  A novel lossless source coding paradigm applies to problems of unreliable
lossless channels with low bit rates, in which a vital message needs to be
transmitted prior to termination of communications. This paradigm can be
applied to Alfred Renyi's secondhand account of an ancient siege in which a spy
was sent to scout the enemy but was captured. After escaping, the spy returned
to his base in no condition to speak and unable to write. His commander asked
him questions that he could answer by nodding or shaking his head, and the
fortress was defended with this information. Renyi told this story with
reference to prefix coding, but maximizing probability of survival in the siege
scenario is distinct from yet related to the traditional source coding
objective of minimizing expected codeword length. Rather than finding a code
minimizing expected codeword length $\sum_{i=1}^n p(i) l(i)$, the siege problem
involves maximizing $\sum_{i=1}^n p(i) \theta^{l(i)}$ for a known $\theta \in
(0,1)$. When there are no restrictions on codewords, this problem can be solve
using a known generalization of Huffman coding. The optimal solution has coding
bounds which are functions of Renyi entropy; in addition to known bounds, new
bounds are derived here. The alphabetically constrained version of this problem
has applications in search trees and diagnostic testing. A novel dynamic
programming algorithm -- based upon the oldest known algorithm for the
traditional alphabetic problem -- optimizes this problem in $O(n^3)$ time and
$O(n^2)$ space, whereas two novel approximation algorithms can find a
suboptimal solution faster: one in linear time, the other in $O(n \log n)$.
Coding bounds for the alphabetic version of this problem are also presented.
