at the source size is large and the probability distribution nearly uniform. Even if the Elias-delta codes are asymptotically optimal, Fibonacci codes of order two perform better with any source of size up to 106/2 (precisely, n = 514 228). 4 This fact illustrates that asymptotic code optimality is not the only criterion for selecting the most efficient code. Such a feature was also illustrated in the previous example. The comparative code performance also depends on the type of source distribution. Recalling that the Fibonacci code is parameterized by an integer m > 2, one must find an optimal value of m for each source distribution under consideration. Such an optimization is advantageous, but case-specific. This represents both an advantage and a drawback, in comparison with nonparameterized codes (such as Elias codes), which are fixed once and for all. The Golomb codes constitute a second important category of parameterized codes. For a Golomb code with parameter m, the codeword G(i) of integer i is made of two parts: (a) A prefix, which is made of 1 preceded by q zero bits, with q being the quotient = L(i - 1)/m], (b) A suffix, which is the binary representation in [log2 m bits of the remainder r = i - 1 - qm. The first rule (a) can also be changed with the definition q = Li/m] if, by convention, the list of integers i is made to start from zero. The second rule (b) represents a simplified version and is not the one actually used in Golomb codes. However, we shall use it as a first step for easily introducing the concept. To provide a practical example, assume m = 4. We have, for the first 12 integers: i = 1, prefix prefix prefix 001, etc., 4 D.A. Lelewer and D.S. Hirschberg, Data compression. Computing Surveys, 19 (1987), 261-97, see www.ics.uci.edu/~dan/pubs/DataCompression.html. Integer, arithmetic, and adaptive coding = 0, 1, 2, suffix = 00, 01, 10, 11, r = 0,1,2,3 suffix = 00, 01, 10, 11, r = 0, 1, 2, 3 suffix = 00, 01, 10, 11. We, thus, observe that the prefix increases by one bit at each multiple of m