Damm’s Algorithm
November 18, 2014
This is simple; here are the table and two functions:
(define damm '#(
#(0 3 1 7 5 9 8 6 4 2)
#(7 0 9 2 1 5 4 8 6 3)
#(4 2 0 6 8 7 1 3 5 9)
#(1 7 5 0 9 8 3 4 2 6)
#(6 1 2 3 0 4 5 9 7 8)
#(3 6 7 4 2 0 9 5 8 1)
#(5 8 6 9 7 2 0 1 3 4)
#(8 9 4 5 3 6 2 0 1 7)
#(9 4 3 8 6 1 7 2 0 9)
#(2 5 8 1 4 3 6 7 9 0)))
(define (check num)
(let loop ((d 0) (ds (digits num)))
(if (null? ds) (+ (* num 10) d)
(loop (vector-ref (vector-ref damm d) (car ds)) (cdr ds)))))
(define (valid? num)
(let loop ((d 0) (ds (digits num)))
(if (null? ds) (zero? d)
(loop (vector-ref (vector-ref damm d) (car ds)) (cdr ds)))))
And here are some examples:
> (check 572)
5724
> (valid? 5724)
#t
We used digits from the Standard Prelude. You can run the program at http://programmingpraxis.codepad.org/mIPEQIZX.
It is a mystery to my why the Luhn algorithm is so often used, whereas the Damm algorithm is so seldom used. The Damm algorithm finds all single-digit errors and all adjacent-digit transpositions; Luhn’s algorithm finds most, but not all. And Damm’s algorithm is arguably simpler, using table lookup instead of arithmetic. Perhaps Luhn is preferred because it was available first, and because it doesn’t require space to store the lookup table (though at only 100 half-bytes, the table size is probably about the same memory size as the program code).
Programming Praxis 
my @map = qw( 0317598642 7092154863 4206871359 1750983426 6123045978 3674209581 5869720134 8945362017 9438617209 2581436790 ); sub cs { my $cs=0; $cs = substr $map[$cs],$_,1 foreach split m{}, $_[0]; return "$_[0]$cs"; } sub valid { return cs(substr $_[0],0,-1) eq $_[0]; }Haskell: http://codepad.org/plvEcNXF
Having leading zeroes not affect the check digit makes things a bit simpler.
#!/usr/bin/env python3 TABLE = [[0, 3, 1, 7, 5, 9, 8, 6, 4, 2], [7, 0, 9, 2, 1, 5, 4, 8, 6, 3], [4, 2, 0, 6, 8, 7, 1, 3, 5, 9], [1, 7, 5, 0, 9, 8, 3, 4, 2, 6], [6, 1, 2, 3, 0, 4, 5, 9, 7, 8], [3, 6, 7, 4, 2, 0, 9, 5, 8, 1], [5, 8, 6, 9, 7, 2, 0, 1, 3, 4], [8, 9, 4, 5, 3, 6, 2, 0, 1, 7], [9, 4, 3, 8, 6, 1, 7, 2, 0, 9], [2, 5, 8, 1, 4, 3, 6, 7, 9, 0]] def digits(n): if n <= 0: return [0] else: q, r= divmod(n, 10) ds = [r] ds.extend(digits(q)) return ds def check(n): i = 0 for j in reversed(digits(n)): i = TABLE[i][j] return i def verify(c): 0 == check(c) if __name__ == "__main__": from random import randrange from sys import exit for _ in xrange(10000): n = randrange(int(1e42)) if not verify(10 * n + check(n)): exit("Failure! {0}".format(n)) print("All tests passed.")Didn’t read the directions carefully.
checkshould return10 * n + i, and the test at the end can be simplified toverify(check(n)). Sorry!On my laptop, using a dict of dicts for the table and processing the number as a string, is about twice as fast as using a list of lists and processing the number as digits (i.e., ints).
data = """0 3 1 7 5 9 8 6 4 2 7 0 9 2 1 5 4 8 6 3 4 2 0 6 8 7 1 3 5 9 1 7 5 0 9 8 3 4 2 6 6 1 2 3 0 4 5 9 7 8 3 6 7 4 2 0 9 5 8 1 5 8 6 9 7 2 0 1 3 4 8 9 4 5 3 6 2 0 1 7 9 4 3 8 6 1 7 2 0 9 2 5 8 1 4 3 6 7 9 0 """.splitlines() digits = '0123456789' table = dict(zip(digits, (dict(zip(digits, row.split())) for row in data))) def damm(n): check = '0' for d in str(n): check = table[check][d] return int(check) def add_check(n): return 10*n + damm(n) def validate(n): return not damm(n)I’ve been getting into Clojure lately:
(def damm [[0 3 1 7 5 9 8 6 4 2] [7 0 9 2 1 5 4 8 6 3] [4 2 0 6 8 7 1 3 5 9] [1 7 5 0 9 8 3 4 2 6] [6 1 2 3 0 4 5 9 7 8] [3 6 7 4 2 0 9 5 8 1] [5 8 6 9 7 2 0 1 3 4] [8 9 4 5 3 6 2 0 1 7] [9 4 3 8 6 1 7 2 0 9] [2 5 8 1 4 3 6 7 9 0]]) (defn digits [n] (map #(- (int %) (int \0)) (str n))) (defn checkdigit[n] (reduce #((damm %1) %2) 0 (digits n))) (defn check[n] (+ (* n 10) (checkdigit n))) (defn valid?[n] (= (checkdigit n) 0)) (check 572) (valid? 5724)Just to let you guys know, the lookup table you’re using is incorrect. The 8th row, 9th column should be a 5. https://en.wikipedia.org/wiki/Damm_algorithm