How do you approach Longest String Chain?

Sort words by length so predecessors are processed first.

What are common mistakes on Longest String Chain?

Iterating the dimensions in an order that reads a cell before it has been written. Getting the base case wrong. It carries the whole recurrence, and the error stays invisible until a large input. Rolling down to one dimension without reversing the inner loop, which lets a 0/1 item be taken twice.

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Longest String Chain

MediumAlgorithms

Description

You are given an array of words. Word A is a predecessor of word B if inserting exactly one letter into A (without reordering) yields B. A word chain is a sequence where each word is a predecessor of the next.

Return the length of the longest possible word chain.

Example 1

Input: words = ["a","b","ba","bca","bda","bdca"]

Output: 4

Explanation: "a" -> "ba" -> "bda" -> "bdca".

Constraints

- 1 <= words.length <= 1000 - 1 <= words[i].length <= 16 - words[i] consists of lowercase English letters

Longest String Chain: approach, complexity and pitfalls

A medium dynamic programming problem, graded against 7 test cases (5 of them hidden).

The pattern: Dynamic Programming

Overlapping subproblems solved once and reused - the pattern candidates fear most.

Reach for it when you see: "Number of ways", "minimum/maximum cost", or a recursion that recomputes the same state.

If you are stuck

Show the 2-step hint ladder

Sort words by length so predecessors are processed first.
For each word, delete one character at a time to look up its best predecessor chain.

The optimal approach

Show the approach: The approach

DP keyed by word. Sort by length. For each word, try removing each character to form a candidate predecessor; `dp[word] = max(dp[pred] + 1)`. Track the global maximum.

Time: O(n·L²). Space: O(n).

The full reference solution in every supported language stays in the editor above - reveal it there once you have had a real attempt.

What the tests check

Read off this problem's own test suite, so these are the cases a submission actually has to survive.

Single element. A one-element case is included. Two-pointer and window solutions frequently return the wrong thing when the two indices start out equal.
Duplicate values. Repeated values appear in the input, so any logic that assumes distinct elements - or that skips over equal neighbours - is exercised.

Common Dynamic Programming mistakes

These apply to the pattern as a whole, not just this problem.

Iterating the dimensions in an order that reads a cell before it has been written.
Getting the base case wrong. It carries the whole recurrence, and the error stays invisible until a large input.
Rolling down to one dimension without reversing the inner loop, which lets a 0/1 item be taken twice.