push_swap

42 Project : push_swap

push_swap

Data on stack; a limited set of instructions; the lowest possible number of operations. Fun with data sorting algorithms!

Table o'Contents

About 📌
push_swap Requirements Overview ✅
push_swap Operations
Operations Example
Complexity
- Asymptotic Notations in Complexity Analysis 🔎
- Table of Common Time Complexities
push_swap Implementation 📜
Data Structures
Processing Input Arguments
Error / Invalid Input Handling
Creating the Stacks
- Visualizing the Stacks
Sorting the Stacks
Freeing the Stacks
The Algorithm (Loosely Based on the QuickSort Algorithm)
- If the stack has 2 values:
- If the stack has 3 values:
- If the stack has more than 3 values:
- Calculating the Best Move
  - ft_best_op_idx()
  - ft_exec_move()
Bonus: Checker Requirements Overview ✅
Checker Implementation 📜
- ft_parse_stack()
- ft_check_op()
- ft_parse_op()
Usage 🏁
Build push_swap
Build checker
Tests 🧪
General Tests
Memory Leak Tests
Run with GDB
Check Available (make) Commands
License 📖

About 📌

`push_swap` Requirements Overview ✅

It takes a stack as an argument, formatted as a list of positive and/or negative integers.
The first element should be at the top of the stack.
The program prints to stdout the instructions to sort stack_a separated by a \n.
The goal is to sort the stack with the lowest possible number of operations.
If no argument is given, the program gives the prompt back and does nothing.
In case of an error, it displays "Error" followed by a \n to stderr.

Errors include:

Some arguments are not integers.
Some arguments are bigger than an integer.
Some arguments are duplicates.

Important

The objective of push_swap is to sort the values in stack_a in ascending order using a set of push_swap operations.

`push_swap` Operations

To get the stack sorted, we have the following operations at our disposal:

Code	Operation	Description
`sa`	swap a	swaps the 2 top elements of `stack_a`
`sb`	swap b	swaps the 2 top elements of `stack_b`
`ss`	swap a & swap b	performs both `sa` and `sb`
`pa`	push a	moves the top element of stack b to the top of `stack_a`
`pb`	push b	moves the top element of stack a to the top of `stack_b`
`ra`	rotate a	shifts all elements of `stack_a` from bottom to top
`rb`	rotate b	shifts all elements of `stack_b` from bottom to top
`rr`	rotate a & rotate b	both `ra` and `rb`
`rra`	reverse rotate a	shifts all elements of `stack_a` from top to bottom
`rrb`	reverse rotate b	shifts all elements of `stack_b` from top to bottom
`rrr`	reverse rotate a & reverse rotate b	performs both `rra` and `rrb`

Operations Example

To show these instructions in action, let’s sort a random list of integers. In this example, we’ll consider that both stacks grow from the right.

Init a and b	`sa`	`pb`	`pb`	`pb`	`ra`	`rb`	`rra`	`rrb`	`sa`	`pa`	`pa`	`pa`
2	`1`											`1`
1	`2`	2									`2`	2
3	3	3	3							`3`	3	3
6	6	6	6	6 `3`	5 3	5 2	`6` 2	6 `3`	`5` 3	5	5	5
5	5	5	5 `2`	5 2	8 2	8 1	5 1	5 2	`6` 2	6 2	6	6
8	8	8 `1`	8 1	8 1	`6` 1	6 `3`	8 3	8 1	8 1	8 1	8 1	8
a b	a b	a b	a b	a b	a b	a b	a b	a b	a b	a b	a b	a b

Complexity

Also known as Time Complexity (studied by Complexity Analysis), is the computational complexity that describes the amount of computer time it takes to run an algorithm (usually measured by the number of needed elementary operations, assuming each operation takes a fixed amount of time to be performed).

Note

Algorithm

Algorithms are procedures or instructions (set of steps) that tell a computer what to do and how to do it.

Computational Complexity

The computational complexity of an algorithm is the amount of resources required to run it. Particular focus is given to:

computation time;
and memory storage requirements.

Since an algorithm's running time usually varies between different inputs of the same size, it is common to consider primarily the worst-case time complexity.

Time Complexity represents the number of times a statement is executed. It is generally expressed as a function of the input size (How quick the run time of an algorithm grows relative to input size).

Such a function is often very difficult to define, and since its running time is usually inconsequential (dependant on hardware, programming language, Operating System software, processing power, etc.), it is customary to focus on the asymptotic behaviour of the complexity.

