How to write a functional anova for different datasets in R language?

I am trying to make a functional ANOVA in R language that applies to different datasets in different conditions, but I am not able to make the code functional and appropriate in these different situations. How can I make the variable handling flexible so that the operator can choose? Example:

input <- data.frame(
   order = gl(2,50, label = c(paste('area', LETTERS[1:2]))),
   f1 = gl(5,10, label = c(paste('conc', LETTERS[1:5]))),
   f2 = gl(5,2, label = c(paste('plot', LETTERS[1:5]))),
   f3 = factor(rep(paste("cond", 1:2, sep =""), 5)),
   values = abs(rnorm(100))

model <- by(input,input$order, function(x){
   f1 = levels(factor(x$f1))
   f2 = levels(factor(x$f2))
   f3 = levels(factor(x$f3))
   order = levels(factor(x$order))

     for( i in (1: length(f1))){
        for(j in (1: length(order))){

        di <- x[x$f1 == f1[i] & x$order == order[j] ,]

        write(paste('\nf1:', "f1", f1[i],order[j],'\n'), stderr())
        anova.1 <- aov(values ~ f2 * f3, di)

        write("Analyse Finished! \n", stderr())  

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