Tabulation Bottom Up DP in DSA C - Cheat Sheet & Quick Revision

Recall & Review

beginner

What is Tabulation in Dynamic Programming?

Tabulation is a bottom-up approach in dynamic programming where we solve smaller subproblems first and store their results in a table (usually an array) to build up solutions to bigger problems.

beginner

How does Tabulation differ from Memoization?

Tabulation solves problems iteratively from the smallest subproblem up, filling a table. Memoization solves problems recursively and stores results to avoid repeated work.

beginner

In Tabulation, why do we start filling the table from the base cases?

Base cases are the simplest subproblems with known answers. Starting from them ensures that when solving bigger subproblems, the smaller required answers are already computed and available.

intermediate

What is the time complexity advantage of using Tabulation?

Tabulation avoids repeated calculations by storing results in a table, so each subproblem is solved once. This usually reduces exponential time to polynomial time.

beginner

Give an example problem where Tabulation Bottom Up DP is useful.

The Fibonacci sequence calculation is a classic example. Using tabulation, we fill an array from the first two Fibonacci numbers up to the desired number, avoiding repeated recursive calls.

What does Tabulation in DP primarily use to store intermediate results?

A A queue

B An array or table

C A stack

D A linked list

Tabulation uses an array or table to store results of subproblems for bottom-up computation.

Which approach solves subproblems recursively and stores results to avoid recomputation?

A Memoization

B Brute force

C Greedy

D Tabulation

Memoization is the top-down recursive approach that caches results.

In Tabulation, what is the first step to solve a problem?

A Call the recursive function

B Solve the biggest subproblem first

C Initialize the table with base case values

D Sort the input data

Tabulation starts by initializing base cases in the table.

What is a key benefit of Tabulation over naive recursion?

A Does not require base cases

B Uses less memory

C Runs slower

D Avoids repeated calculations

Tabulation avoids repeated calculations by storing subproblem results.

Which problem is commonly solved using Tabulation Bottom Up DP?

A Finding Fibonacci numbers

B Sorting an array

C Binary search

D Depth-first search

Fibonacci sequence calculation is a classic example for tabulation.

Explain how Tabulation Bottom Up DP works using the Fibonacci sequence as an example.

Think about how you can build Fibonacci numbers from the first two numbers upwards.

Describe the main differences between Tabulation and Memoization in dynamic programming.

Consider how each approach solves subproblems and stores answers.