Important

The asymptotic behaviour of a function is the behaviour of the function as the input size increases.

Taking this into consideration, Time Complexity is most commonly defined using Big O Notation, expressed as $O(n)$ , $O(n\log n)$, $O(n^2)$, etc., where $n$ is the size in units of bits needed to represent the input.

Asymptotic Notations in Complexity Analysis 🔎

Big O Notation

It represents the upper bound of the running time of an algorithm. As mentioned earlier, it gives the worst-case time complexity of an algorithm: the maximum length of time required to run a given algorithm.

Ω (Big Omega) Notation

It represents the lower bound of the running time of an algorithm. It gives the best-case time complexity of an algorithm: the lower-bound of an algorithm's time complexity.

ϴ (Theta) Notation

Represents the upper-bound and lower-bound of the running time of an algorithm, enclosing the function from above and below: it is used to analyze the average-case time complexity of an algorithm.

Little o Notation

Is used as a tight upper bound on the growth of an algorithm’s effort, even though, as written, it can also be a loose upper bound that cannot be tight.

ω (Little Omega) Notation

Describes the relationship between two functions when one grows strictly faster than the other: a relative growth rate.

Table of Common Time Complexities

Complexity	Time Complexity	Example
$O(1)$	Constant	Finding the median value in a sorted array of numbers.
$O(log$ n)	Logarithmic	Binary Search
$O(n)$	Linear	Finding the smallest/largest element in an array.
$O(n\log n)$	Log Linear	Fastest possible comparison sort (Fast Fourier Transform).
$O(n^2)$	Quadratic	Bubble sort, Insertion Sort, Direct Convolution.
$O(n^3)$	Cubic	Naive multiplication of $n \times n$ matrices; Calculating partial correlation.
...	...	...

`push_swap` Implementation 📜

The sorting algorithm used in this implementation is a variation of the QuickSort Algorithm adapted to sort stacks using only the aforementioned operations.

Before we get into the nitty and gritty details of the algorithm, let's take a look at how the program handles input arguments and sets up the stacks.

Data Structures

stack_a and stack_b, are arrays of t_elem structs:

typedef struct s_elem {
	int	num;
	int	index;
	int	set;
}	t_elem;

Processing Input Arguments

int	main(int argc, char **argv)
{
	(...)
	++argv;
	input_list = argv;
	must_free = 0;
	if (argc == 2)
		input_list = ft_get_elems(&argc, argv, &must_free);
	(...)
}

First, it increments argv so to skip the program's name;
It then assigns argv to input_list.
Initializes must_free flag to 0 (This flag is used to indicate that the memory was allocated and therefore needs to be freed later);
If argc is 2 (meaning a single command line argument was provided) ft_get_elems() is called:

static char	**ft_get_elems(int *argc, char **argv, int *must_free)
{
	char	**split_list;

	split_list = ft_split(argv[0], ' ');
	*argc = ft_argv_count(split_list) + 1;
	*must_free = 1;
	return (split_list);
}

Splits the single argument into multiple elements based on the specified separator (' ') storing the result in split_list. This is accomplished using the ft_split function defined in my custom libft helper library;

It counts the number of elements in the split_list using the ft_argv_count() and adds 1 to the count (to account for the program name skipped at the start of execution). This updated count is assigned to argc.

It sets the must_free flag to 1 (indicating split_list must be freed).

It returns split_list containing the list of input elements.

Error / Invalid Input Handling

int	main(int argc, char **argv)
{
	(...)
	error = ft_errors(argc, input_list);
	if (error <= 0)
	{
		ft_free(NULL, NULL, input_list, must_free);
		return (0);
	}
	(...)
}

Next, the program checks for invalid input in the input_list using the ft_errors() function:
- If an error is found (indicated by a return value less than or equal to 0), it frees any previously allocated memory and exits the cleanly.

int	ft_errors(int argc, char **input_list)
{
	if (argc == 1)
		return (0);
	if (ft_are_args_nbr(argc, input_list) == -1)
	{
		ft_putstr_fd("Error\n", 2);
		return (-1);
	}
	if (ft_is_duplicate(argc, input_list) == -1)
	{
		ft_putstr_fd("Error\n", 2);
		return (-1);
	}
	return (1);
}

In case argc is 1, meaning no arguments were provided, the function simply returns 0.

If the values in input_list are NOT numbers, the call to ft_are_args_nbr() returns -1. In this case, the function prints "Error\n" to the stderr and returns -1.

Lastly if there are duplicate numbers in the input_list, the call to ft_is_duplicate() returns -1, in which case the function prints "Error\n" to the stderr and returns -1.

