I stumbled across this and it got me thinking …

Update

I’ve updated the Textile formatter on the site and the code for this entry is now displaying correctly. The previous version was swalling the == operators in the code.

Lisp 1.5 Programmer’s Manual

I stumbled across this in Bill Clementson’s blog and remembered using the Lisp 1.5 Prgrammers manual from the college years. I have strong memories of pouring over that particular page in the manual and attempting to understand all the nuances.

If you’ve never read the Lisp 1.5 Programamers Manual, page 13 is the guts of a Lisp Interpreter, the “eval” and “apply” functions. It is written in Lisp, although the notation used is a bit funky. The entire interpreter (minus two utility functions) is presented on a single page of the book. Talk about a concise language definition!

In Ruby?

I had often thought about implementing a Lisp interpreter, but back in the “old days”, the thought of implementing garbage collection and the whole runtime thing was a bit daunting. This was in the day before C, so my implementation language would have been assembler … yech.

But as I was reviewing the page, I realized that with today’s modern languages, I could problably just convert the funky M-Expressions used on page 13 directly into code. So … why not?

The Code

Here is the complete Ruby source code for the Lisp interpreter from page 13 of the Lisp Programmers manual:

  # Kernel Extensions to support Lisp
  class Object
    def lisp_string
      to_s
    end
  end

  class NilClass
    def lisp_string
      "nil" 
    end
  end

  class Array
    # Convert an Array into an S-expression (i.e. linked list).
    # Subarrays are converted as well.
    def sexp
      result = nil
      reverse.each do |item|
        item = item.sexp if item.respond_to?(:sexp)
        result = cons(item, result)
      end
      result
    end
  end

  # The Basic Lisp Cons cell data structures.  Cons cells consist of a
  # head and a tail.
  class Cons
    attr_reader :head, :tail

    def initialize(head, tail)
      @head, @tail = head, tail
    end

    def ==(other)
      return false unless other.class == Cons
      return true if self.object_id == other.object_id
      return car(self) == car(other) && cdr(self) == cdr(other)
    end

    # Convert the lisp expression to a string.
    def lisp_string
      e = self
      result = "(" 
      while e
        if e.class != Cons
          result << ". " << e.lisp_string
          e = nil
        else
          result << car(e).lisp_string
          e = cdr(e)
          result << " " if e
        end
      end
      result << ")" 
      result
    end
  end

  # Lisp Primitive Functions.

  # It is an atom if it is not a cons cell.
  def atom?(a)
    a.class != Cons
  end

  # Get the head of a list.
  def car(e)
    e.head
  end

  # Get the tail of a list.
  def cdr(e)
    e.tail
  end

  # Construct a new list from a head and a tail.
  def cons(h,t)
    Cons.new(h,t)
  end

  # Here is the guts of the Lisp interpreter.  Apply and eval work
  # together to interpret the S-expression.  These definitions are taken
  # directly from page 13 of the Lisp 1.5 Programmer's Manual.

  def apply(fn, x, a)
    if atom?(fn)
      case fn
      when :car then caar(x)
      when :cdr then cdar(x)
      when :cons then cons(car(x), cadr(x))
      when :atom then atom?(car(x))
      when :eq then car(x) == cadr(x)
      else
        apply(eval(fn,a), x, a)
      end
    elsif car(fn) == :lambda
      eval(caddr(fn), pairlis(cadr(fn), x, a))
    elsif car(fn) == :label
      apply(caddr(fn), x, cons(cons(cadr(fn), caddr(fn)), a))
    end
  end

  def eval(e,a)
    if atom?(e)
      cdr(assoc(e,a))
    elsif atom?(car(e))
      if car(e) == :quote
        cadr(e)
      elsif car(e) == :cond
        evcon(cdr(e),a)
      else
        apply(car(e), evlis(cdr(e), a), a)
      end
    else
      apply(car(e), evlis(cdr(e), a), a)
    end
  end

  # And now some utility functions used by apply and eval.  These are
  # also given in the Lisp 1.5 Programmer's Manual.

  def evcon(c,a)
    if eval(caar(c), a)
      eval(cadar(c), a)
    else
      evcon(cdr(c), a)
    end
  end

  def evlis(m, a)
    if m.nil?
      nil
    else
      cons(eval(car(m),a), evlis(cdr(m), a))
    end
  end

  def assoc(a, e)
    if e.nil?
      fail "#{a.inspect} not bound" 
    elsif a == caar(e)
      car(e)
    else
      assoc(a, cdr(e))
    end
  end

  def pairlis(vars, vals, a)
    while vars && vals
      a = cons(cons(car(vars), car(vals)), a)
      vars = cdr(vars)
      vals = cdr(vals)
    end
    a
  end

  # Handy lisp utility functions built on car and cdr.

  def caar(e)
    car(car(e))
  end

  def cadr(e)
    car(cdr(e))
  end

  def caddr(e)
    car(cdr(cdr(e)))
  end

  def cdar(e)
    cdr(car(e))
  end

  def cadar(e)
    car(cdr(car(e)))
  end

An Example

And to prove it, here’s an example program using Lisp. I didn’t bother to write a Lisp parser, so I need to express the lists in standard Ruby Array notation (which is converted to a linked list via the “sexp” method).

Here’s the ruby program using the lisp interpreter. The Lisp system is very primitive. The only way to define the function needed is to put them in the environment structure, which is simply an association list of keys and values.

  require 'lisp'

  # Create an environment where the reverse, rev_shift and null
  # functions are bound to an appropriate identifier.

  env = [
    cons(:rev_shift,
      [:lambda, [:list, :result],
        [:cond,
          [[:null, :list], :result],
          [:t, [:rev_shift, [:cdr, :list],
              [:cons, [:car, :list], :result]]]]].sexp),
    cons(:reverse,
      [:lambda, [:list], [:rev_shift, :list, nil]].sexp),
    cons(:null, [:lambda, [:e], [:eq, :e, nil]].sexp),
    cons(:t, true), 
    cons(nil, nil)
  ].sexp

  # Evaluate an S-Expression and print the result

  exp = [:reverse, [:quote, [:a, :b, :c, :d, :e]]].sexp

  puts "EVAL: #{exp.lisp_string}" 
  puts "  =>  #{eval(exp,env).lisp_string}" 

The program will print:

$ ruby reverse.rb
EVAL: (reverse (quote (a b c d e)))
  =>  (e d c b a)

All I need to do is write a Lisp parser and a REPL, and I’m in business!

The Example in Standard Lisp Notation

If you found the Ruby-ized Lisp code hard to read, here is the reverse funtions written in a more Lisp-like manner.

(defun reverse (list)
  (rev-shift list nil))

(defun rev-shift (list result)
  (cond ((null list) result)
        (t (rev-shift (cdr list) (cons (car list) result))) ))

Paul Graham issues the Arc Challenge … who could resist?

Paul Graham’s Arc Challenge

You can read about the Arc Challenge here: The Arc Challenge. Go ahead a read it now, but I will summarize the challenge.

