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Given a list of binary strings and two integers m and n representing the maximum allowed zeros and ones respectively, which approach is most suitable to find the maximum number of strings that can be selected without exceeding these limits?

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Dynamic Programming: Knapsack - Ones and Zeroes (2D Knapsack)
Given a list of binary strings and two integers m and n representing the maximum allowed zeros and ones respectively, which approach is most suitable to find the maximum number of strings that can be selected without exceeding these limits?
AGreedy algorithm sorting strings by length
BDynamic programming using a 2D knapsack approach
CDepth-first search with backtracking only
DSorting strings by number of zeros and picking the first <code>m</code>
Step-by-Step Solution
Solution:
  1. Step 1: Identify problem constraints

    The problem limits the total zeros and ones used, which are two separate constraints.
  2. Step 2: Recognize problem type

    This is a variation of the 2D knapsack problem where each item (string) has two weights (zeros and ones).
  3. Step 3: Choose algorithmic pattern

    Dynamic programming with a 2D DP table indexed by zeros and ones counts is the optimal approach.
  4. Final Answer:

    Option B -> Option B
  5. Quick Check:

    Two constraints imply 2D knapsack DP [OK]
Quick Trick: Two constraints require 2D knapsack DP [OK]
Common Mistakes:
MISTAKES
  • Assuming greedy approach works for multiple constraints
  • Ignoring the two-dimensional nature of the problem
  • Using DFS without memoization leading to inefficiency
Trap Explanation:
PITFALL
  • Greedy or single constraint knapsack approaches ignore the dual constraints and fail.
Interviewer Note:
CONTEXT
  • Tests understanding of problem classification and appropriate algorithmic pattern.
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