# Why do we consider the order of growth when analyzing algorithms? [duplicate]

Seriously why do we consider how the computation time time increase with the number of inputs as a measure of performance when we can easily measure such as program execution time,power consumption,memory usage etc?Because all of these facts are depends on the hardware and programming language we use in that moment and order growth is only depends on inputs?

## marked as duplicate by David Richerby, Evil, Discrete lizard♦, Yuval Filmus algorithms StackExchange.ready(function() { if (StackExchange.options.isMobile) return; $('.dupe-hammer-message-hover:not(.hover-bound)').each(function() { var$hover = $(this).addClass('hover-bound'),$msg = $hover.siblings('.dupe-hammer-message');$hover.hover( function() { $hover.showInfoMessage('', { messageElement:$msg.clone().show(), transient: false, position: { my: 'bottom left', at: 'top center', offsetTop: -7 }, dismissable: false, relativeToBody: true }); }, function() { StackExchange.helpers.removeMessages(); } ); }); }); Jul 7 '18 at 21:04

• We can analyze the asymptotic running time of an algorithm without ever programming it. – Yuval Filmus Jul 7 '18 at 16:10
• There is two separate topic to be discussed here. 1) why asymptotic w.r.t. input size 2) why time. (as you see memory --- one of the thing OP suggested as alternative --- is also popularly measurable via asymptotic) – Apiwat Chantawibul Jul 7 '18 at 16:25
• In fact, basically an exact duplicate, but the above is an automatically generated comment. – David Richerby Jul 7 '18 at 17:59