Write a web program such that:

• The first page of the program displays nothing but a text box and a submit button. You enter some arbitrary text and press the submit button, which takes you to …

• The second page is nothing but a single link labeled “click here”. The URL linked to must not contain the text entered in the first step (i.e. you are not supposed to pass the text as a parameter on the link). Clicking the link takes you to …

• The third page which contains “You said: XXX” (where XXX is the text you entered in the first step).

Here’s a screen cast demoing my solution to the Arc Challenge. (We will show the code shortly).

Paul’s Solution

Paul has been working on designing Arc, his ideal programming language for the future. Given Paul’s language preferences, it is no surprise that Arc is very Lisp-like. Here is Paul’s solution written in Arc:

  (defop said req
    (aform [w/link (pr "you said: " (arg _ "foo"))
             (pr "click here")]
      (input "foo") 
      (submit)))

Paul points out that the solution is very short and elegant, only 23 nodes in the codetree. I’m sure I don’t quite understand exactly what it is doing (I’d love to see a step by step explanation of the code). He wonders what it would look like in other languages.

Several people have responded with solutions in their own languages. I’ve seen a Smalltalk Solution as well as a Ruby solution (which pretty closely mimics the Arc code from Paul) on the Arc Language Forum page that was setup for responses.

Continuation Web Servers

The Arc challenge is a perfect candidate for a continuation based server solution. And I recalled that Chad Fowler and I had written a demo continuation based server for the Continuations Demystified talk we did at RubyConf 2005. (Look for the “Poor Man’s Seaside Demo in that presentation.) I wondered how easy it be to code up an Arc challenge solution using that code base.

The key to a continuation based server is that it allows the programmer to code in a linear fashion. All the request/response nature of web interaction is completely hidden from you as a programmer.

For example, let’s pretend we wanted to solve the Arc challenge using a terminal and command line rather than a web based solution. How would you write it? Probably something like this:

  text = gets
  puts "click here" 
  gets
  puts "You said: #{text}" 

Simple, linear programming. (OK, printing “click here” is silly in a text program, but you get the idea). You ask a question and read a response. You pause for a click. You then tell the user what the result is.

Ask. Pause. Tell.

Those are our basic abstract operations for this problem. Lets rewrite our text based solution using these abstractions. We’ll put this in a file called “arc_challenge.rb”.

  Conversation.interact do |io|
    text = io.ask
    io.pause("click here")
    io.tell("You said: #{text}")
  end

I’ve introduced three operations (methods) that are provided by an I/O object (let’s ignore the interact line for now). “ask” will ask the user for input, returning the string. “pause” will pause until the user indicates he/she is ready to continue (e.g. pressing return in our command line version). “tell” sends the given string to the user.

So, what does “Conversation.interact” do? It creates the environment where the user have a conversation with the program. The interation is controlled through our ask/pause/tell functions provided by the I/O object passed to the interact block.

Here is an implementation of a text based conversation.

class TextBased
  def interact
    yield(self)
  end

  def ask(prompt=nil)
    print prompt, "  " if prompt
    gets.chomp
  end

  def pause(prompt="")
    print prompt, "  " if prompt
    gets
  end

  def tell(message)
    puts message
  end
end

Conversation = TextBased.new

To run the text based conversation, just require the text. Here’s a demo:

Arc on the Web

Well, anybody can solve the challenge in text mode. How much work do we have to do to get it on the web.

The answer: Zero!

The code Chad and I wrote for Continuations Demystified includes a web-based version of the conversation object that is ready to go. All we have to do is plug it in and run it. No changes are required to our basic Arc challenge solution.

Again, a screen demo:

Yes, we know that although we now have our Arc Challenge on the web, we haven’t quite conformed to the exact requirements of the challenge. We will handle that next.

The Final Arc Solution

The problem is that the current Web based conversation object makes all kinds of assumptions that are not appropriate for the final Arc solution.

In particular, we need to change:

• Get rid the head line, restart link and other extraneous HTML elements.

• Don’t keep a running log of the conversation. When you move to a new page, you start from scratch.

• The “click here” should be a real link, not just a text box where you can press enter.

To get to here, we will have to make some modifications to the conversation web library. It turns out the changes are pretty straight forward. The whole interaction framework is controlled by the Conversation object that implements ask/pause/tell methods. You can see the changes made for the Arc challenge in the “noecho_web_based.rb” file (see the end of this post for the availability of the source code).

The Final Conversation Based Solution

In cased you missed it, here is the Arc Challenge Solution:

  Conversation.interact do |io|
    text = io.ask
    io.pause("click here")
    io.tell("You said: #{text}")
  end

Yep, it’s the exact same file we used for the text based solution. I don’t know if it is as elegant as Paul’s version, but I certainly find it easy to read and understand. (Rerun the very first screen cast in this posting if you want to see it in action again).

If you want to look at the code, there is a tarball available that contains all the continuation server demo code from Continuations Demystified talk, as well as the two new files I added for the Arc challenge. “arc_challenge.rb” is the actually solution and “noecho_web_based.rb” is the conversation library that renders the solution in the style set forth by the challenge.

Enjoy.

Some fun with Erlang and FlexMock.

Erlang Function Definitions

Erlang defines functions by listing a set of possible argument lists and the body of the function to be executed for each argument list. For example, the factorial function might be defined in Erlang as:

    factorial(0) ->    1;
    factorial(N) ->    N * fac(N-1).

If factorial is called with a 0 (zero) for an argument, the first argument list will be chosen and the value of the factorial function will be 1. Otherwise, the value returned will be calculated by a recursive call to factorial.

FlexMock and Erlang

While playing around with FlexMock the other day, I realized that it does parameter matching, much like Erlang, when deciding what mock method to call. So I started wondering if you could write Erlang-like function definitions in FlexMock.

Here’s the result.

    mock = flexmock('fact')
    mock.should_receive(:factorial).with(0).and_return(1)
    mock.should_receive(:factorial).with(Integer).
      and_return { |n| n * mock.factorial(n-1) }

Ok, that was fun. But let’s not start building entire systems using nothing but FlexMock.

New Release of FlexMock

FlexMock 0.6.4 Release

Just wanted to drop a quick note that a new version of FlexMock is now available.

There are two nice enhancements and a minor bug fix in this version.

The second enhancement is in regard to the What Should flexmock(real_obj) Return? question I blogged about last May. I asked the question: What should flexmock(real_obj) return, the real object or the mock object? Someone had suggested returning the real object when flexmock() is given a block. There was some positive response to that, so that was included in the FlexMock release.

But after several months of using it, I found it difficult to remember which version of flexmock() returned what. At one point I found myself caling flexmock() with an empty block, just to get the real object back. That was madness.

So starting with release 0.6.4, flexmock will always return the real object. This is the best of both worlds, but it comes with a small price. Real objects partially mocked by FlexMode will now be enhanced with some extra methods, just enough methods so that addition mock behavior can be added to it. For example, should_receive is added to the partially mocked real object. This pollutes the method namespace for an object, but the result is much simplier for the programmer to use. If you really want to avoid method namespace pollution, there is a :safe mode offered. Read the docs for all the gory details.

