Time complexity indicates how the runtime of code changes as the input size varies, focusing on scalability rather than execution speed. Space complexity refers to the memory usage of code concerning input size. Both metrics are crucial for developers aiming to improve performance and efficiency in coding. The series intends to break down calculating these complexities from basic structures to more complex algorithms, targeting those new to data structures and algorithms, while also aiding in coding interview preparations.
Time complexity assesses the relationship between the input size and the runtime of the code, allowing developers to predict performance as the dataset scales.
Space complexity measures the amount of memory required by the code in relation to the input size, which is critical for optimizing resource usage.
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