Can anyone Briefly describe what the following piece of R code is doing/showing?

n.fake = 1000

x = seq (1,5); n = length (x)

cover.68 = rep(NA, n.fake)

cover.95 = rep(NA, n.fake)

a = 5; b = 1;

for (i in 1 : n.fake)

{

#Fit regression model

y= a + b*x + rnorm(n,0,0.9);

m= lm(y~x)

b.hat = coef (m) [2]

#Calculate CI

sse = sum((y-fitted.values(m))^2)

s_2 = sse/(length(x)-2)

sxx = sum(x^2-mean(x)^2)

bse = sqrt(s_2/sxx )

cover.68[i] = abs (b-b.hat)< qt(0.84, n-2)*bse

cover.95[i] = abs (b-b.hat)< qt(0.975, n-2)*bse

}

mean(cover.68)

mean(cover.95)