By The Way, If You Grabbed Version 0.6.3 …

If you are one of the handful of people that downloaded verion 0.6.3 yesterday, then go ahead and grab 0.6.4. The only difference is in the API for mocking ActiveRecord models. After using it for a bit, I realized that the API could be improved, hence version 0.6.4. Sorry about that.

This is a fun example of using FlexMock

Andrew Sweeney Asks:

Andrew Sweeney emailed me with the following question:

I am currently working on a ruby project in which I think flexmock would be a good fit for unit testing. I have read the documentation and gone over the examples however fail to wrap my head around how to apply flexmock to my own app. I was hoping that you could give me some guidence and get me started or point me in the right direction.

You can find his original source code here.

I thought his problem was interesting enough to write it up as an example of using FlexMock. Andrew and his mentor, Bil Kleb gave permission for me to reproduce the code in my blog. The F3DQueue class is part of a Computational Fluid Dynamics project (http://fun3d.larc.nasa.gov) at NASA.

Quick Code Review

The F3DQueue class is small, so there’s not a lot of code we need to wade through. We see it uses a second class named AutoF3D, but the only clues we have to what AutoF3D might do are the four method calls on the “job” object in the run method.

It looks like the main interface to the queue object is the add_to_queue method. There is a thread started that pulls jobs (i.e. AutoF3D objects) from the queue and processes them in turn. There is some server delays built into the system. I presume that Computational Fluid Dynamics is, ummm, computationally complex and the delays are just there to make sure the workload does eat up all the CPU time on the server.

Starting Testing

When writing new code, I always like to approach it in a Test-First manner. Because I won’t write solution code without a test that forces me to write it, I have a high confidence that the code is well covered with tests.

Unfortunately, dealing with legacy code means that the code is already written and the test-first approach won’t work. That’s ok, I have a little trick that I use. Just comment out the bodies of all the methods in the class you are about to test. Then write the tests that force you to uncomment the code. Just uncomment only enought to get the tests to pass, don’t uncomment anything you don’t have to. You have enough tests when all the code has been uncommented. The technique is almost as good as doing real test-first.

The Commented Out Version

Here is the code base as I started the test.

An Existence Test

I almost always start out with an existence test. Existence tests basically prove the proper files are included and the object can be created. Normally I delete these after a few tests have been written. But I left this one in for an example.

   def test_initial_conditions
    q = F3DQueue.new
    assert_not_nil q
  end

Nothing really exciting here. Let’s move on …

Proving FIFO Queue Order

The first thing I want to prove is that items put into the queue are removed in FIFO order. Since add_to_queue creates a AutoF3D object, I mock out the new method on the class object and tell FlexMock to expect new to be called twice. Once with :a, :b, and :c as parameters, then again with :x, :y, :z paramters. Each invocation of new will return a different symbol (:first and :second) so we can easily test the items are pulled off the queue in FIFO order.

Notice that I pass in simple symbols for the arguments to add_to_queue. Our code doesn’t interpret the values of the arguments, they are merely passed directly to the AutoF3D constructor. All we do is verify that the AutoF3D (mocked) constructor does indeed receive the arguments we pass in.

Here’s the test:

  def test_adding_to_queue_is_removed_in_fifo_order
    flexmock(AutoF3D).should_receive(:new).once.with(:a, :b, :c).and_return(:first).ordered
    flexmock(AutoF3D).should_receive(:new).once.with(:x, :y, :z).and_return(:second).ordered
    q = F3DQueue.new

    q.add_to_queue(:a, :b, :c)
    q.add_to_queue(:x, :y, :z)

    assert_equal :first, q.remove_from_queue
    assert_equal :second, q.remove_from_queue
  end

This test caused three changes. First, the add_to_queue method needed lines uncommented:

  def add_to_queue(modelLoc, params, gridFile)
     autoF3D = AutoF3D.new(modelLoc, params, gridFile)
     @queue.push autoF3D
#     $log.info 'Request added to queue'
  end

(Notice I didn’t uncomment the log. The logger is not needed to pass the test, and doesn’t contribute to the actual functionality of the method. I will not be testing the logger in the for the purposes of this article.)

Also the remove_from_queue needed its body uncommented:

  def remove_from_queue
    @queue.pop
  end

And finally, the initializer code needed to create the queue array:

  def initialize  
     @queue = []
#     Thread.new{ process }
  end

Notice that the Thread.new line is left commented. We will deal with that in a bit.

So now we run the test:

$ ruby test_f3dqueue.rb
Started
F.
Finished in 0.010184 seconds.

  1) Failure:
test_adding_to_queue_is_removed_in_fifo_order(TestF3DQueue) [test_f3dqueue.rb:23]:
<:first> expected but was
<:second>.

2 tests, 2 assertions, 1 failures, 0 errors

Oops! This test uncovered the first bug. The code as written has stack behavior (i.e. LIFO). The naming seems to indicate that we want FIFO.

No problem. That’s an easy fix.

  def remove_from_queue
    @queue.shift
  end

Now the tests run clean:

$ ruby test_f3dqueue.rb
Started
..
Finished in 0.001925 seconds.

2 tests, 3 assertions, 0 failures, 0 errors

Proving that Running a Job Works

Now when I run a job, I need to show that the proper four methods are called once each and in the proper order. This is very straight forward using FlexMock.

  def test_running_a_job_will_call_the_right_stuff_in_the_right_order
    job = flexmock("job")
    job.should_receive(:generate_geometry_and_grid).once.ordered
    job.should_receive(:partition_grid_and_initialize_flow).once.ordered
    job.should_receive(:run_flow_solver).once.ordered
    job.should_receive(:post_process_solution).once.ordered
    q = F3DQueue.new

    q.run(job)
  end

Uncommenting the body of run is all that is needed here:

  def run( job )
#     $log.info 'Request being processed'
     job.generate_geometry_and_grid
#     $log.info 'Created Geometry'
     job.partition_grid_and_initialize_flow
#     $log.info 'Partitioned Grid'
     job.run_flow_solver
#     $log.info 'Flow Solver Completed'
     job.post_process_solution
#     $log.info 'Post process Completed'
#     $log.info 'Request completed'
  end

Test are now showing:

3 tests, 3 assertions, 0 failures, 0 errors

Processing an Empty Queue

Ok, now it gets interesting. I want to show that attempting to process a job when the queue is empty will cause the process to sleep for the check queue interval.

This is one spot where I changed the code to make it easier to test. It is difficult to test endless loops in unit tests (it tends to make the tests run a bit long), so I broke out the logic for a single pass through the loop into a method called process_one_job. We can then test this logic without dealing with the looping at the same time.

Note: It is possible to test endless loops and an example will be given below. But it is slightly tricky and this allows us to concentrate on proving the logic.

