In this post I will show you an example of refactoring existing code to use the

*template and strategy design*pattern in

*Ruby*!

The application we are going to design today models a game where

*an oracle thinks of a number*in a certain range (0...Max) and

*each participant to this game makes a number of guess to find out what this number is*;

After each guess, the oracle tells the participant if he is correct or not!

The starting code for this application is composed only by two classes and a main:

- The participant class is the first class I am going to show you.
*A participant tries to guess the 'secret' number using several different strategies:*

`require_relative 'oracle.rb' # Tries to guess the 'secret' number using several different strategies class Participant attr_reader :num_attempts def initialize(oracle, max_num_attempts:10) @oracle, @max_num_attempts = oracle, max_num_attempts @num_attempts = 0 end def reset @num_attempts = 0 end def`

`play_randomly`

`(lower,upper) num = Kernel.rand(lower..upper) @num_attempts+=1 while @oracle.is_this_the_number?(num)!=:correct && (@num_attempts <= @max_num_attempts) do num = Kernel.rand(lower..upper) @num_attempts+=1 end if (@num_attempts <= @max_num_attempts) :success else fail end end def`

`play_linear`

`(lower) num=lower @num_attempts+=1 while @oracle.is_this_the_number?(num)!=:correct && (@num_attempts <= @max_num_attempts) do end num+=1 @num_attempts+=1 end if (@num_attempts <= @max_num_attempts) :success else fail end end def`

`play_smart_random`

`(lower, upper) num = Kernel.rand(lower..upper) @num_attempts+=1 while ((result = @oracle.is_this_the_number?(num)) != :correct) && (@num_attempts <= @max_num_attempts) do end if result == :less_than upper = num-1 elsif result == :greater_than lower = num+1 end num = Kernel.rand(lower..upper) @num_attempts+=1 end if (@num_attempts <= @max_num_attempts) :success else fail end end def`

`play_binary_search`

`(lower, upper) num = (lower+upper)/2 @num_attempts+=1 while ((result = @oracle.is_this_the_number?(num)) != :correct) && (@num_attempts <= @max_num_attempts) do end if result == :less_than upper = num-1 elsif result == :greater_than lower = num+1 end num=(lower+upper)/2 @num_attempts+=1 end if (@num_attempts <= @max_num_attempts) :success else fail end end private def fail :fail end end`

- The second class represent the Oracle, which generates the number the Participant is trying to guess:

```
class Oracle
attr_writer :secret_number
def initialize(secret_num:0)
@secret_number = secret_num end
def is_this_the_number? num if num == @secret_number
:correct elsif num > @secret_number
:less_than elsif num < @secret_number
:greater_than end end
end
```

As you can see the class Participant defines several methods to play this game highlighted in red.

**Each of them uses a different algorithm.**The main method, wants to make a comparison between this algorithm and measure their performances:

`# Evaluate the performance of participants using different guessing strategies require_relative 'oracle.rb' require_relative 'participant.rb' NUM_OF_RUNS = 8 oracle = Oracle.new # evaluate random strategy total_num_attempts = 0 total_num_failures = 0 homer = Participant.new(oracle, max_num_attempts: NUM_OF_RUNS*2) 1.upto(NUM_OF_RUNS) do |i| oracle.secret_number = i homer.reset if`

`homer.play_randomly`

`(1,NUM_OF_RUNS)==:success total_num_attempts += homer.num_attempts else total_num_failures += 1 end end puts "play randomly took on average #{total_num_attempts/(NUM_OF_RUNS-total_num_failures)} attempts to succeed" # evaluate linear strategy total_num_attempts = 0 total_num_failures = 0 bart = Participant.new(oracle, max_num_attempts:NUM_OF_RUNS*2) 1.upto(NUM_OF_RUNS) do |i| oracle.secret_number = i bart.reset if`

`bart.play_linear`

`(1)==:success total_num_attempts += bart.num_attempts else total_num_failures += 1 end end puts "play_linear took on average #{total_num_attempts/(NUM_OF_RUNS-total_num_failures)} attempts to succeed" total_num_attempts = 0 total_num_failures = 0 maggie = Participant.new(oracle, max_num_attempts:NUM_OF_RUNS*5) 1.upto(NUM_OF_RUNS) do |i| oracle.secret_number = i maggie.reset if`

