Sign in
Skip to solution
hardDSA

What is backtracking?

277 views
01

Understand the problem

Explain backtracking.

backtracking
02

Attempt it yourself

Sketch your approach before reading the solution — that's what interviews test.

Nudge consolestandby

Stuck? Beam a request up — the console returns a conceptual nudge that guides your logic without spoiling the implementation.

03

Study the solution

Backtracking incrementally builds candidates and abandons ('backtracks' from) a partial solution as soon as it can't lead to a valid result. It explores the solution space as a tree — used for permutations, combinations, N-Queens, Sudoku, and subset-sum.

Solution ready — 2 min read

Classified // press E to declassify

04

Read the code

Generate all subsets
Run Playground
def subsets(nums):
    result, path = [], []
    def backtrack(start):
        result.append(path[:])           # record a copy
        for i in range(start, len(nums)):
            path.append(nums[i])         # choose
            backtrack(i + 1)             # explore
            path.pop()                   # un-choose
    backtrack(0)
    return result


# --- demo ---
print(subsets([1, 2, 3]))   # [[], [1], [1,2], [1,2,3], [1,3], [2], [2,3], [3]]
05

Join the discussion

Discussion (0)

Sign in to join the discussion.

No responses yet. Be the first to share what you think.

Transmission complete // awaiting log

KEEP THE
STREAK ALIVE.

Dossier 121 of 127 decoded in the Data Structures & Algorithms track. One more won't hurt.

Back to track