If there are no jobs to be processed, then all the code should do is sleep for a particular amount of time. We will locally mock out the sleep method on the queue object and insist that it will be called exactly once with the expected interval.

  def test_processing_with_no_jobs_will_sleep_the_check_interval
    q = F3DQueue.new
    flexmock(q).should_receive(:sleep).once.with(F3DQueue::CHECK_QUEUE_INTERVAL)

    q.process_one_job
  end

Here is process_one_job with just two lines uncommented so that the test will pass.

  def process_one_job
#       execution_attempts = 0
    job = remove_from_queue
#       begin
#         if job
#       run job
#           execution_attempts = 0
#           sleep SERVER_RECOVERY_TIME
#         else
    sleep CHECK_QUEUE_INTERVAL
#         end
#       rescue
#         $log.warn 'An error occurred during execution'
#         $log.warn $ERROR_INFO
#         $log.debug $ERROR_POSITION
#         sleep SERVER_RECOVERY_TIME
#         if execution_attempts > MAX_EXECUTION_ATTEMPTS
#           $log.error 'Too many failed execution_attempts: aborting'
#           raise
#         else
#           execution_attempts += 1
#           retry
#         end
#       end
   end

There’s a lot of code still left commented in that method. Now we need a test to force us to uncomment more code.

Handling a Single Job

Ok, now what happens when a single job is in the queue. We will assume the happy path (i.e. no exceptions) so we expect run to be called with the queued object, and then a sleep with the recovery interval.

A couple of things to note. First, we mock out AutoF3D again so that when we request something added to the queue, we control what kind of object is returned. We could return a mock object and then mock out the four methods that run will be calling.

However, I chose a slightly different approach. AutoF3D is mocked so that it returns a simple symbol. Then I mock out the run method to do nothing (but it is expected to be called once). This is slightly controversial because I am actually mocking a method on the object under test. But the run method is fairly simple, and we know that run works because of our previous test, so in the end we get clearer and simpler code.

Also note that the run and sleep methods mocks are ordered. This means run will be called first, then sleep.

  def test_processing_with_a_single_job_will_run_the_job_and_pause_for_recovery
    q = F3DQueue.new
    flexmock(AutoF3D).should_receive(:new).once.and_return(:job)
    flexmock(q).should_receive(:run).once.with(:job).ordered
    flexmock(q).should_receive(:sleep).once.with(F3DQueue::SERVER_RECOVERY_TIME).ordered
    q.add_to_queue(:a, :b, :c)

    q.process_one_job
  end

Now we get to uncomment even more lines in process_one_job.

  def process_one_job
#       execution_attempts = 0
    job = remove_from_queue
#       begin
    if job
      run job
#           execution_attempts = 0
      sleep SERVER_RECOVERY_TIME
    else
      sleep CHECK_QUEUE_INTERVAL
    end
#       rescue
#         $log.warn 'An error occurred during execution'
#         $log.warn $ERROR_INFO
#         $log.debug $ERROR_POSITION
#         sleep SERVER_RECOVERY_TIME
#         if execution_attempts > MAX_EXECUTION_ATTEMPTS
#           $log.error 'Too many failed execution_attempts: aborting'
#           raise
#         else
#           execution_attempts += 1
#           retry
#         end
#       end
   end

That just leaves the error handling code to be uncommented. So that will be next.

Handling a Job With Errors

Now we want to test the case where processing a job will return an exception. This test exercise the exception recovery code in the original code base. The technique is similar to the last test, but this time we specify two mock calls for run. The first time run will return an exception. The second time it is called, it will complete normally.

Notice that we have ordered run and sleep so that they interleave execution with each other.

  def test_if_a_job_fails_retry_after_recovery_time
    q = F3DQueue.new
    flexmock(AutoF3D).should_receive(:new).once.and_return(:job)
    flexmock(q).should_receive(:run).once.with(:job).and_raise(RuntimeError).ordered
    flexmock(q).should_receive(:sleep).once.with(F3DQueue::SERVER_RECOVERY_TIME).ordered
    flexmock(q).should_receive(:run).once.with(:job).ordered
    flexmock(q).should_receive(:sleep).once.with(F3DQueue::SERVER_RECOVERY_TIME).ordered
    q.add_to_queue(:a, :b, :c)

    q.process_one_job
  end

I was showing this test code to one of my coworkers and they were a little surprised that the second expectation on run didn’t override the first expectation. FlexMock is explicitly designed to allow you to stack expectations like this. When searching for an expectation during mocking, FlexMock will use the first one matching one if finds. When an expectation has been used its designated number of times (in the above test, the once method designates that the expectation should only be used once), FlexMock will begin to use matching expectations that are defined later.

The upshot is this is that it is easy to define mock behavior for multiple calls to the same method.

Here’s the latest process_one_job method with some more lines uncommented. We are getting close to the end with this one.

  def process_one_job
#       execution_attempts = 0
    job = remove_from_queue
    begin
      if job
        run job
#           execution_attempts = 0
        sleep SERVER_RECOVERY_TIME
      else
        sleep CHECK_QUEUE_INTERVAL
      end
    rescue
#         $log.warn 'An error occurred during execution'
#         $log.warn $ERROR_INFO
#         $log.debug $ERROR_POSITION
      sleep SERVER_RECOVERY_TIME
#         if execution_attempts > MAX_EXECUTION_ATTEMPTS
#           $log.error 'Too many failed execution_attempts: aborting'
#           raise
#         else
#           execution_attempts += 1
      retry
#         end
    end
  end

Processing Jobs that Continually Fail

Finally we test the case where the job will continually raise an exception until the error recovery code gives up and passes the exception on to the caller. I didn’t bother ordering the run/sleep calls here, making it easy to just specify that each are called four times. I believe that the previous test adequately specified interleaving.

I used a RuntimeError for my testing. If you have a specific error in mind, you might want to test explicitly for it. Generally raising the most general error you intend to handle is a good way of testing the boundry conditions on your rescue clause.

  def test_too_many_failures_will_pass_along_exception
    q = F3DQueue.new
    flexmock(AutoF3D).should_receive(:new).once.and_return(:job)
    flexmock(q).should_receive(:run).with(:job).and_raise(RuntimeError.new("XYZZY")).times(4)
    flexmock(q).should_receive(:sleep).with(F3DQueue::SERVER_RECOVERY_TIME).times(4)
    q.add_to_queue(:a, :b, :c)

    ex = assert_raise RuntimeError do
      q.process_one_job
    end
    assert_equal "XYZZY", ex.message
  end

Note that the exception needs to be raised four times. I suspect this is a bug in the error handling logic. I left the logic as is and just made sure the test will pass. The code base specifies a retry count of “2”. This seems to imply that we try run twice, or perhaps three times (if the initail attempt doesn’t count as a retry). In any case, four times seems too much.