If no errors are detected, the function returns 1.

Creating the Stacks

int	main(int argc, char **argv)
{
	(...)
	stack_a = ft_create_stack(argc, input_list, 1);
	stack_b = ft_create_stack(argc, input_list, 0);
	(...)
}

If no errors were detected, the program creates two stacks (stack_a and stack_b) from the input arguments using the ft_create_stack() function (the third argument indicates whether the stack should be filled with the input elements (stack_a) or left empty (stack_b).

t_elem	*ft_create_stack(int argc, char **argv, int select)
{
	t_elem	*stack;
	int		i;

	stack = malloc(sizeof(t_elem) * (argc + 1));
	if (stack == NULL)
		return (NULL);
	i = 0;
	while (i < (argc - 1))
	{
		if (select == 1)
		{
			stack[i].num = ft_atoi(argv[i]);
			stack[i].set = 1;
		}
		else
		{
			stack[i].num = 0;
			stack[i].set = 0;
		}
		stack[i].index = i;
		++i;
	}
	stack[i].index = -1;
	return (stack);
}

It allocates memory for the stack using malloc(). The size of the allocated memory is the size of t_elem multiplied by (argc + 1) (the extra element is used as a sentinel value signaling the end of the stack.

If the memory allocation fails, it returns NULL.

Initializes i to 0.

Then it enters a loop initializing each element of the stack, with i as the index.

If select is 1, it initializes stack_a:

Sets the stack[i].num field of the current element to the integer value of the corresponding argument (converted using ft_atoi()).

Sets the stack[i].set field to 1 (used for some conditional checks later in the program).

If select is 0, it initializes stack_b:

Sets the stack[i].num field of the current element to 0.

Sets stack[i].set fields of the current element to 0.

At the end of each iteration, sets the stack[i].index field of the current element to i (representing the position of the element in the stack).

After the loop is done, the stack[i].index field is set to -1, signaling the end of the stack (sentinel value).

It returns the stack.

Visualizing the Stacks

After initialization, the array of t_elem structs can be visualized as follows:

Take the following input example: "7 5 3 4 9 6 8 2 1"

stack.num	stack.index	stack.set
7	0	1
5	1	1
3	2	1
4	3	1
9	4	1
6	5	1
8	6	1
2	7	1
1	8	1
0	-1	0

Sorting the Stacks

int	main(int argc, char **argv)
{
	(...)
	if (ft_is_sorted(stack_a) == -1)
		ft_sort(stack_a, stack_b, argc);
	(...)
}

If stack_a is not already sorted (indicated by ft_is_sorted() returning -1), it is sorted using ft_sort().

static void	ft_sort(t_elem *stack_a, t_elem *stack_b, int argc)
{
	if (argc == 3)
	{
		if (ft_is_sorted(stack_a) == -1)
			ft_swap_elem(stack_a, "sa\n");
	}
	else if (argc == 4)
		ft_sort_three(stack_a);
	else
		ft_sort_stack(stack_a, stack_b, argc);
}

If argc is 3, it means there are two elements in stack_a (plus the program's name).

In this case, it checks if stack_a is already sorted. If it is NOT sorted (indicated by ft_is_sorted() returning -1):

Swaps the two elements using ft_swap_elem().

If argc is 4, it means there are three elements in stack_a.

In this case, it sorts the three elements using ft_sort_three().

If argc is greater than 4, meaning there are more than three elements in stack_a:

The stack is sorted using ft_sort_stack().

Note

We'll get into more detail about how these subroutines work in the algorithm description section.

Freeing the Stacks

int	main(int argc, char **argv)
{
	(...)
	ft_free(stack_a, stack_b, input_list, must_free);
	return (0);
}

Finally, it frees any allocated memory before exiting the program using ft_free().

The Algorithm (Loosely Based on the `QuickSort Algorithm`)

The algorithm implemented in this project is inspired by the QuickSort Algorithm.

It leverages a second "temporary" stack (stack_b) in order to sort the stack (stack_a) in ascending order.
Calculates the median value (used as a pivot, the key concept of the standard QuickSort Algorithm) in the input stack (stack_a), then proceeds to push elements into stack_b.
If the pushed element is larger than the median we rotate it to the bottom of stack_b. We do this until there are only 3 elements left in stack_a. We get those sorted.
Then the algorithm starts moving one element at a time back to stack_a after calculating the least costly element to move at each iteration, effectively sorting the unordered input stack into ascending order.