`maggie.play_smart_random`

`(1,NUM_OF_RUNS)==:success total_num_attempts += maggie.num_attempts else total_num_failures += 1 end end puts "play_smart_random took on average #{total_num_attempts/(NUM_OF_RUNS-total_num_failures)} attempts to succeed" total_num_attempts = 0 total_num_failures = 0 lisa = Participant.new(oracle, max_num_attempts:NUM_OF_RUNS*5) 1.upto(NUM_OF_RUNS) do |i| oracle.secret_number = i lisa.reset if`

`lisa.play_binary_search`

`(1,NUM_OF_RUNS)==:success total_num_attempts += lisa.num_attempts else total_num_failures += 1 end end puts "play_binary_search took on average #{total_num_attempts/(NUM_OF_RUNS-total_num_failures)} attempts to succeed"`

If we run this application we will get results similar to these ones:

*play randomly took on average 4 attempts to succeed*

*play_linear took on average 4 attempts to succeed*

*play_smart_random took on average 1 attempts to succeed*

*play_binary_search took on average 4 attempts to succeed*

As we said before, the Participant class defines different strategy for playing this game. This is totally fine and it will work producing some results that may change execution by execution;

However, if we take a minute to reflect, we understand that

**the only aim of the class Participant, is to play this game!**The concept that a Participant can play using different strategies should be extrapolated from the class Participant itself.

The

**strategy pattern**(also known as the

**policy pattern**) is a software design pattern that enables an algorithm's behavior to be selected at runtime. The strategy pattern:

*defines a family of algorithms,*

*encapsulates each algorithm, and*

*makes the algorithms interchangeable within that family.*

Strategy lets the algorithm vary independently from clients that use it. Strategy is one of the patterns included in the influential book

*Design Patterns*by Gamma et al. that popularised the concept of using patterns in software design. In our specific case, we know that the class Participant know four different strategies to play this game, so

**we will extract each of this strategy in four different classes**.

But wait a second, we can do even better here. If you take even a closer look, you will see that

**every "play" method as a part in common**; This piece of code:

```
if (@num_attempts <= @max_num_attempts)
:success else fail
end end
```

*guess the number and discover the outcome*!

The

**template method pattern**is a behavioural design pattern that defines the program skeleton of an algorithm in a method, called template method, which defers some steps to subclasses.**It lets one redefine certain steps of an algorithm without changing the algorithm's structure.**
In our specific case, we are going to create a PlayStrategy class that will define

these two steps:

these two steps:

- The
step will be delegate to the subclasses;*playGame**The PlayStrategy doesn't know any strategy to play with, so it will defer the implementation of this step to concrete subclasses that know how to play.* **The outcome step will be implemented in this class**. All the subclasses can call this method because it contains common code.

The class playStrategy will look like this:

`class PlayStrategy def play(lower,upper,context) playGame(lower,upper,context) outcome(context) end def playGame(lower,upper,context)`

`raise`

`("This method should be implemented in the interface") end def outcome(context) if (context.num_attempts <= context.max_num_attempts) :success else :fail end end end`

As we can see the method play doesn't have a real implementation. It just raise

an exception if it is invoked on an object instance of this class. This is one of

the way to simulate abstract method in Ruby.

New concrete subclasses will all look like this one:

an exception if it is invoked on an object instance of this class. This is one of

the way to simulate abstract method in Ruby.

New concrete subclasses will all look like this one:

```
require_relative 'play_strategy'
class BinarySearchPlay < PlayStrategy
def playGame(lower, upper,context)
num = (lower+upper)/2
context.num_attempts+=1
while ((result = context.oracle.is_this_the_number?(num)) != :correct)
&& (context.num_attempts <= context.max_num_attempts) do
# puts "#{__method__}:I guessed #{num}"
if result == :less_than
upper = num-1
elsif result == :greater_than
lower = num+1
end
num=(lower+upper)/2
context.num_attempts+=1
end
end
end
```

They will define the specific algorithm they implement.

