Longest Ideal Subsequence
A medium-tier problem at 47% community acceptance, tagged with Hash Table, String, Dynamic Programming. Reported in interviews at MakeMyTrip and 0 others.
Longest Ideal Subsequence shows up in assessments at companies like MakeMyTrip, and it's a string DP problem that looks straightforward until you realize the brute force approach tanks on length. You're asked to find the longest subsequence where consecutive characters in the subsequence differ by at most k in their ASCII values. The 47% acceptance rate tells you this isn't a gimme: most people either miss the constraint or build a solution that's too slow. If this problem hits your live OA and you blank on the optimization, StealthCoder surfaces a working solution in seconds, invisible to the proctor.
Companies that ask "Longest Ideal Subsequence"
Longest Ideal Subsequence is the kind of problem that decides whether you pass. StealthCoder reads the problem on screen and surfaces a working solution in under 2 seconds. Invisible to screen share. The proctor sees nothing. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know.
Get StealthCoderThe core trick is recognizing this as a DP problem where you track the longest subsequence ending at each character, but you can't afford to scan all previous characters for every position. The naive O(n*26) or worse approaches fail because the constraint linking characters by ASCII distance means you need to efficiently query which characters within distance k have been seen. Hash tables become essential here: store the best subsequence length ending at each character, and for every new character, check only the valid range of previous characters rather than the entire string. Most people either try a full 2D DP table (memory and time killer) or miss that you can compress the state space. The pattern appears in companies testing DP fundamentals with a constraint-based twist, and knowing when to combine hash table lookup with DP state compression separates passing from timing out.
Pattern tags
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Longest Ideal Subsequence recycles across companies for a reason. It's medium-tier, and most candidates blank under the timer. StealthCoder is the hedge: an AI overlay invisible during screen share. It reads the problem and surfaces a working solution in under 2 seconds. Made by a working FAANG engineer who treats the OA the way companies treat hiring: as a game with rules you should know. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Longest Ideal Subsequence interview FAQ
Is Longest Ideal Subsequence actually a MEDIUM difficulty problem?+
The acceptance rate of 47% suggests it plays harder than a typical MEDIUM. The conceptual leap from DP to optimized DP with hash table lookups trips most candidates. You need both the DP insight and the optimization move to solve it cleanly.
Do I need to precompute ASCII values or can I just use character codes?+
Character codes work directly. In Python, ord(c) gives you the ASCII value. The constraint is about the numeric difference between codes, so no special preprocessing needed. The optimization is about which previous characters to check, not how you compare them.
How does the k constraint actually limit which characters I can use?+
If your current character is 'c' and k is 2, you can only extend subsequences ending in characters with ASCII values in the range ord('c') - k to ord('c') + k. That's the filtering window. Hash table stores the best result for each character, so you query that range instead of rescanning the string.
What's the pitfall that tanks most submissions?+
Trying a 2D DP table where you track all characters at all positions, or rechecking all previous positions for every new character. Both are too slow. The hash table optimization is mandatory. People who don't see that hit time limits.
Will this pattern show up in other DP problems I see?+
Yes. The pattern of combining DP state compression with a hash table to avoid redundant lookups appears in edit distance variants and range-based DP problems. Once you nail this problem, that pattern becomes portable.
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