What is memoization?
Q: What is memoization?
A: Memoization is a technique in computer programming that optimizes programs by storing the results of function calls in a table or associative array.
Q: How does memoization work?
A: Before a value is returned from a function call, it is stored in a lookup table. Later, the function will look up the value of the input in the lookup table instead of recalculating it, which is much less expensive.
Q: What are the benefits of memoization?
A: Memoization can improve program performance by reducing the number of calculations needed. It is also a simple optimization technique that can be applied to many programs.
Q: How does the lookup table work?
A: The lookup table stores the values returned by the function calls. Like a cache, it has a limit on how many results it can store, and it is periodically cleaned by removing values that have not been accessed in a while.
Q: What distinguishes memoization from other forms of caching?
A: Memoization is a specific case of caching that refers to storing the results of function calls. It is different from other forms of caching such as buffering or page replacement.
Q: Is memoization used in logic programming languages?
A: Yes, memoization is also known as tabling in some logic programming languages.
Q: What is the relationship between memoization and a lookup table?
A: Memoization involves using a lookup table to store the results of function calls. The function can look up values in the table instead of recalculating them.
