  Undetected errors are important for linear codes, which are the only type of
errors after hard decision and automatic-repeat-request (ARQ), but do not
receive much attention on their correction. In concatenated channel coding,
suboptimal source coding and joint source-channel coding, constrains among
successive codewords may be utilized to improve decoding performance. In this
paper, list decoding is used to correct the undetected errors. The benefit
proportion of the correction is obviously improved especially on Hamming codes
and Reed-Muller codes, which achieves about 40% in some cases. But this
improvement is significant only after the selection of final codewords from the
lists based on the constrains among the successive transmitted codewords. The
selection algorithm is investigated here to complete the list decoding program
in the application of Markov context model. The performance of the algorithm is
analysed and a lower bound of the correctly selected probability is derived to
determine the proper context length.
