Question 1

What is time complexity?

Accepted Answer

Time complexity describes how the runtime of an algorithm grows as the input size increases. It is expressed using Big-O notation — for example, O(n) means the runtime grows linearly with the input size, while O(n²) means it grows quadratically.

Question 2

What is Big-O notation?

Accepted Answer

Big-O notation is a mathematical notation that describes the upper bound of an algorithm's growth rate. Common complexities include O(1) constant, O(log n) logarithmic, O(n) linear, O(n log n) linearithmic, O(n²) quadratic, and O(n³) cubic.

Question 3

How do I find the time complexity of my Python code?

Accepted Answer

Paste your Python code into TC Getter and the tool will automatically parse it into an Abstract Syntax Tree, identify loops, comprehensions, and function definitions, and display Big-O annotations inline next to each relevant line.

Question 4

Does this tool send my code to a server?

Accepted Answer

No. TC Getter runs entirely in your browser using WebAssembly. Your code never leaves your machine — there is no backend server involved.

Question 5

How do nested loops affect time complexity?

Accepted Answer

Each level of loop nesting multiplies the complexity. A single loop is O(n), two nested loops are O(n²), and three nested loops are O(n³). TC Getter detects nesting depth automatically and annotates functions accordingly.

Question 6

What Python constructs does TC Getter analyze?

Accepted Answer

TC Getter analyzes for loops, while loops, list comprehensions, generator expressions, and function definitions. It computes per-line complexity and overall function-level complexity based on maximum nesting depth.

Question 7

What is the difference between time complexity and space complexity?

Accepted Answer

Time complexity measures how the number of operations grows with input size. Space complexity measures how memory usage grows. For example, copying a list is O(n) space, while sorting in-place is O(1) extra space. TC Getter focuses on time complexity analysis.

Question 8

Can I use TC Getter to prepare for coding interviews?

Accepted Answer

Yes. Paste your LeetCode or HackerRank solution into the editor and instantly see the Big-O complexity of every loop and function. This helps you verify whether your solution meets the expected time complexity before submitting.

Question 9

How is time complexity different from cyclomatic complexity?

Accepted Answer

Cyclomatic complexity counts independent execution paths through code (branches, conditions). Time complexity measures how runtime scales with input size. TC Getter focuses on time complexity (Big-O), which is what matters for algorithm efficiency.