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Cover

Also called: covering, minimal cover, minimum cover, set cover, covering problem, prime implicant cover

A set of implicants that together are 1 on every 1 of the function. A minimal SOP is a cheapest cover made of prime implicants.

A set of product terms covers a function when every row where F = 1 is made 1 by at least one of the terms, and none of them is 1 on a row where F = 0. In other words, it is a correct SOP for F.

Finding a minimal SOP is a covering problem, solved in two stages:

  1. Find all the prime implicants. Only primes need to be considered, because any non-prime term can be swapped for a bigger prime that covers at least as much.
  2. Choose the cheapest set of primes that covers every 1.

For the second stage:

  • List, for each 1 of F, the primes that cover it.
  • A 1 covered by only one prime forces that prime into the cover. It is an essential prime implicant.
  • Remove the 1s already covered, then add the cheapest primes for whatever is left.

Primes that are left out are redundant. Sometimes there is a tie, and the function has more than one minimal SOP.

Overlap is fine: covering a 1 twice costs nothing. What costs is an extra term.

A\BC00011110
0
1m0
0m1
0m3
0m2
1
1m4
1m5
1m7
0m6

Worked example

Example

Choosing a cover

F(A, B, C) = Σm(0, 4, 5, 7) has prime implicants (rows 0, 4), (rows 4, 5) and (rows 5, 7). Choose a minimal cover.

  1. 1.

    Row 0 is covered only by , so it must be chosen.

  2. 2.

    Row 7 is covered only by , so it must be chosen.

  3. 3.

    Those two cover rows 0, 4, 5 and 7: everything.

  4. 4.

    is redundant. Minimal SOP: , the two groups on the map above.

Common mistakes

  • Including every prime implicant. Only enough to cover every 1 is needed.

  • Choosing the biggest primes first and missing an essential one, which leads to an extra term.

  • Treating don't-cares as rows that must be covered.

Practice Cover

Interactive questions with instant feedback and a worked solution for every wrong answer.

Learn it step by step

Cover is taught in Boolean Simplification and Karnaugh Maps.