So, here is the code for process_one_job with most of its lines uncommented.

  def process_one_job
    execution_attempts = 0
    job = remove_from_queue
    begin
      if job
        run job
#           execution_attempts = 0
        sleep SERVER_RECOVERY_TIME
      else
        sleep CHECK_QUEUE_INTERVAL
      end
    rescue
#         $log.warn 'An error occurred during execution'
#         $log.warn $ERROR_INFO
#         $log.debug $ERROR_POSITION
      sleep SERVER_RECOVERY_TIME
      if execution_attempts > MAX_EXECUTION_ATTEMPTS
#           $log.error 'Too many failed execution_attempts: aborting'
        raise
      else
        execution_attempts += 1
        retry
      end
    end
  end

Again note that this test surfaced a (rather minor) bug. There is an extra assignment that clears the execution attempt counter after a successful run of job. Since a successful run will exit the loop, clearing it has no effect (unless it is the sleep command that fails, that would be an interesting test scenario).

Since we haven’t shown the test results for a while, here’s how we stand at this point:

7 tests, 5 assertions, 0 failures, 0 errors

Processing Multiple Jobs

Now we know that we can handle a single job successfully. Now let’s make sure that we can handle multiple jobs. Remember that we broke process into two methods: process_one_job and a much shorter process that will call process_one_job in a loop.

Here’s what the original process method is looking like at the moment:

  def process
#     loop do
#     end
  end

We pulled out its guts and left the still commented loop there. We haven’t even bothered to have it call process_one_job yet. So let’s write a test that will force us to fix that.

We will just mock out process_one_job so that it must be called 10 times. On the eleventh call it throws a symbol that we catch in the test. Throwing a symbol is the trick that breaks us out of the infinite loop. By throwing a symbol (rather than raising an error), we don’t interact with the error handling logic of the code under test.

This is actually the trick refereced earlier. By breaking the body of the loop into a separate method, we only have to use this trick once rather than on each of the process job tests.

  def test_process_calls_process_one_job_in_a_loop
    q = F3DQueue.new
    flexmock(q).should_receive(:process_one_job).times(10)
    flexmock(q).should_receive(:process_one_job).and_return { throw :done }

    assert_throws(:done) do 
      q.process
    end
  end

To get this to pass, we implement the process method as follows:

  def process
    loop do
      process_one_job
    end
  end

Threading Issues

Finally we need to make sure a thread is started. Here is another place I changed the code to make testing easier. The original code base started a thread in the initializer of the object. This means that every F3DQueue object ran in its own thread. This would means every test would have to deal with multithread issues. Yuck!

I changed the code so that a thread is started only when explicitly calling the start method. I like this better for real object anyways. Although it is an extra step, it gives you more control about when the threads are started. If you really want to start a thread at object creation, you can just say:

queue = F3DQueue.new.start

Since I really don’t want to start a Thread in the test (I just want to make sure that the Thread.new method is called), I mock out Thread.new so that it must be called once and when called will execute the given block.

I then mock out the process method to that it must be called once. The combination of these two mocks will ensure that start will start a new thread that calls process.

And finally, I ensure that the return value of start will be the queue object. This makes sure that the F3DQueue.new.start idiom works.

  def test_start_will_start_a_process_thread
    q = F3DQueue.new
    flexmock("thread", Thread).should_receive(:new).with(Proc).once.
      and_return { |block| block.call }
    flexmock(q).should_receive(:process).once

    return_value = q.start
    assert_equal q, return_value
  end

And is is the little start method that needed to be written for the test. The Thread.new line is moved from the initialize method to here.

  def start
    Thread.new do process end
    self
  end

Here’s our final test run:

9 tests, 7 assertions, 0 failures, 0 errors

Code Coverage

We know that TDD gives pretty code code coverage stats out of the box. How did our “Comment-out First” approach do with regards to code coverage?

Here is the RCov report:

+----------------------------------------------------+-------+-------+--------+
|                  File                              | Lines |  LOC  |  COV   |
+----------------------------------------------------+-------+-------+--------+
|AutoF3D.rb                                          |     5 |     2 | 100.0% |
|f3dqueue.rb                                         |    82 |    53 | 100.0% |
|test_f3dqueue.rb                                    |   100 |    76 | 100.0% |
+----------------------------------------------------+-------+-------+--------+
|Total                                               |   187 |   131 | 100.0% |
+----------------------------------------------------+-------+-------+--------+
100.0%   3 file(s)   187 Lines   131 LOC

Wow! 100% on the first try.

Final Code Samples

You can find the final versions of the F3DQueue object and its tests here:

• F3DQueue Code
• F3DQueue Test Code

Future Directions

Now that the F3DQueue object is well testing, it is time to take a step back and think about the overall design of the class. There are a couple of things that stick out in my mind about this code.

(1) First Item

We did a lot of mocking on the F3DQueue object itself while it was being testing. Although a valid technique, you must be careful so that you don’t end up just testing your own mocks. What it does indicate is that the object you are testing might be trying to do too many things. Perhaps the class needs to be broken up into small classes, or perhaps some functionality needs to move into other classes.

With this in mind, the run method seems to know an awful lot about the workings of an Auto3D job object. It seems a bit out of place. Why don’t we move the run method to the job itself. Moving run into the Auto3D job object would allow us to write the following code fragment (in the process_one_job method):

...
  job = remove_from_queue
    begin
      if job
        job.run                       # was: run job
        sleep SERVER_RECOVERY_TIME
...

Now, our queue class is one method shorter and is just concerned with the scheduling of the jobs and not the details of running the job itself. This is good …

Except for the following little piece of code, which leads us into the second thing that bothered me:

  def add_to_queue(modelLoc, params, gridFile)
    autoF3D = AutoF3D.new(modelLoc, params, gridFile)
    @queue.push autoF3D
  end

(2) Second Item

Here we have direct knowledge of the AutoF3D class. If we remove the reference to AutoF3D, then our queue will suddenly become much more general, and usable in situations where we might want to process a different kind of job.

I would recommend changing the above code to:

  def add_to_queue(job)
    @queue.push job
  end

This does mean that adding a job to the queue would now have to create the job object explicitly. So, instead of:

   queue.add_to_queue(loc, param, grid)        

you would have to write:

   queue.add_to_queue(new AutoF3D.new(loc, param, grid))

If you don’t like to manually create an AutoF3D object all the time (and I don’t), then the following solution is an easy fix to that:

  queue = F3DQueue.new
  def queue.add_job(loc, params, grid)
    add_to_queue(AutoF3D.new(loc, params, grid))
  end

The more traditionally minded of us might want to just subclass the F3DQueue class and add the add_job method in the subclass rather than in the singleton class. That works too. Either way, it is easy to do.

Recap

I hope this was useful for you. Here is a recap of some of the important ideas from this exercise:

• Comment-First is not a bad way to handle legacy code.

• Test scenarios, not methods. Note that I didn’t just pick a method in F3DQueue and write a single test for it. I choose scenarios that would exercise different sections of the code base. Start with the simple (e.g. a Job that Doesn’t Fail). Then pick increasing harder scenarios (e.g. “a Job that Fails Once”, “a Job that Fails Multiple Times”).

