Break down the sliding window technique to solve computational problems with optimized efficiency.

Coding

Uses a window, either fixed or dynamic, to optimize the analysis of sequential data (substring or subarray) through iterative processing, minimizing the need for nested loops.

Sliding Window

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Behavioral

# Statement
Given an array of positive integers, `nums`, and a positive integer, `target`, find the minimum length of a contiguous subarray whose sum is greater than or equal to the `target`. If no such subarray is found, return `0`.

**Constraints:**

* $1$ $\leq$ `target` $\leq$ $10^4$
* $1$ $\leq$ `nums.length` $\leq$ $10^3$ 
* $1$ $\leq$ `nums[i]` $\leq$ $10^3$

# Examples

# Understand the problem

Let’s take a moment to make sure you’ve correctly understood the problem. The quiz below helps you check if you’re solving the correct problem:


What is the output if the following values are given as input?

nums = [1, 2, 7, 1, 8]

target = 9

What is the output if the following values are given as input?
nums = [1, 2, 7, 1, 8]
target = 9

What is the output if the following values are given as input?

nums = [1, 3, 4, 5, 2]

target = 12

What is the output if the following values are given as input?
nums = [1, 3, 4, 5, 2]
target = 12

What is the output if the following values are given as input?

nums = [7, 2, 4, 6, 5, 8]

target = 6

What is the output if the following values are given as input?
nums = [7, 2, 4, 6, 5, 8]
target = 6

Minimum Size Subarray Sum

Minimum Size Subarray Sum

We have a game for you to play. Rearrange the logical building blocks to develop a clearer understanding of how to solve this problem.


Implement your solution in the following coding playground:

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

# Review Code\nEdward, your current task is to review the `min_sub_array_len` function(s) and the other function(s) invoked in it/them.\n\n-Take your time and review the candidate's solution code.\n- Do not review any extra/helper files or functions not invoked in the solution function `min_sub_array_len`.\n- 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. \n- Also, if the solution code doesn’t use the coding pattern stated above, then please encourage the candidate to reattempt the problem using that pattern corectly.

# Review time complexity\n- Please provide a brief time complexity analysis of the function(s) `min_sub_array_len`. \n- While calculating time complexity, include the time complexity of built-in Python functions invoked by the code. \n- The answer should be to the point in approximately 60 words.

# Review space complexity\n- Please provide a brief space complexity analysis of the function(s) `min_sub_array_len`. \n- While calculating space complexity, include the space complexity of built-in Python functions invoked by the code. \n- 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). \n- The answer should be to the point in approximately 60 words.

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
        """
        # Solution
        def min_sub_array_len_eval(target, nums):
            window_size = float('inf')
            start = 0
            sum = 0
            for end in range(len(nums)):
                sum += nums[end]
                while sum >= target:
                    curr_subarr_size = (end + 1) - start
                    window_size = min(window_size, curr_subarr_size)
                    sum -= nums[start]
                    start += 1

            if window_size != float('inf'):
                return window_size

            return 0
        
        # Expected output
        expected = min_sub_array_len_eval(self.__inputs[0], self.__inputs[1])

        # Actual output
        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

def min_sub_array_len(target, nums):

    # Replace this placeholder return statement with your code
    
    return -1

minimum-size-subarray-sum.yaml

testcases:
  - name: "testcase 1"
    inputs:
    - 1 : 7
    - 2 : [2, 3, 1, 2, 4, 3]
    output: 
    - 1 : 2
  - name: "testcase 2"
    inputs:
    - 1: 4
    - 2: [1, 4, 4]
    output:
    - 1 : 1
  - name: "testcase 3"
    inputs:
    - 1 : 11
    - 2 : [1, 1, 1, 1, 1, 1, 1, 1]
    output: 
    - 1 : 0
  - name: "testcase 4"
    inputs:
    - 1: 10
    - 2: [1, 2, 3, 4]
    output:
    - 1 : 4
  - name: "testcase 5"
    inputs:
    - 1: 5
    - 2: [1, 2, 1, 3]
    output:
    - 1 : 3

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
 """

 target_lower_bound = 1
 target_upper_bound = 10**9

 nums_length_lower_bound = 1
 nums_length_upper_bound = 10**5

 nums_value_lower_bound = 1
 nums_value_upper_bound = 10**4

 target = self.__inputs[0]
 nums = self.__inputs[1]

 def is_valid_1d_array(arr):
 if not isinstance(arr, list):
 return False # Not a valid 1D array if it's not a list
 
 return all(isinstance(elem, int) and not isinstance(elem, bool) for elem in arr)
 
 def check_overflow(arr, t):
 for num in arr:
 if not (-2**31 <= num <= (2**31) - 1):
 return num
 if not (-2**31 <= t <= (2**31) - 1):
 return t
 return True

 # inputs can be accessed using self.__inputs starting from 0 to len(self.__inputs) - 1
 if not is_valid_1d_array(nums):
 self.store_result ("Not a valid test case", ValidationFunction.FAIL)
 
 elif check_overflow(nums, target) != True:
 num = check_overflow(nums, target)
 self.store_result (str(num) + " is not a valid value of type integer", ValidationFunction.FAIL) 

 elif target < target_lower_bound or target > target_upper_bound:
 self.store_result ("expected 'target' to have value from " + str(target_lower_bound) + " to " + str(target_upper_bound) + " only", ValidationFunction.FAIL)

 elif len(nums) < nums_length_lower_bound or len(nums) > nums_length_upper_bound:
 self.store_result("expected 'nums' to have " + str(nums_length_lower_bound) + " <= size <= " + str(nums_length_upper_bound) + " but got " + str(len(nums)), ValidationFunction.FAIL)

 elif not all (nums_value_lower_bound <= value <= nums_value_upper_bound for value in nums):
 self.store_result("'nums' must consist of values from " + str(nums_value_lower_bound) + " to " + str(nums_value_upper_bound) + " only", ValidationFunction.FAIL)
 
 else:
 self.store_result("", ValidationFunction.PASS)

Try to solve the Minimum Size Subarray Sum problem.

Problem: Minimum Size Subarray Sum

Statement

Examples

Understand the problem

Figure it out!