Speaker Jacinta Richardson, Perl Training Australia
Time 2008-01-29 11:30
Conference LCA2008


  • perl -d:DProf program.pl
  • great way to find areas of code that need improvement.


improve code before you write it

Big-O notation

  • Find out why program is so slow
  • How does program scale with increase data set
  • Data set size n
    • O(c) - Constant time regardless on n
    • O(log n) - logarithmic
    • O((log n)^c) - poly logarithmic
    • O(n) - linear
    • O(n log n) - almost linear
    • O(n^2)
    • O(n^3)
    • O(n!) - insane with large data sets
    • etc

cN + dN^2 -> O(N^2)
N^4 + N! -> O(N!)
2N -> O(N)
500N -> O(N)

Details only important when comparing algorithms with same order.

loop (items) {

loop (items) {
    do stuff
    loop (items) {
            do stuff
    do stuff

O(N + NN) => O(N^2)

Nested loops not always O(N^2).

Avoid reading input data (file) more then once.

Complicated data structures scary, but may save time.

  • Go and learn complicated data structures.
  • Alternative, right code so that it is modular, and can be changed later.

Memory plentiful, use more memory for faster results.

loop (items) {

Cache result of do_long_task

use Memoize;

Don’t use for functions with side effects. Will cache the result of the do_long_task function.

If you can leave loop early, do so.


system("grep $subject $file > $results");

Code is not organic, it doesn’t cry. Do not worry about deleting/rewriting old stuff.


Do the things I told you so we can relax.