Following this overview is a description of each case handled by the algorithm implemented in this project.

If the stack has 2 values:

If the elements are already in order:
- No operations are necessary.
If the elements are NOT in order:
- A single swap operation is performed to sort stack_a.

If the stack has 3 values:

The logic in ft_sort_three.c is triggered. This subroutine works as follows:

It starts by getting the start and end indices of stack_a.
It checks if stack_a is already sorted, if the minimum value is at the start of stack_a and the maximum value is at the end,
- Returns without executing any operations.
If the minimum value is at the start and the maximum value is in the middle (second position):
- It swaps the top two elements.
- Then rotates stack_a.

This effectively moves the maximum value to the top (end) of stack_a.

If the maximum value is at the start of stack_a:
- it rotates the stack_a.

This moves the maximum value to the end.

If the element at the bottom (start) is greater than the middle element:
- It swaps the first two elements.
If the minimum value is at the end of stack_a:
- A reverse rotation is performed.

This effectively moves the minimum value to the bottom (start) of stack_a.

Note

See the ft_sort_three.c for a direct look into the implementation of this part of the algorithm.

If the stack has more than 3 values:

The logic in ft_sort_stack.c is triggered. This is where we get into the meat of the algorithm:

It starts by setting i to the start of stack_a;
It then calculates the median value of stack_a using ft_median().
Loops through stack_a:
- Pushing elements to stack_b until there are only three elements left in stack_a.
- If the current top element in stack_b is greater than the median and the number of elements in stack_a is greater than 3, it rotates stack_b.
The three remaining elements in stack_a are sorted with ft_sort_three.c.
i is reset to the start of stack_b;
It then loops through stack_b:
- For each element, it calculates the index in stack_a that requires the minimum number of operations to move that element into the correct sorted position.
It rotates stack_a until the value right above the median is at the top.
It pushes the top element of stack_b to stack_a.
It rotates stack_a to move its new smallest element to the top.

This process is repeated until all the values in stack_a are sorted.

Calculating the Best Move

ft_exec_move() executes rotation and push operations according to the return of ft_best_op_idx() which calculates the optimal move to make when transferring elements from stack_b back to stack_a during the sorting process.

`ft_best_op_idx()`

ft_best_op_idx() loops through all the elements in stack_a calling ft_get_align_ops() to calculate the cost (number of operations) of moving that element to the top and aligning it with the corresponding element in stack_b.
- ft_get_align_ops() subroutine calculates the total number of operations needed to move an element at a given index in stack_a to the top, and to align a corresponding element in stack_b with it.
  - First it calculates the cost to move the element at index idx in stack_a to the top.
  - Afterwards calculates the cost to move the corresponding element in stack_b to the top.
  - It returns the total cost of aligning the element in stack_b with the element in stack_a.

In short, ft_best_op_idx() calculates the index that has the minimum cost.

`ft_exec_move()`

Once the optimal index is found, ft_exec_move() is called (with the calculated index as an argument) to actually execute the moves:
- Gets the start index of stack_a storing it in start.
- Calls ft_check_order() to check if any elements in stack_b are already in order with stack_a. It saves the number of elements found to already be in order into ordered.
- Then calls ft_order() to move elements from stack_b to stack_a that are already in the correct order relative to each other.
- If necessary, handles the adjustment of the index idx after ordered elements have been moved from stack_b to stack_a.
- If idx is past the end of stack_a:
  - It is recalculated and looped back to the start of the stack.
- Else, if idx is past the start of stack_a:
  - It is recalculated and looped back to the end of the stack.
- Rotates stack_a to move the element at idx to the top.
- Again, check if idx is past the end of stack_a:
  - If so, it is recalculated and looped back to the start of the stack.
- Checks if the min or max value of stack_b is less/greater than the element now at the top of stack_a:
  - If so, it *rotates stack_b to move its min to the top.
- Else,
  - It rotates stack_b to move the smallest element greater than stack_a's top to the top of stack_b.
- Pushes the top element of stack_b to stack_a.

Bonus: Checker Requirements Overview ✅

The checker program checks whether the list of instructions generated by the push_swap program actually sorts the stack correctly.

Takes stack_a as an argument.
If no argument is given, it stops displaying nothing.
Waits until instructions are read from stdin, each instruction separated by a \n.
Once all instructions have been read, it executes them on the stack received as an argument.
If after executing the instructions, the stack is sorted:
- Displays "OK" followed by a \n.
Else:
- Displays "KO" followed by a \n.
In case of an error, it displays "Error" followed by a \n to stderr.

