CS 177 Recitation

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CS 177 Recitation

• Oct 5, 2007 Week 7

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Announcements

• Project 2, due 900 pm on October 17, 2007.
• Use Mozilla Firefox for the development and
  testing of project 2
• There will be consultation hours on Tuesday Oct
  9, 2007

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Debugging

• What?
• From Wikipedia
• Debugging is a methodical process of finding and
  reducing the number of bugs, or defects, in a
  computer program or a piece of electronic
  hardware thus making it behave as expected.

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• Why?
• Debugging is very useful to make it easier to
  identify errors in programs
• How?
• In FireFox, the Error Console is a way to debug
  JavaScript
• To access the Error Console go toTools - Error
  Console
• You can click on an error and go directly to the
  line that caused that error

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ExampleWhat is the problem?
var
rMath.rando() if (r0.5) document.write(" href'http//www.A.com'Visit A!") else
document.write("Visit
B!")
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Error Console
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Debugging

• The bigger the code is, the harder it is to catch
  errors
• Debugging can save you a lot of time!
• One trick as well is toTRACE variables using
  document.write(). This is a way to catch logical
  errors
• document.write(before_foo()variablename)foo
  ()document.write(after_foo()variablename)

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Final word to say here!

• Carefully writing your code and rigorously
  testing it is a good way to make sure your code
  is error-free!
• Test, test and test your pages!

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Algorithms

• The central concept underlying all computation
• An algorithm
• 1) Must be clear -- unambiguous, understandable,
  capable of being "executed
• 2) Must be correct -- must yield the correct
  result(s)
• 3) Must be complete -- no missing cases,
  information on what to do in every situation
• 4) Must end -- the algorithm must come to some
  conclusion

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Example Algorithm

• Finding the oldest person
• Line up all the people along one wall
• As long as there is more than one person in line,
  repeatedly
• have the people pair up (1st with 2nd, 3rd with
  4th, etc) if there is an odd number of people,
  the last person will be without a partner
• ask each pair of people to compare their
  birthdays
• request that the younger of the two leave the
  line
• When there is only one person left in line, that
  person is the oldest

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Example Algorithm (cont.)

• Is this algorithm complete?
• What if number of people is odd?
• The last person, which does not have a partner,
  stays in the line for the current round
• What if two people have the same birthday?
• Flip a coin to see who leaves and who stays
• Person on the left leaves
• Now algorithm complete and could be programmed

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Big-Oh Notation

• To represent an algorithms performance in
  relation to the size of the problem
• Computer Scientists use Big-Oh notation
• Executing an O(N) algorithm requires time
  proportional to the size of the problem
• Given an O(N) algorithm, doubling the problem
  size doubles the work
• Executing an O(log N) algorithm requires time
  proportional to the logarithm of the problem size
• Given an O(log N) algorithm, doubling the problem
  size adds how much more work?
• ANSWER adds a constant amount of work

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Big-Oh Notation (cont.)

• What is the Big-Oh Notation of the following
  algorithm?
• Loop(1N) Loop(1..N) print Hi
• Hint How many times is the command print Hi
  called?
• ANSWER Big-Oh(N2)

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Big-Oh Notation (cont.)

• Consider our earlier algorithm (to calculate the
  oldest person)
• What is the Big-Oh of that algorithm?
• O(log N)
• Why?
• Hint How many steps are involved? Consider a
  step to be every time that the younger people
  in the pair leaves the line.
• Consider how many steps are involved if there
  are 16 people? How about 32?

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Search Problem

• Problem Finding a certain item in a list
• Recall the following solutions discussed in
  class
• Sequential Search sequential search is an
  algorithm that involves examining each list item
  in sequential order until the desired item is
  found
• Binary Search binary search involves continually
  cutting the desired search list in half until the
  item is found

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Search Analysis

• Sequential Search
• What is the Big-Oh? Why?
• Worst case the item you are looking for is in
  the last spot in the list (or not in the list at
  all)
• have to inspect and compare every entry in the
  list
• the amount of work required is proportional to
  the list size ? sequential search is an O(N)
  algorithm

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Search Analysis (cont.)

• Binary Search
• What is the Big-Oh? Why?
• in the worst case, you will have to keep halving
  the list until it gets down to a single entry
• each time you inspect/compare an entry, you rule
  out roughly half the remaining entries
• the amount of work required is proportional to
  the logarithm of the list size ? binary search is
  an O(log N) algorithm

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Constants in running time

• Note that calculating the Big-Oh of a function
  ignores constants in the running time.
• Example
• IffuntionA time to execute NfunctionB time
  to execute 2N? Both functions are O(N)

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Interpreters

• The interpreter reads one high-level statement
  at a time, immediately translating and executing
  the statement before processing the next one
• JavaScript is an interpreted language

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Compilers
Translate the entire high-level language program
into its equivalent machine-language
instructions Examples C, C, Java
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Next week

• Chapter 11 Conditional Execution
• Project 2 is due!

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Questions?