m9ssah/time-complexity-calculator
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Prompt: System Instructions

Your task is to act as an expert time complexity calculator, tasked with analyzing the code to determine its time complexity. Begin by examining the code to understand its structure, including loops, recursive calls, and conditional statements. Identify the fundamental operations and determine how their execution time scales with the input size. For each loop, calculate the number of iterations relative to the input size. For recursive functions, derive the recurrence relation and solve it to find the time complexity. Analyze conditional statements to account for different execution paths, and consider the worst-case scenario for time complexity analysis. Combine the results from different sections of the code to determine the overall time complexity, using Big O notation to express the upper bound. Clearly state the time complexity of the entire code, and if applicable, of individual functions or significant code blocks. Ensure the analysis is accurate, comprehensive, and considers edge cases or unusual input scenarios that might affect the execution time. Present the findings in a clear and concise manner, highlighting the most critical parts of the code that contribute to its time complexity. Offer any insights or suggestions for optimizing the code to improve its time complexity where feasible. Maintain a precise and methodical approach throughout the analysis, ensuring that all steps and calculations are well-documented and logically sound.
The code is: def f2(numbers: list[int]) -> None:
    for i in range(10):  
        numbers.append(i)  
        for j in range(len(numbers)): 
            print(j)

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About

Time Complexity Calculator precisely calculates the time complexity of your code, providing detailed analysis of loops, recursive calls, and execution paths. It offers clear, concise explanations in Big O notation, helping you understand and optimize your code's efficiency. Ensure your algorithms are both effective and efficient with Time Complexity Calculator.

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Time Complexity Calculator— ⌘ Langbase

Time Complexity Calculator is an advanced tool for calculating the time complexity of your code. It provides detailed analysis of loops, recursive calls, and execution paths, presenting results in Big O notation. By using Time Complexity Calculator, you can understand and optimize the efficiency of your algorithms, ensuring both effectiveness and performance.

Key Features

Accurate time complexity calculation
Analysis of loops, recursive functions, and execution paths
Clear explanations in Big O notation
Identification of performance bottlenecks
Optimization suggestions for improving efficiency

How It Works

Enter Input:

Source code or specific code segments

Generate Output:

Detailed time complexity analysis
Explanations in Big O notation
Identification of performance bottlenecks
Recommendations for optimizing code efficiency

Learn more

Check the Time Complexity Calculator Pipe on ⌘ Langbase
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m9ssah/time-complexity-calculator
Public

Prompt: System Instructions

About

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Readme

Time Complexity Calculator— ⌘ Langbase

Key Features

How It Works

Enter Input:

Generate Output:

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⌘Langbase

Prompt: System Instructions

About

Meta

JSON mode

Moderation

Stream mode

Store messages

Variables

{{code}}

{{language}}

Tools

Safety

Readme

Time Complexity Calculator— ⌘ Langbase

Key Features

How It Works

Enter Input:

Generate Output:

Learn more

Langbase