Covariance bug in R-1.8.0

R-1.8.0 seems to calculate wrong covariances, when the argument of cov()
is a matrix or a data frame.
The following should produce a matrix of zeroes and NaNs:

x <- matrix(c(NA ,NA ,0.9068995 ,NA ,-0.3116229,
              -0.06011117 ,0.7310134 ,NA ,1.738362 ,0.6276125,
              0.6615581 ,NA ,NA ,-2.646011 ,-2.126105,
              NA ,1.081825 ,NA ,1.253795 ,1.520708,
              0.2822814 ,NA ,NA ,NA ,NA,
              0.03291028 ,NA ,NA ,NA ,NA,
              NA ,NA ,NA ,-0.5462126 ,-0.1997394,
              NA ,-0.3419413 ,-0.2675226 ,-1.000133 ,-0.1346234,
              NA ,NA ,-0.411743 ,1.301612 ,NA,
              0.922197 ,NA ,0.9513522 ,0.2357021 ,NA),
            nrow=10, ncol=5)

c1 <- cov(x, use="pairwise.complete")

c2 <- matrix(nrow=5, ncol=5)
for (i in 1:5)
{
    for (j in 1:5)
    {
        c2[i,j] <- cov(x[,i], x[,j], use="pairwise.complete")
    }
}

c2-c1

Instead, R-1.8.0 produces this result:

            [,1]        [,2]       [,3]          [,4]        [,5]
[1,]  0.00000000 -0.03053828         NA -0.0144996353 -0.03485883
[2,] -0.03053828 -0.01649857         NA  0.0137259383 -0.02960707
[3,]          NA          NA -0.1296134            NA          NA
[4,] -0.01449964  0.01372594         NA -0.0003152629  0.08717648
[5,] -0.03485883 -0.02960707         NA  0.0871764791  0.04961190

This happens as well under Linux (Suse 9.1) as well as under Windows NT.

Under 1.9.1 (Linux) and 1.9.0 (Windows) i get the expected matrix of
zeroes and NaNs.

This example is not very special. Under R-1.8.0 cov produced wrong result
for any random matrix i tried.

Doesn't this mean, that *any* result obtained under R 1.8.0 is unreliable?

By the way, i just recompiled R-1.8.0 from source under Linux and tried
'make check'. All tests were ok.
Does there exist a more detailed set of tests, which could insure that
at least the most basic R functions work correctly?


Christian