• Don’t be afraid to refactor to make testing easier. Breaking out process_one_job was a great idea that not only made testing much easier, but made the code easier to read.

• The “Use Symbols as Cheap Mocks” is an idea I stole from Stu Halloway in his “Refactoring of the Week” presentation. If a method takes arguments that you don’t want to deal with, try passing in symbols. If the arguments aren’t used, the symbols work great. If an argument is actually used, the error message will identify the symbol at fault. At that point, just replace the symbol with the appropriate mock. This technique save you lots of time and makes the tests easier to read.

• If you want to break out of an infinite loop in the code under test, throw a symbol from your mocks and catch it in your test. This generally doesn’t interfere with any exception handling code in your code under test.

• Always take a step back and look for ways of improving the code. A well tested module is fairly easy to change with confidence. Don’t be afraid to improve things.

More Samples

Do you have a bit of code that you are having trouble testing? If so, go ahead and send it to me. If your code is interesting enough, I’ll take a look at it and post the results here (so don’t send anything you aren’t willing to see published in this blog). I can’t look at everything, but I’ll try to find some interesting examples.

Condensing thoughts down to one sentence …

In One Sentence …

So I was asked this question in IM today:

If you had one sentence to explain to a Java programmer why Dependency Injection is rarely necessary in Ruby, what would it be?

Wow, one sentence! After some thought, here’s what I sent back:

Dependency injection provides vital flexibility in Java and unneeded overhead in Ruby.

Anyone have other suggestions?

Bruce Williams asked this question at RailsConf, and I am soliciting feedback.

Background

First, a little background. There are two possibilities when calling flexmock(). First, you are creating a full mock object:

# Example 1
mock = flexmock("description")
mock.should_receive(...)

A full mock fulfills two roles: (1) it is a target for should_receive to define expectations, and (2) it is a target for normal domain messages when testing.

The other possibility is that you are creating a partial mock (i.e. a regular Ruby object with just a few mocked methods):

# Example 2
real_obj = RealObject.new
proxy_mock = flexmock(real_obj, "description")
proxy_mock.should_receive(...)

The object returned from the flexmock() method is actually a proxy object that can accept should_receive() messages to define the expectations, but does not handle normal domain messages. After all, we have a real object that that handles domain messages.

Partial Mocks

It is clear that when creating a partial mock using the non-block form of flexmock(real_obj), we must return the proxy, else there would be no way to add expectations. But the return value for the block form of flexmock is not so clear.

Consider the following code:

# Example 3
real_obj = RealObject.new
result = flexmock(real_obj) do |mock|
  mock.should_receive(...)
end

Here the proxy object is passed as the block argument. All the expectation setup is done within the block. It is very tempting to write this code as:

# Example 4
result = flexmock(RealObject.new) do |mock|
  mock.should_receive(...)
end

But here is the problem: in example 4 we no longer have a reference to the RealObject instance. The flexmock() method returns the proxy object, not the real object; just as it does in the non-block form.

Bruce’s Suggestions

Bruce suggested changing the block version of flexmock() to go ahead and return the real object. Since the proxy is used in the block, there is no real need for it outside the function. And, I will admit, example 4 is short and relatively clear, especially with those familiar with the returning idiom used in Rails.

The Dilemma

So here is my dilemma. Changing FlexMock so that example 4 works properly is attractive. And I suspect that the return value of flexmock(real_obj) is not ever used in a significant way in existing code, so backwards compatibility should be be only a minor concern. However, changing the return object based on whether or not the method has a block just seems … wrong.

There is precedent for this. In the standard Ruby libraries open(fn) and open(fn) { ... } return different things (an open file for the former and the value of the block for the latter). I’ve never had problems with this behavior in open, so perhaps I am just being over sensitive here.

I told Bruce I would blog the issue and consider the feedback received. So let me know what you think. Should flexmock() be modified to return the real_object when defining partial mocks using the block form?

You can email me (jim@weirichhouse.org) or add a comment using the comments link below.

FlexMock is a flexible mocking library for use in unit testing and behavior specification in Ruby. Version 0.6.0 introduces a number of API enhancements to make testing with mocks even easier than before.

New in 0.6.0

• Better integration with Test::Unit (no need to explicitly include FlexMock::TestCase).
• Integration with RSpec (version 0.9.0 or later of RSpec is required).
• The flexmock method will now create both regular mocks and partial mocks.

     flexmock()          # => a full mock
     flexmock(person)    # => a partial mock based on person
  

  (flexstub is still included for backwards compatibility).

• Quick and simple mocks my now be created using an expectation hash. For example:

    flexmock(:foo => 10, :bar => "Hello")
  

  will create a mock with two methods, :foo and :bar,defined. :foo will return 10 when invoked, and :bar will return "Hello".

• The should_receive method will now allow multiple methods (with the same constraints) be defined in a single call. For example, the following declares that both :read and :write need to be called at least one time each on the mock object.

    flexmock.should_receive(:read, :write).at_least.once
  

• should_recieve now will allow expectation hashes as arguments. This is similar to the list of methods, but allows each defined method to have its own return value.

    flexmock.should_receive(:name => "John", :age => 32)
  

• In addition to using a block for defining constrains, constraints may now be applied directly to the return value of new_instances. Combined with the expectation hashes supported by should_receive, simple mocking scenarios have become much more succinct. For example:

      flexmock(Person).new_instances.should_receive(:name => "John", :age => 32)
  

• Improved implementation, allowing for more flexible use and greater consistency between full mock and partial mocks.
• Version 0.6.0 also includes a fix for an incompatibility with some older versions of RCov. The FlexMock Rakefile now includes a RCov task (and we have 100% code coverage).

What is FlexMock?

FlexMock is a flexible framework for creating mock object for testing. When running unit tests, it is often desirable to use isolate the objects being tested from the "real world" by having them interact with simplified test objects. Sometimes these test objects simply return values when called, other times they verify that certain methods were called with particular arguments in a particular order.

FlexMock makes creating these test objects easy.

Features

• Easy integration with both Test::Unit and RSpec. Mocks created with the flexmock method are automatically verified at the end of the test or example.
• A fluent interface that allows mock behavior to be specified very easily.
• A "record mode" where an existing implementation can record its interaction with a mock for later validation against a new implementation.
• Easy mocking of individual methods in existing, non-mock objects.
• The ability to cause classes to instantiate test instances (instead of real instances) for the duration of a test.

Example

Suppose you had a Dog object that wagged a tail when it was happy. Something like this:

  class Dog
    def initialize(a_tail)
      @tail = a_tail
    end
    def happy
      @tail.wag
    end
  end

To test the Dog class without a real Tail object (perhaps because real Tail objects activate servos in some robotic equipment), you can do something like this:

require ‘test/unit’ require ‘flexmock/test_unit‘

  class TestDog < Test::Unit::TestCase
    def test_dog_wags_tail_when_happy
      tail = flexmock("tail")
      tail.should_receive(:wag).once
      dog = Dog.new(tail)
      dog.happy
    end
  end

FlexMock will automatically verify that the mocked tail object received the message wag exactly one time. If it doesn’t, the test will not pass.

