Get started with two-pointers to solve linear data structure problems efficiently.

Coding

The Two Pointers pattern uses two coordinated pointers or iterators to traverse data efficiently. By adjusting their movement according to problem-specific conditions, it uncovers meaningful connections within any data structure, reducing redundant work and improving performance.

Two Pointers

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Behavioral

What is the next permutation of the given array?

`nums` $= [1, 5, 4, 2]$

What is the next permutation of the given array?
<code>nums</code> <math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo>=</mo><mo stretchy="false">[</mo><mn>1</mn><mo separator="true">,</mo><mn>5</mn><mo separator="true">,</mo><mn>4</mn><mo separator="true">,</mo><mn>2</mn><mo stretchy="false">]</mo></mrow><annotation encoding="application/x-tex">= [1, 5, 4, 2]</annotation></semantics></math>=[1,5,4,2]

What is the next permutation of the given array?

`nums` $= [1, 2, 2, 1]$

What is the next permutation of the given array?
<code>nums</code> <math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo>=</mo><mo stretchy="false">[</mo><mn>1</mn><mo separator="true">,</mo><mn>2</mn><mo separator="true">,</mo><mn>2</mn><mo separator="true">,</mo><mn>1</mn><mo stretchy="false">]</mo></mrow><annotation encoding="application/x-tex">= [1, 2, 2, 1]</annotation></semantics></math>=[1,2,2,1]

If $[3, 4, 5, 2]$ is the next permutation, then what is its immediately previous permutation?

If <math xmlns="http://www.w3.org/1998/Math/MathML"><semantics><mrow><mo stretchy="false">[</mo><mn>3</mn><mo separator="true">,</mo><mn>4</mn><mo separator="true">,</mo><mn>5</mn><mo separator="true">,</mo><mn>2</mn><mo stretchy="false">]</mo></mrow><annotation encoding="application/x-tex">[3, 4, 5, 2]</annotation></semantics></math>[3,4,5,2] is the next permutation, then what is its immediately previous permutation?

Next Permutation

Next Permutation

def nextPermutation(nums):
    
    # Write your code here
    pass


# Quick Fix You are Edward, a Senior Software Engineer who specializes in coding interview patterns, data structures and algorithms, and is great at debugging issues in code. - Edward, please keep in mind that you do not have to print the data of the placeholders. Also, do not mention anything about yourself. Edward, you are given the following data in the placeholders: - Function name: `nextPermutation` - User’s submitted solution code: USER_CODE - Error: ERROR_DESCRIPTION - Failed test case: FAILED_TEST_CASE - Coding language: Python  - Edward, your task is to understand the type of error that is occurring in the coding language provided. - Once you understand the error using the error’s description, and why the test case failed. You will suggest how the learner can improve their solution code to fix the error. - Edward, you will not give the corrected code, just a hint on what the error tells, and how to fix it. - Edward, please limit your response strictly to 100 words. No more words than the limit.

# Review Code Edward, your current task is to review the `nextPermutation` function(s) and the other function(s) invoked in it/them. - Take your time and review the user’s solution code. - Do not review any extra/helper files or functions not invoked in the solution function `nextPermutation`. - Do not review the code of data structure objects instantiated like a binary tree, linked list, trie, union find, etc., in the solution functions. Just review the solution/algorithm function of the problem. - Also, if the solution code doesn’t use the coding pattern stated above, then please encourage the user to reattempt the problem, to correctly use the coding pattern.

# Review time complexity - Please provide a brief time complexity analysis of the function(s) `nextPermutation`. - While calculating time complexity, include the time complexity of built-in Python functions invoked by the code. - The answer should be to the point and in a few lines.

# Review space complexity - Please provide a brief space complexity analysis of the function(s) `nextPermutation`. - While calculating space complexity, include the space complexity of built-in Python functions invoked by the code. - Do not include the space used for the input parameters and the space used for just returning an output (not used as a scratch space). - The answer should be to the point and in a few lines.

def evaluate_results(self) -> object:
 """
 self.__inputs is the list of inputs that are passed as input to function
 self.__actual_output is a list of outputs that is produced by the learner's code
 return : self.__edu__result object
 """
 def swap(nums, i, j):
 temp = nums[i]
 nums[i] = nums[j]
 nums[j] = temp
 
 def nextPermutationEval(nums):
 i = len(nums) - 2
 
 while i >= 0 and nums[i + 1] <= nums[i]:
 i -= 1
 
 if i >= 0:
 j = len(nums) - 1
 while nums[j] <= nums[i]:
 j -= 1
 
 swap(nums, i, j)
 
 reverse(nums, i + 1, len(nums) - 1)
 return nums
 
 def reverse(nums, start, end):
 while start < end:
 swap(nums, start, end)
 start += 1
 end -= 1
 
 expected = nextPermutationEval(self.__inputs[0])
 actual = self.__actual_outputs[0]

 # multiple outputs will be added at each index respectively for a single test_case
 expected_outputs = [] 
 # store the 1st expected output that should be displayed to the user 
 expected_outputs.append(expected)

 if json.dumps(expected) == json.dumps(actual):
 self.__edu_result.store_result(expected_outputs, TestCaseResult.PASS)
 else:
 self.__edu_result.store_result(expected_outputs, TestCaseResult.FAIL)

 return self.__edu_result

from Solution import nextPermutation

def nextPermutationDriver(nums):
    nextPermutation(nums)
    return nums


next_permutation.yaml

testcases:
  - name: "testcase 1"
    inputs:
      - 1: [4, 1, 5, 2]
    output:
      - 1: [4, 2, 1, 5]

  - name: "testcase 2"
    inputs:
      - 1: [2, 3, 1, 3]
    output:
      - 1: [2, 3, 3, 1]

  - name: "testcase 3"
    inputs:
      - 1: [1, 5, 1, 1]
    output:
      - 1: [5, 1, 1, 1]

  - name: "testcase 4"
    inputs:
      - 1: [5, 3, 4, 2]
    output:
      - 1: [5, 4, 2, 3]

  - name: "testcase 5"
    inputs:
      - 1: [1, 4, 3, 2]
    output:
      - 1: [2, 1, 3, 4]


def sum(input_1, input_2):
    return input_1+input_2

def validate_inputs(self) -> None:
 """
 self.__inputs is the list of inputs that are passed as input to function.
 Store the result using the self.store_result(error_msg, status)
 return : void
 """
 
 def is_valid_1d_array(arr):
 # Must be a list
 if not isinstance(arr, list):
 return False
 
 # Must contain only integers (bool is a subclass of int → exclude)
 return all(isinstance(elem, int) and not isinstance(elem, bool) for elem in arr)
 
 # Extract the nums array
 nums_array = self.__inputs[0]
 
 # 1. Validate structure
 if not is_valid_1d_array(nums_array):
 self.store_result(("Not a valid 1D integer array."), ValidationFunction.FAIL)
 
 # 2. Validate element values: 0 ≤ nums[i] ≤ 100
 elif not all(0 <= num <= 100 for num in nums_array):
 self.store_result(("Each element must be in range 0 to 100."), ValidationFunction.FAIL)
 
 # 3. Validate length: 1 ≤ len(nums) ≤ 100
 elif not (1 <= len(nums_array) <= 100):
 self.store_result(("Array length must satisfy 1 ≤ nums.length ≤ 100."), ValidationFunction.FAIL)
 
 # 4. Passed all checks
 else:
 self.store_result("", ValidationFunction.PASS)

Try to solve the Next Permutation problem.

Problem: Next Permutation

Statement

Examples

Understand the problem

Figure it out!