Card Packs
Reported by candidates from IBM's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
IBM's Card Packs question appeared in November 2024 assessments, and candidates report hitting it with minimal context. You're given some number of card packs, likely with constraints on how they're distributed or selected, and you need to compute an outcome. The problem statement isn't always crystal clear on the first read, so half the battle is parsing what they're actually asking. StealthCoder will grab the exact wording from your screen and pattern-match it in real time, so you're not stuck re-reading in a panic.
Pattern and pitfall
Without the full problem text, the pattern could range from simulation (if you're iterating through pack selections) to combinatorics or greedy logic (if you're optimizing distribution). Card Pack problems typically hinge on one insight: whether order matters, whether you're maximizing or minimizing, and whether there's a constraint that forces a specific approach. The trick is almost always in the constraint you almost missed. Many candidates overshoot with dynamic programming when a greedy pass or a single loop would work. Skim the problem for hard limits, then decide if you need state tracking. StealthCoder acts as your safety net if the exact approach isn't obvious in the first minute.
If this hits your live OA and you blank, StealthCoder solves it in seconds, invisible to the proctor.
You can drill Card Packs cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Built by an Amazon engineer who would have shipped this the night before his JPMorgan OA if he'd had it.
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IBM reuses patterns across OAs. Built by an Amazon engineer who would have shipped this the night before his JPMorgan OA if he'd had it. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Card Packs FAQ
Is this a greedy or DP problem?+
IBM's Card Packs problems rarely need DP. Check if you can solve it with a single pass or a greedy selection. If sorting helps, do that first. DP is usually overkill unless you're tracking multiple states across different pack combinations.
What's the hidden constraint I'm probably missing?+
Read the problem twice. The constraint is often buried in a sentence like 'each pack can be used only once' or 'total packs is limited to N'. Constraints define whether brute force works or you need optimization.
How do I parse this if the problem text is vague?+
Look at the input format and examples first, not the description. Examples show what's actually being asked. If there are no examples, ask the proctor to clarify, or code the simplest interpretation and iterate.
Should I worry about edge cases with empty or single packs?+
Yes. Test your logic with n=0, n=1, and a typical case. Card pack problems often have a clean answer for edge cases. If your code breaks there, you've misunderstood the problem.
Is this still asked at IBM in late 2024?+
Yes, it appeared in November 2024. IBM rotates problems but doesn't retire them quickly. If you see this title, the core pattern is fair game. Nail the basics and you're fine.