See the FlexMock documentation at flexmock.rubyforge.org for details on specifying arguments and return values on mocked methods, as well as a simple technique for mocking tail objects when the Dog class creates the tail objects directly.

Availability

You can make sure you have the latest version with a quick RubyGems command:

  gem install flexmock    (you may need root/admin privileges)

Otherwise, you can get it from the more traditional places:

You will find documentation at: flexmock.rubyforge.org.

— Jim Weirich

Google4R is a simple Ruby wrapper around the Google APIs. In this extended example, we will use FlexMock to test software that uses the Google APIs, without every communicating with Google itself.

Purchase.rb

Here is the bit of code that we will be testing…

  require 'google4r/checkout'
  require 'item'

  class Purchase

    def initialize(config)
      @frontend = Frontend.new(config)
      @frontend.tax_table_factory = TaxTableFactory.new
    end

    # Purchase the +quantity+ items identified by +item_id+.  Return the
    # confirmation page URL.
    def purchase(item_id, quantity=1)
      item = Item.find(item_id)
      checkout = @frontend.create_checkout_command
      checkout.cart.create_item do |cart_item|
        cart_item.name = item.name
        cart_item.description = item.description
        cart_item.unit_price = item.unit_price
        cart_item.quantity = quantity
      end
      response = checkout.send_to_google_checkout
      response.redirect_url
    end

  end

FrontEnd is a Google4R class that provides a lot of the front end work for talking to the Google APIs. The config object given to the Purchase initializer is simply a hash of values defining the merchant_id, merchant_key and sandbox flag. To use the real Google checkout APIs, you will need to obtains a merchant id and key from Google. Since we will be mocking the Google interaction, we can use dummy values in our test.

The tax table factory is required by the Google4R software. We provide the following simplified one. Read the Google API documents for more information.

  class TestTaxTableFactory
    def effective_tax_tables_at(time)
      tax_free_table = TaxTable.new(false)
      tax_free_table.name = "default table"
      tax_free_table.create_rule do |rule|
        rule.area = UsCountryArea.new(UsCountryArea::ALL)
        rule.rate = 0.0
      end
      return [tax_free_table]
    end
  end

Item is simply an ActiveRecord class that we are using to hold our purchase item information. It should respond to the name, description and unit_price messages.

Testing Without Using External Resources

Our first test attempt will be to run the purchase method without talking to either the live Google web services, or hitting an actual ActiveRecord database.

Mocking Active Record

The ActiveRecord part is easy to mock. The following will handle it:

  flexmock(Item).should_receive(:find).with(1).and_return(
    flexmock("guitar",
      :name => "Deschutes",
      :description => "Deschutes model Guitar",
      :unit_price => Money.new(2400.00)))

We have mocked out the find method on Item so that whenever we call find with an integer argument of 1, we will return a mock item that will report its name, description and unit_price. This gives us an item for testing without actually reading the database.

Mocking the Google Web Services Call

Next we want to prevent the Google4R API from actually talking to the live web service. Everything that happens in the purchase method is all done locally except for the final call to send_to_google_checkout. All we need to do is mock out that one method.

  flexmock(Google4R::Checkout::CheckoutCommand).new_instances do |instance|
    instance.should_receive(:send_to_google_checkout).once.
      and_return(flexmock(:redirect_url => "http://google.response.url"))
  end

When we ask FrontEnd to create a check out command, it returns an instance of Google4R::Checkout::CheckoutCommand. We then use flexmock to specify that when Google4R::Checkout::CheckoutCommand creates a new instance, it should actually return a partial mock of that instance. The block given to the new_instances method allows us to configure the mocked checkout command. We tell it return a response object (yes, another mock) that report our dummy response URL.

The Final Result

Here is the complete unit test:

  def test_buying_a_guitar
    # Setup
    flexmock(Item).should_receive(:find).with(1).and_return(
      flexmock("guitar",
        :name => "Deschutes",
        :description => "Deschutes model Guitar",
        :unit_price => Money.new(2400.00)))

    flexmock(Google4R::Checkout::CheckoutCommand).new_instances do |instance|
      instance.should_receive(:send_to_google_checkout).once.
        and_return(flexmock(:redirect_url => "http://google.response.url"))
    end

    # Execute
    p = Purchase.new({
      :merchant_id => 'dummy_id',
      :merchant_key => 'dummy_key',
      :use_sandbox => true })
    url = p.purchase(1)

    # Assert
    assert_equal "http://google.response.url", url
  end

Testing the Details

The above test is fine as far as it goes. It demonstrates how to use mocks to avoid talking to external resources such as databases and web services. But as a unit test, it is sorely lacking in several areas.

All the test really demonstrates is that the send_to_google_checkout method is called. There are no tests to ensure that the right item descriptions and prices are correctly stored in the cart. In fact, if we rewrote the purchase method as follows:

  def purchase(item_id, quantity=1)
    @frontend.create_checkout_command.send_to_google_checkout.redirect_url
  end

it would still pass the unit test we designed, even though the rewrite is obviously an incorrect implementation.

A more complete test is a bit more complicated. Here are the details.

Mocking Active Record

Our incorrect version of purchase never calls the find method of Item. We can easily test for that by adding a once constraint one that mock specification. Since find is a read-only method, we don’t really care if it is called multiple times, as long as it is called at least one time, so we will add an at_least modifier as well.

Finally, we are going to break the guitar mock out into its own declaration. The reason will become obvious in a bit.

  mock_guitar = flexmock("guitar",
    :name => "Deschutes",
    :description => "Deschutes model guitar",
    :unit_price => Money.new(2400.00))

  flexmock(Item).should_receive(:find).with(1).at_least.once.
    and_return(mock_guitar)

Mocking a Cart Item

The next bit is a wee bit complicated, but we will handle it a little bit at a time so that it doesn’t become overwhelming.

There are three main objects in the Google checkout API that we deal with in the next section.: (1) the checkout command object returned by the front end, (2) the cart object returned by the checkout command, and (3) the item passed to the block in the create_item call.

We will tackle them in reverse order, starting with the item objects given to the create_item block. The item must respond to four attribute assignments. This is straightforward to mock, just make sure you include the once constraint so that the assignments are required.

  mock_item = flexmock("item")
  mock_item.should_receive(:name=).with(mock_guitar.name).once
  mock_item.should_receive(:description=).with(mock_guitar.description).once
  mock_item.should_receive(:unit_price=).with(mock_guitar.unit_price).once
  mock_item.should_receive(:quantity=).with(1).once

Notice how we used the mock_guitar object defined earlier to provide values in the with constraint. This way we don’t have to repeat the explicit strings and values we are checking. (Keep it DRY!).

