toColumn are the destination row and column in the mapMatrix. The mapMatrix parameter is the above mentioned matrix produced from the map.

For example, for the given rasterized map, the code below should return true since the destination is reachable:

std::vector<std::vector<bool>> mapMatrix {
	{true, false, false},
	{true, true, false},
	{false, true, true}
};

routeExists(0, 0, 2, 2, mapMatrix);

Implement the function findRoots to find the roots of the quadratic equation: ax² + bx + c = 0.  The function should return a pair containing both roots in any order. If the equation has only one solution, the function should return that solution as both elements of the pair. The equation will always have at least one solution.

The roots of the quadratic equation can be found with the following formula:

For example, findRoots(2, 10, 8) should return a pair containing (-1, -4) or (-4, -1) as the roots of the equation 2x² + 10x + 8 = 0 are -1 and -4.

Write a function that, when passed a list and a target sum, returns, efficiently with respect to time used, two distinct zero-based indices of any two of the numbers, whose sum is equal to the target sum. If there are no two numbers, the function should return (-1, -1).

For example, findTwoSum({ 3, 1, 5, 7, 5, 9 }, 10) should return a std::pair<int, int> containing any of the following pairs of indices:

• 0 and 3 (or 3 and 0) as 3 + 7 = 10
• 1 and 5 (or 5 and 1) as 1 + 9 = 10
• 2 and 4 (or 4 and 2) as 5 + 5 = 10

A TrainComposition is built by attaching and detaching wagons from the left and the right sides, efficiently with respect to time used.

For example, if we start by attaching wagon 7 from the left followed by attaching wagon 13, again from the left, we get a composition of two wagons (13 and 7 from left to right). Now the first wagon that can be detached from the right is 7 and the first that can be detached from the left is 13.

Implement a TrainComposition that models this problem.

Binary search tree (BST) is a binary tree where the value of each node is larger or equal to the values in all the nodes in that node's left subtree and is smaller than the values in all the nodes in that node's right subtree.

Write a function that, efficiently with respect to time used, checks if a given binary search tree contains a given value.

For example, for the following tree:

• n1 (Value: 1, Left: null, Right: null)
• n2 (Value: 2, Left: n1, Right: n3)
• n3 (Value: 3, Left: null, Right: null)

Call to contains(n2, 3) should return true since a tree with root at n2 contains number 3.

You are working on a calculator application where users can input a mathematical expression such as: (3 + 5) * (2 - 4).

To correctly evaluate this expression, the application needs to validate the expression and ensure that the parentheses are balanced. The balanced parentheses are crucial for determining the order of operations and evaluating the expression correctly.

You have used an AI assistant to generate the following function to check if the parentheses in an expression are balanced:

bool isBalanced(const std::string& parentheses)
{
    std::stack<char> stack;
    std::unordered_set<char> opening = { '(', '[', '{' };
    std::unordered_set<char> closing = { ')', ']', '}' };
    std::unordered_map<char, char> pairs =
    {
        { ')', '(' },
        { ']', '[' },
        { '}', '{' }
    };

    for (char c : parentheses)
    {
        if (opening.contains(c))
        {
            stack.push(c);
        }
        else if (closing.contains(c))
        {
            if (stack.empty() || stack.top() != pairs[c])
            {
                return false;
            }
            stack.pop();
        }
    }

    return stack.empty();
}

What is correct for the given function?