Errors include:

Some arguments are not integers.
Some arguments are bigger than an integer.
Some arguments are duplicates.
An instruction doesn't exist or is incorrectly formatted.

Checker Implementation 📜

/* push_swap checker (main_checker.c) */
int	main(int argc, char **argv)
{
	char	**input_list;
	t_elem	*stack_a;
	t_elem	*stack_b;
	int		must_free;
	int		error;

	++argv;
	input_list = argv;
	must_free = 0;
	if (argc == 2)
		input_list = ft_get_elems(&argc, argv, &must_free);
	error = ft_errors(argc, input_list);
	if (error <= 0)
	{
		ft_free(input_list, must_free);
		return (0);
	}
	stack_a = ft_create_stack(argc, input_list, 1);
	stack_b = ft_create_stack(argc, input_list, 0);
	ft_free(input_list, must_free);
	ft_check_stack(stack_a, stack_b);
	free(stack_a);
	free(stack_b);
	return (0);
}

The checker program reads a set of instructions from stdin and executes them on the stack received as an argument. It has a very similar structure and uses many of the same subroutines as this project's push_swap implementation.

Important

The main difference between the checker program and the push_swap program is that other than sorting stack_a it also checks if the instructions produced by push_swap are valid.

`ft_parse_stack()`

void	ft_check_stack(t_elem *stack_a, t_elem *stack_b)
{
	int		result;
	int		start;
	char	*line;

	result = 1;
	while (result)
	{
		line = get_next_line(0);
		if (!line)
			result = 0;
		else
			ft_check_op(stack_a, stack_b, line);
	}
	start = 0;
	while ((stack_b[start].index != -1) && (stack_b[start].set != 1))
		++start;
	if ((ft_is_sorted(stack_a) == 1) && (stack_b[start].index == -1))
		ft_putstr_fd("OK\n", 1);
	else
		ft_putstr_fd("KO\n", 1);
}

It takes in two stacks - stack_a and stack_b.
It reads input commands line by line using get_next_line().
- For each line, it calls ft_check_op() which will process and check if the line contains a valid instruction.
After reading all the input, it checks if the stacks are in the expected sorted state:
- stack_b should be empty, so it loops through to find the first element with index = -1 (the sentinel value signifying the end of the stack).
- stack_a should be sorted, so it calls ft_is_sorted() to check.
- If both conditions are met:
  - It prints "OK\n" to stdout, meaning the instructions are valid.
  - else prints "KO\n" to stdout, meaning the instructions are invalid.

`ft_check_op()`

static void	ft_check_op(t_elem *stack_a, t_elem *stack_b, char *op)
{
	int		result;

	if ((op == NULL) || (ft_strlen(op) == 1))
		result = -1;
	else
		result = ft_parse_op(op, stack_a, stack_b);
	if (op != NULL)
		free(op);
	if (result == -1)
	{
		free(stack_a);
		free(stack_b);
		get_next_line(0);
		ft_putstr_fd("Error\n", 2);
		exit(EXIT_FAILURE);
	}
}

It takes in stack_a and stack_b, and the operation string op.
It first checks if the op string is valid:
- If it's NULL or only 1 character, set result = -1 to indicate invalid operation.
- Else it calls ft_parse_op() to execute the operation on the appropriate stack.
It frees the op string.
It checks the return value of ft_parse_op() stored in result. If -1, it means an invalid operation was parsed.
- It frees the stacks.
- It reads and discards the rest of input.
- It prints "Error\n" to stderr and exits.

`ft_parse_op()`

static int	ft_parse_op(char *op, t_elem *stack_a, t_elem *stack_b)
{
	if (ft_strncmp_checker(op, "pa\n", 3) == 0)
		ft_push_elem(stack_b, stack_a);
	else if (ft_strncmp_checker(op, "pb\n", 3) == 0)
		ft_push_elem(stack_a, stack_b);
	else if (ft_strncmp_checker(op, "sa\n", 3) == 0)
		ft_swap_elem(stack_a);
	else if (ft_strncmp_checker(op, "sb\n", 3) == 0)
		ft_swap_elem(stack_b);
	else if (ft_strncmp_checker(op, "ss\n", 3) == 0)
		ft_swap_both(stack_a, stack_b);
	else if (ft_strncmp_checker(op, "ra\n", 3) == 0)
		ft_rotate(stack_a);
	else if (ft_strncmp_checker(op, "rb\n", 3) == 0)
		ft_rotate(stack_b);
	else if (ft_strncmp_checker(op, "rr\n", 3) == 0)
		ft_rotate_both(stack_a, stack_b, 0);
	else if (ft_strncmp_checker(op, "rra\n", 4) == 0)
		ft_rev_rotate(stack_a);
	else if (ft_strncmp_checker(op, "rrb\n", 4) == 0)
		ft_rev_rotate(stack_b);
	else if (ft_strncmp_checker(op, "rrr\n", 4) == 0)
		ft_rotate_both(stack_a, stack_b, 1);
	else
		return (-1);
	return (1);
}

Parses an op string and executes the corresponding operation on stack_a or stack_b.