Mocking the Cart

The mock cart object will pass the mock_item to a block when the create_item method is called. We specify that with the following:

  mock_cart = flexmock("cart")
  mock_cart.should_receive(:create_item).with(Proc).once.and_return { |block|
    block.call(mock_item)
  }

FlexMock objects can handle blocks passed to them by treating them as the final object in the calling list. Use Proc in the with constraint to match the block and then invoke the block explicitly via block.call(…) in the and_return specification.

Mocking the Checkout Command

Finally, we tie it all together by mocking the checkout command. As before, we use new_instances to force newly created checkout commands to be stubbed. This time we not only mockout the send_to_google method, but we also mock the cart command to return the carefully crafted mock_cart object from the previous section.

  flexmock(Google4R::Checkout::CheckoutCommand).new_instances do |instance|
    instance.should_receive(:cart).with().once.and_return(mock_cart)
    instance.should_receive(:send_to_google_checkout).once.
      and_return(flexmock(:redirect_url => "http://google.response.url"))
  end

The Final Test Method

Here is the complete detailed version of the test method.

  def test_buying_a_guitar_with_details
    # Setup
    mock_guitar = flexmock("guitar",
      :name => "Deschutes",
      :description => "Deschutes model guitar",
      :unit_price => Money.new(2400.00))

    flexmock(Item).should_receive(:find).with(1).at_least.once.
      and_return(mock_guitar)

    mock_item = flexmock("item")
    mock_item.should_receive(:name=).with(mock_guitar.name).once
    mock_item.should_receive(:description=).with(mock_guitar.description).once
    mock_item.should_receive(:unit_price=).with(mock_guitar.unit_price).once
    mock_item.should_receive(:quantity=).with(1).once

    mock_cart = flexmock("cart")
    mock_cart.should_receive(:create_item).with(Proc).once.and_return { |block|
      block.call(mock_item)
    }

    flexmock(Google4R::Checkout::CheckoutCommand).new_instances do |instance|
      instance.should_receive(:cart).with().once.and_return(mock_cart)
      instance.should_receive(:send_to_google_checkout).once.
        and_return(flexmock(:redirect_url => "http://google.response.url"))
    end

    # Execute
    p = Purchase.new({
      :merchant_id => 'dummy_id',
      :merchant_key => 'dummy_key',
      :use_sandbox => true })
    url = p.purchase(1)

    # Assert
    assert_equal "http://google.response.url", url
  end

Summary

Testing with mock objects can get complex. We used seven different mock or partial mock objects in testing the interaction of our code with the Google checkout API. Most testing scenarios won’t require that many, but anytime your code touches something external, it might require a mock object for testing.

We should stop and ask ourselves: was it worth it? It seems like an awful lot of work just to test a very simple purchase method. Wouldn’t it just be easier to just use the Google API directly for testing and forget about the mocks?

Perhaps, but using mock objects have several definite advantages:

• You can run the test at any time without worrying whether Google, the internet, or anything else is up and connected.
• You can easy test for error conditions using mock objects. For example, does your code correctly handle the case where you get an exception when connecting to google? Mocks can easily create those error conditions that are difficult to achieve with real objects.

  E.g.

     instance.should_receive(:send_to_google_checkout).once.
       and_return { raise Google4R::Checkout::GoogleCheckoutError }
  

Some might point out that in the final test method we are hardly using Google4R software at all, most of the code we interact with are mock objects. Doesn’t that defeat the purpose of testing?

The answer is simple. Always keep in mind what you are testing. The goal of the TestPurchase test case is not the make sure the Google4R code is correct, but that our Purchase class correctly interoperates with it. We do that by carefully stating what methods are called with what arguments and what they return. The test just checks that we are using to external software as we expect it to. We don’t actually care about the Google4R software itself in this test case (presumably we do have tests that cover Google4R, but those are different tests).

In the end, mock objects are a power tool to have in your testing toolbox.

It’s a bit hard to dig up, but I did figure out how to do UDP packet multicasting in Ruby.

Multicasting

I’ve been playing around with some network peer to peer discovery techniques and wanted to try some of them out in Ruby. The trick to self discovery is the ability to send network packets without knowing the address of the receiver. To do this, you either have to broadcast or multicast.

Because broadcasted packets are received by every device on the local network, it is generally considered good manners to not use broadcasted packets.

Multicasting, on the other hand, is only received by hosts that explicitly express an interest in the multicast address. Although abuse of multicasting is still bad manners, it is a better option than broadcasting.

Sending Multicast Packets

The IP addresses 224.0.0.0 through 239.255.255.255 are reserved for multicast messages. Simply sending a UDP messsage to an address in that range is sufficient.

One minor refinement is to set the TTL (Time To Live) option on the socket. My understanding is that this controls how far the packet is propagated. As polite net-citizens, we don’t want our multicast packets travelling too far abroad, so we set the TTL value to 1 (we need the ugly packing stuff because the value is passed directly to the C level setsockopt() function with no interpretation by Ruby).

So the Ruby code to send a multicast message is:

require 'socket'

MULTICAST_ADDR = "225.4.5.6" 
PORT= 5000

begin
  socket = UDPSocket.open
  socket.setsockopt(Socket::IPPROTO_IP, Socket::IP_TTL, [1].pack('i'))
  socket.send(ARGV.join(' '), 0, MULTICAST_ADDR, PORT)
ensure
  socket.close 
end

Receiving Multicast Messages

Receiving a multicast message is a bit tricker. Since multicast messages are generally ignored unless someone has explicitly registered an interest in a particular address, there is a bit of setup that needs to be done.

Here’s the code for receiving multicast messages:

require 'socket'
require 'ipaddr'

MULTICAST_ADDR = "225.4.5.6" 
PORT = 5000

ip =  IPAddr.new(MULTICAST_ADDR).hton + IPAddr.new("0.0.0.0").hton

sock = UDPSocket.new
sock.setsockopt(Socket::IPPROTO_IP, Socket::IP_ADD_MEMBERSHIP, ip)
sock.bind(Socket::INADDR_ANY, PORT)

loop do
  msg, info = sock.recvfrom(1024)
  puts "MSG: #{msg} from #{info[2]} (#{info[3]})/#{info[1]} len #{msg.size}" 
end

The tricky part was figuring out the right setsockopt options and values needed to register interest in our multicast address. I had to do a little reading in the Unix man pages on the C level setsockopt() function call. The third option to the C function is a structure that contains two 4-byte IP addresses. The first IP address is the multicast address, and the second IP address is the address of the local host adapter that we wish to use to listen for the multicast. The 0.0.0.0 address means use any of the local network adapters. IPAddr handles parsing the human readable form of the IP address and returns a string of 4 bytes in the order needed by the C level setsockopt() function.

Usage

Save the above code in files named send.rb and rcv.rb. In one console window, type:

ruby rcv.rb

In another console window on the same or different machine (on the same local network), type:

ruby send.rb This is a test.

For more fun, bring up several receive windows and all will receive the messages send by the send script.

I can think of all kinds of fun things to do with this.

Update

I added the Time To Live option on send.