The participant class is much simpler now because we have extract the knowledge of the different play strategies:

```
require_relative 'oracle.rb'
class Participant
attr_accessor :num_attempts
attr_reader :playStrategy
attr_reader :oracle
attr_reader :max_num_attempts
def initialize(oracle,playStrategy, max_num_attempts:10)
@oracle, @max_num_attempts = oracle, max_num_attempts
@num_attempts = 0
@playStrategy = playStrategy
end
def play(lower,upper)
@playStrategy.play(lower,upper,self)
end
def reset
@num_attempts = 0
end
private
def fail
:fail
end
end
```

Participant doesn't know how to play, but the instance variable

**@playStrategy**will help it on this matter.
Finally the main:

`# Evaluate the performance of participants using different guessing strategies require_relative 'oracle.rb' require_relative 'participant.rb' require_relative 'binary_search_play' require_relative 'linear_play' require_relative 'play_strategy' require_relative 'smart_random_play' require_relative 'random_play' NUM_OF_RUNS = 8 oracle = Oracle.new # evaluate random strategy total_num_attempts = 0 total_num_failures = 0 homer = Participant.new(oracle,`

`RandomPlay.new,`

`max_num_attempts: NUM_OF_RUNS*2,) 1.upto(NUM_OF_RUNS) do |i| oracle.secret_number = i homer.reset if`

`homer.play`

`(1,NUM_OF_RUNS)==:success # puts "play randomly found #{i} in #{homer.num_attempts} attempts" total_num_attempts += homer.num_attempts else # puts "play randomly failed to find #{i} after #{homer.num_attempts} attempts" total_num_failures += 1 end end puts "play randomly took on average #{total_num_attempts/ (NUM_OF_RUNS-total_num_failures)} attempts to succeed" # evaluate linear strategy total_num_attempts = 0 total_num_failures = 0 bart = Participant.new(oracle,`

`LinearPlay.new,`

`max_num_attempts:NUM_OF_RUNS*2) 1.upto(NUM_OF_RUNS) do |i| oracle.secret_number = i bart.reset if`

`bart.play`

`(1,0)==:success # puts "play_linear found #{i} in #{bart.num_attempts} attempts" total_num_attempts += bart.num_attempts else # puts "play_linear failed to find #{i} after #{bart.num_attempts} attempts" total_num_failures += 1 end end puts "play_linear took on average #{total_num_attempts/ (NUM_OF_RUNS-total_num_failures)} attempts to succeed" # evaluate 'smart random' strategy total_num_attempts = 0 total_num_failures = 0 maggie = Participant.new(oracle,`

`SmartRandomPlay.new,`

`max_num_attempts:NUM_OF_RUNS*5) 1.upto(NUM_OF_RUNS) do |i| oracle.secret_number = i maggie.reset if`

`maggie.play`

`(1,NUM_OF_RUNS)==:success # puts "play_smart_random found #{i} in #{maggie.num_attempts} attempts" total_num_attempts += maggie.num_attempts else # puts "play_smart_random failed to find #{i} after #{maggie.num_attempts} attempts" total_num_failures += 1 end end puts "play_smart_random took on average #{total_num_attempts/ (NUM_OF_RUNS-total_num_failures)} attempts to succeed" # evaluate binary search strategy total_num_attempts = 0 total_num_failures = 0 lisa = Participant.new(oracle,`

`LinearPlay.new,`

`max_num_attempts:NUM_OF_RUNS*5) 1.upto(NUM_OF_RUNS) do |i| oracle.secret_number = i lisa.reset if`

`lisa.play`

`(1,NUM_OF_RUNS)==:success # puts "play_binary_search found #{i} in #{lisa.num_attempts} attempts" total_num_attempts += lisa.num_attempts else # puts "play_binary_search failed to find #{i} after #{lisa.num_attempts} attempts" total_num_failures += 1 end end puts "play_binary_search took on average #{total_num_attempts/ (NUM_OF_RUNS-total_num_failures)} attempts to succeed"`

The most important difference to notice, highlighted in red, is that when we create a Participant, we also

**pass the Strategy as parameter to the constructor.**In this way,

**we decoupled the PlayStrategy from the Participant class,**and we will have to call simply the "play" method on the Participant because the strategy as been "injected" by the Client in the Participant constructor.

This is a class diagram of the new application:

HAPPY CODING!!

Luca