Let be the support of the weight- codeword , and let delete all coordinates in . Its kernel consists of codewords supported in . If , then but , so is nonzero in every coordinate of . Over this forces . Hence
has dimension one, and the punctured code has length and rank by the rank-nullity theorem.
To bound its minimum distance, take whose puncture is nonzero. If has nonzero coordinates in , then has there, while both words have the same nonzero coordinates outside . Both and are nonzero codewords, so
Adding gives , and therefore
Iterate the puncturing inequality from part (ii) times and then use part (i):
This is the binary Singleton bound:
Form the punctured code by deleting one fixed coordinate from every codeword. Two distinct original words differ in at least positions, so after one deletion they still differ and cannot coalesce. The new code therefore retains size , while every pairwise Hamming distance falls by at most one. It is an code with , and hence also an code in the minimum-distance-at-least convention. Therefore
Fix a coordinate, say the last one. The punctured code is
Deleting one coordinate lowers each pairwise distance by at most one. Thus, when , no two words merge and
In guaranteed-distance notation this is recorded as an code. If , puncturing a coordinate on which a distance-one pair differs can merge words, so its exact size must then be stated separately.
Write for the all-one column vector. The parity-check extension of a linear code is
The defining map is linear, so is a binary linear code. If is a generator matrix and a parity-check matrix for , then one may take
The punctured code in, say, the last coordinate is
Coordinate deletion is a linear map, so is linear. Its generator matrix is obtained by deleting the last column of . If the minimum distance is at least two, deletion is injective on , and hence has the same dimension as .
For its parity-check matrix, first use invertible row operations on to make its nonzero last column a coordinate vector. The last column is nonzero because otherwise the weight-one word supported there would belong to , contrary to . Delete the pivot row and the last column; the resulting matrix is a parity-check matrix for . Equivalently, is obtained by shortening the dual code at the deleted coordinate.
Finally, the shortened code in the last coordinate is
It is linear whenever is linear, because it is the puncture of the subspace .