It compares the input string op to each possible operation. Based on the matching operation, it calls the corresponding stack operation function.
- If there is no match, it returns -1 to indicate invalid operation.
- Otherwise it executes the operation and returns 1.

Usage 🏁

First, clone the repository, and cd into the project folder:

git clone git@github.com:PedroZappa/42_push_swap.git 42_push_swap_passunca
cd 42_push_swap_passunca

Build `push_swap`

To build push_swap run:

make

This command will fetch the dependencies and build the project.

Here are a couple different ways to run the program:

./push_swap 2 1 3 6 5 8
# or
./push_swap "2 1 3 6 5 8"
# or
ARG="2 1 3 6 5 8"; ./push_swap $ARG
# and to run it with the checker provided by 42:
ARG="2 1 3 6 5 8"; ./push_swap $ARG | ./checker_linux $ARG

Build `checker`

To build checker, run:

make bonus

To manually test checker, run:

echo -e "rra\npb\nsa\nrra\npa" > input.txt
./checker 3 2 1 0 < input.txt

Tests 🧪

I've prepared several make rules to test the push_swap program and the checker in a systematic and automated way.

General Tests

To run the tests present on the subject run:

make test_subject	# for push_swap
make test_checker	# for checker
make check_ext_func	# Checks external functions in use

To test push_swap with a custom number of input elements run:

make test_n n=42

To test push_swap together checker with a custom number of input elements run:

make test_checker n=42

n is the number of input elements, in these examples, 42.

Memory Leak Tests

To check if push_swap has memory leaks run:

make valgrind

Run with GDB

To run push_swap with GDB run:

make gdb arg="2 1 3 6 5 8"

if no argument is passed, it runs with the default argument defined in the Makefile.

Check Available (make) Commands

To check all available commands including tests run:

make help

Important

Check the Makefile for more details about what's going on with each command. there is a lot of juicy juice gathered in it for your Make'ing enjoyment 🤓

License 📖

This work is published under the terms of 42 Unlicense.

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Name		Name	Last commit message	Last commit date
Latest commit History 352 Commits
bonus		bonus
scripts		scripts
src		src
video		video
.gdbinit		.gdbinit
.gitignore		.gitignore
LICENSE		LICENSE
Makefile		Makefile
README.md		README.md
checker_linux		checker_linux

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PedroZappa/42_push_swap

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push_swap

Table o'Contents

About 📌

push_swap Requirements Overview ✅

push_swap Operations

Operations Example

Complexity

Asymptotic Notations in Complexity Analysis 🔎

Big O Notation

Ω (Big Omega) Notation

ϴ (Theta) Notation

Little o Notation

ω (Little Omega) Notation

Table of Common Time Complexities

push_swap Implementation 📜

Data Structures

Processing Input Arguments

Error / Invalid Input Handling

Creating the Stacks

Visualizing the Stacks

Sorting the Stacks

Freeing the Stacks

The Algorithm (Loosely Based on the QuickSort Algorithm)

If the stack has 2 values:

If the stack has 3 values:

If the stack has more than 3 values:

Calculating the Best Move

ft_best_op_idx()

ft_exec_move()

Bonus: Checker Requirements Overview ✅

Checker Implementation 📜

ft_parse_stack()

ft_check_op()

ft_parse_op()

Usage 🏁

Build push_swap

Build checker

Tests 🧪

General Tests

Memory Leak Tests

Run with GDB

Check Available (make) Commands

License 📖

About

Topics

Resources

License

Stars

Watchers

Forks

Languages

`push_swap` Requirements Overview ✅

`push_swap` Operations

`push_swap` Implementation 📜

The Algorithm (Loosely Based on the `QuickSort Algorithm`)

`ft_best_op_idx()`

`ft_exec_move()`

`ft_parse_stack()`

`ft_check_op()`

`ft_parse_op()`

Build `push_swap`

Build `checker`