Measure Your Changes | Speed Up Your Site[c] Web Site Optimization

Measurement is a key part of the optimization process. Use the simplest algorithms and data structures you can, and measure your code's performance to see whether you need to make any changes. Use timing commands or profilers to locate any bottlenecks. Optimize these hot spots one at a time, and measure any improvement. You can use the date object to time individual snippets:

 <script type="text/javascript">  function DoBench(x){     var startTime,endTime,gORl='local';     if(x==1){         startTime=new Date().getTime();         Bench1();         endTime=new Date().getTime();     }else{         gORl='global';         startTime=new Date().getTime();         Bench2();         endTime=new Date().getTime();     } alert('Elapsed time using '+gORl+' variable: '+((endTime-startTime)/1000)+' seconds.'); } ... </script>

This is useful when comparing one technique to another. But for larger projects, only a profiler will do. Mozilla.org includes the Venkman profiler in the Mozilla browser distribution to help optimize your JavaScript.

The Venkman JavaScript Profiler

For more information on the Venkman profiler, see the following web sites:

http://mozilla.org/performance/jsprofiler.html
http://www.hacksrus.com/~ginda/venkman/profiles/

The Pareto Principle

Economist Vilfredo Pareto found in 1897 that about 80 percent of Italy's wealth was owned by about 20 percent of the population. ^[8] This has become the 80/20 rule or the Pareto principle, which is often applied to a variety of disciplines. Although some say it should be adjusted to a 90/10 rule, this rule of thumb applies to everything from employee productivity and quality control to programming.

Barry Boehm found that 20 percent of a program consumes 80 percent of the execution time. ^[9] He also found that 20 percent of software modules are responsible for 80 percent of the errors. ^[10] Donald Knuth found that more than 50 percent of a program's run time is usually due to less than 4 percent of the code. ^[11] Clearly, a small portion of code accounts for the majority of program execution time. Concentrate your efforts on these hot areas.

^[8] Vilfredo Pareto, Cours d'conomie politique profess l'Universit de Lausanne , 2 vols. (Lausanne, Switzerland:F. Rouge, 1896-97).

^[9] Barry W. Boehm, "Improving Software Productivity," IEEE Computer 20, no. 9 (1987): 43-57.

^[10] Barry W. Boehm and Philip N. Papaccio, "Understanding and Controlling Software Costs," IEEE Transactions on Software Engineering 14, no. 10 (1988): 1462-1477.

^[11] Donald E. Knuth, "An Empirical Study of FORTRAN Programs," SoftwarePractice and Experience 1, no. 2 (1971): 105-133. Knuth analyzed programs found by sifting through wastebaskets and directories on the computer center's machines.