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VERSION:2.0
CALSCALE:GREGORIAN
PRODID:UW-Madison-Physics-Events
BEGIN:VEVENT
SEQUENCE:0
UID:UW-Physics-Event-3292
DTSTART:20140408T170500Z
DURATION:PT1H0M0S
DTSTAMP:20260419T193832Z
LAST-MODIFIED:20140220T204541Z
LOCATION:4274 Chamberlin (refreshments will be served)
SUMMARY:Algorithms\, complex systems and chaos\, Chaos & Complex Syste
 ms Seminar\, Jerry Tutsch\, UW Department of Computer Sciences
DESCRIPTION:Computer programs consist of large collections of interact
 ing algorithms. They are prime examples of complex systems. The recent
  advent of cheap\, fast\, small computers has led to an explosion of v
 ery complex programs that must remain easy to use. To a large extent\,
  it is the ease-of-use constraint that is driving up the level of comp
 lexity. The programs generally have a direct-manipulation user interfa
 ce\, as opposed to a simple text-based interface. They are nonautonomo
 us\, that is event-driven.<br>
\n<br>
\nAdditional technical constrain
 ts drive up the complexity. The program's component parts may be distr
 ibuted over various computers and they may be executing at different t
 imes. Furthermore the programs may need to be able execute on differen
 t platforms which themselves change over time as operating systems and
  hardware is updated.  Even with the help of software development tool
 s\, an increasingly difficult task facing the software engineer is tha
 t of controlling and managing the complexity of a program over its lif
 etime as it inevitable grows in functionality and size.<br>
\n<br>
\nI
 n the parlance of  dynamical systems\, as perhaps best defined in Math
  and Physics\, computer programs in general are extremely complex nona
 utonomous t-advancing iterative maps defined on discrete phase spaces 
 of high dimension.<br>
\n<br>
\nOver the past several years\, as an ex
 periment to learn more about controlling and managing the complexity o
 f computer programs\, I have been writing a program designed to help s
 tudents visualize the complexity and chaos that emerges when small non
 linear dynamical systems\, in the form of differential equations and i
 terative maps\, evolve in time. In the course of writing the program\,
  I came to the realization that the program itself was a meta dynamica
 l system.<br>
\n<br>
\nI will discuss how a program's complexity is co
 ntrolled and managed in theory. Time permitting\, I will also demonstr
 ate how the complexity arises and is managed in practice.&lt\;br&gt\;<
 br><br>
\n
URL:https://www.physics.wisc.edu/events/?id=3292
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