Logging With log4j

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Logging With log4j

• http//logging.apache.org/log4j/

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Why Log?
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The Concept of Log Levels
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Who are the Players?

• Logger (what)
• Appender (where)
• Layout (how)

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Logger

• Logger is a named entity, each named logger is a
  singelton.
• Logger log Logger.getLogger(myLogger)

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Logger

• There is a hierarchy of loggers (determined by
  their names).
• The logger named "com.foo" is a parent of the
  logger named "com.foo.Bar".
• Similarly, "java" is a parent of "java.util" and
  an ancestor of "java.util.Vector".

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Logger

• At the top of the hierarchy is the root logger.
• Logger root Logger.getRootLogger()

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Logger

• When you have a logger, you can use it to log
  messages at various levels.
• logger.debug(a debug message)
• logger.info(an info message)
• logger.warn(a warning)
• logger.error(an error)
• logger.fatal(oh no.)

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Logger

• You can assign a level to a logger.
• logger.setLevel(Level.INFO)
• It will then ignore all messages of lower levels.

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Logger

• If there is no assigned level, the logger assumes
  the level of its parent.

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Logger

• Suggestion use the full class name as the logger
  name for that class
• Logger log Logger.getLogger(oosd.examples.logge
  r.LoggingApp)

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Appender

• The destination of the logger.
• You can write your own, but usually youll just
  use an existing one
• ConsoleAppender
• FileAppender
• SocketAppender

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Layout

• How will the message look like.
• Again, you can write your own, but usually use
  one of
• SimpleLayout
• PatternLayout
• HTMLLayout
• XMLLayout

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Example

• Logger log Logger.getLogger(my.logger)
• log.setLevel(Level.ERROR)
• log.addAppender(new ConsoleAppender(new
  SimpleLayout())
• log.warn(This will not be shown)
• log.fatal(This will)

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Hierarchy

• Level if there is no level assigned, look for
  level of parent.
• Appender append to all appenders assigned to
  current logger, as well to appenders of all
  ancestros.
• You can override this by setting
  logger.setAdditivity(false)

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Log Configuration

• BasicConfigurator
• BasicConfigurator.configure()
• BasicConfigurator.configure(Appender a)

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Log Configuration

• From file
• PropertyConfigurator.configure(String filename)
• DOMConfigurator.configure(String filename)
• This reads the configuration from a file (either
  Properties or XML). See documentation for the
  configuration files formats.

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Java Exceptions
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Java Exceptions

• Throws
• Try
• Catch
• Finally

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Java Exceptions - Throwable
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Java Exceptions

• Finally things we should do no matter what
  happened in the try block.

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Finally inner working of superman

• Try
• wearUniform()
• fly(whereTheBadGuyIs)
• catch (CantWearUniformInPublicException pe)
• //
• catch (CantFlyNearCryptonException ce)
• //
• finally
• // no matter what went wrong before, the
  world WILL be saved
• saveTheWorld()

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Finally the boring example

• try
• out new PrintWriter(new FileWriter(f.txt))
• //
• catch (FileNotFoundException fnf)
• //
• catch (IOException e)
• // ..
• finally
• if (out ! null) out.close()

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Creating your own exceptions

• Extend Exception and define the appropriate
  constructors.

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Any questions about exceptions?

• Good. So now we can continue to an

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Algorithm!
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MinMax Algorithm

• Choosing the best move in a game

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Perfect Decision, Two person games

• Can be represented as a game-tree.

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Perfect Decision, Two person games

• Two players
• MAX and MIN
• MAX moves first alternate turns thereafter.
• Formal definition of game
• Initial State how the game starts?
• Successor Function what are the possible
  moves?
• Terminal Test can we continue playing?
• Utility Function how good is the position for
  the given player?
• No one player has full control, must develop a
  strategy.

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Minimax Algorithm Basics
MAX
3
MIN
0
3
2
MAX
7
0
9
3
6
2
MIN
6
5
7
2
1
3
9
0
4
5
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Process of Backing up minimax decision Assumption
Both players are knowledgeable and play the
best possible move
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Minmax Algorithm

• Generate game tree to all terminal states.
• Apply utility function to each terminal state.
• Propagate utility of terminal states up one
  level.
• MAXs turn MAX tries to maximize utility value.
• MINs turn MIN minimizes utility value.
• Continue backing-up values toward root, one layer
  at a time.
• At root node, MAX chooses the value with highest
  utility.

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Problem

• Full games might be too large to generate
• Solution generate tree up to a fixed depth, use
  a heuristic function to calculate the utility of
  the non-terminal leafs.

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Example Partial Search for Tic-Tac-Toe
Position p win for Max, u(p) ? loss for MAX,
u(p) ? otherwise, u(p) ( of complete
rows, cols, diags still open for MAX) ( of
complete rows, cols, and diags still open for MIN)
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Tic-Tac-Toe Move 2
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MAX Player 3rd move
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