examples/cxx-api/evaldemo.cc


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/* A simple Yosys plugin. (Copy&paste from http://stackoverflow.com/questions/32093541/how-does-the-yosys-consteval-api-work)

Usage example:

$ cat > evaldemo.v <<EOT
module main(input [1:0] A, input [7:0] B, C, D, output [7:0] Y);
  assign Y = A == 0 ? B : A == 1 ? C : A == 2 ? D : 42;
endmodule
EOT

$ yosys-config --build evaldemo.so evaldemo.cc
$ yosys -m evaldemo.so -p evaldemo evaldemo.v
*/

#include "kernel/yosys.h"
#include "kernel/consteval.h"

USING_YOSYS_NAMESPACE
PRIVATE_NAMESPACE_BEGIN

struct EvalDemoPass : public Pass
{
	EvalDemoPass() : Pass("evaldemo") { }

	void execute(vector<string>, Design *design) YS_OVERRIDE
	{
		Module *module = design->top_module();

		if (module == nullptr)
			log_error("No top module found!\n");

		Wire *wire_a = module->wire("\\A");
		Wire *wire_y = module->wire("\\Y");

		if (wire_a == nullptr)
			log_error("No wire A found!\n");

		if (wire_y == nullptr)
			log_error("No wire Y found!\n");

		ConstEval ce(module);
		for (int v = 0; v < 4; v++) {
			ce.push();
			ce.set(wire_a, Const(v, GetSize(wire_a)));
			SigSpec sig_y = wire_y, sig_undef;
			if (ce.eval(sig_y, sig_undef))
				log("Eval results for A=%d: Y=%s\n", v, log_signal(sig_y));
			else
				log("Eval failed for A=%d: Missing value for %s\n", v, log_signal(sig_undef));
			ce.pop();
		}
	}
} EvalDemoPass;

PRIVATE_NAMESPACE_END
(**Note:** If you get compiler errors that you don't understand, be sure to consult [Google Mock Doctor](FrequentlyAskedQuestions.md#how-am-i-supposed-to-make-sense-of-these-horrible-template-errors).)

# What Is Google C++ Mocking Framework? #
When you write a prototype or test, often it's not feasible or wise to rely on real objects entirely. A **mock object** implements the same interface as a real object (so it can be used as one), but lets you specify at run time how it will be used and what it should do (which methods will be called? in which order? how many times? with what arguments? what will they return? etc).

**Note:** It is easy to confuse the term _fake objects_ with mock objects. Fakes and mocks actually mean very different things in the Test-Driven Development (TDD) community:

  * **Fake** objects have working implementations, but usually take some shortcut (perhaps to make the operations less expensive), which makes them not suitable for production. An in-memory file system would be an example of a fake.
  * **Mocks** are objects pre-programmed with _expectations_, which form a specification of the calls they are expected to receive.

If all this seems too abstract for you, don't worry - the most important thing to remember is that a mock allows you to check the _interaction_ between itself and code that uses it. The difference between fakes and mocks will become much clearer once you start to use mocks.

**Google C++ Mocking Framework** (or **Google Mock** for short) is a library (sometimes we also call it a "framework" to make it sound cool) for creating mock classes and using them. It does to C++ what [jMock](http://www.jmock.org/) and [EasyMock](http://www.easymock.org/) do to Java.

Using Google Mock involves three basic steps:

  1. Use some simple macros to describe the interface you want to mock, and they will expand to the implementation of your mock class;
  1. Create some mock objects and specify its expectations and behavior using an intuitive syntax;
  1. Exercise code that uses the mock objects. Google Mock will catch any violation of the expectations as soon as it arises.

# Why Google Mock? #
While mock objects help you remove unnecessary dependencies in tests and make them fast and reliable, using mocks manually in C++ is _hard_:

  * Someone has to implement the mocks. The job is usually tedious and error-prone. No wonder people go great distances to avoid it.
  * The quality of those manually written mocks is a bit, uh, unpredictable. You may see some really polished ones, but you may also see some that were hacked up in a hurry and have all sorts of ad-hoc restrictions.
  * The knowledge you gained from using one mock doesn't transfer to the next.

In contrast, Java and Python programmers have some fine mock frameworks, which automate the creation of mocks. As a result, mocking is a proven effective technique and widely adopted practice in those communities. Having the right tool absolutely makes the difference.

Google Mock was built to help C++ programmers. It was inspired by [jMock](http://www.jmock.org/) and [EasyMock](http://www.easymock.org/), but designed with C++'s specifics in mind. It is your friend if any of the following problems is bothering you:

  * You are stuck with a sub-optimal design and wish you had done more prototyping before it was too late, but prototyping in C++ is by no means "rapid".
  * Your tests are slow as they depend on too many libraries or use expensive resources (e.g. a database).
  * Your tests are brittle as some resources they use are unreliable (e.g. the network).
  * You want to test how your code handles a failure (e.g. a file checksum error), but it's not easy to cause one.
  * You need to make sure that your module interacts with other modules in the right way, but it's hard to observe the interaction; therefore you resort to observing the side effects at the end of the action, which is awkward at best.
  * You want to "mock out" your dependencies, except that they don't have mock implementations yet; and, frankly, you aren't thrilled by some of those hand-written mocks.

We encourage you to use Google Mock as:

  * a _design_ tool, for it lets you experiment with your interface design early and often. More iterations lead to better designs!
  * a _testing_ tool to cut your tests' outbound dependencies and probe the interaction between your module and its collaborators.

# Getting Started #
Using Google Mock is easy! Inside your C++ source file, just `#include` `"gtest/gtest.h"` and `"gmock/gmock.h"`, and you are ready to go.

# A Case for Mock Turtles #
Let's look at an example. Suppose you are developing a graphics program that relies on a LOGO-like API for drawing. How would you test that it does the right thing? Well, you can run it and compare the screen with a golden screen snapshot, but let's admit it: tests like this are expensive to run and fragile (What if you just upgraded to a shiny new graphics card that has better anti-aliasing? Suddenly you have to update all your golden images.). It would be too painful if all your tests are like this. Fortunately, you learned about Dependency Injection and know the right thing to do: instead of having your application talk to the drawing API directly, wrap the API in an interface (say, `Turtle`) and code to that interface:

```
class Turtle {
  ...
  virtual ~Turtle() {}
  virtual void PenUp() = 0;
  virtual void PenDown() = 0;
  virtual void Forward(int distance) = 0;
  virtual void Turn(int degrees) = 0;
  virtual void GoTo(int x, int y) = 0;
  virtual int GetX() const = 0;
  virtual int GetY() const = 0;
};
```

(Note that the destructor of `Turtle` **must** be virtual, as is the case for **all** classes you intend to inherit from - otherwise the destructor of the derived class will not be called when you delete an object through a base pointer, and you'll get corrupted program states like memory leaks.)

You can control whether the turtle's movement will leave a trace using `PenUp()` and `PenDown()`, and control its movement using `Forward()`, `Turn()`, and `GoTo()`. Finally, `GetX()` and `GetY()` tell you the current position of the turtle.

Your program will normally use a real implementation of this interface. In tests, you can use a mock implementation instead. This allows you to easily check what drawing primitives your program is calling, with what arguments, and in which order. Tests written this way are much more robust (they won't break because your new machine does anti-aliasing differently), easier to read and maintain (the intent of a test is expressed in the code, not in some binary images), and run _much, much faster_.

# Writing the Mock Class #
If you are lucky, the mocks you need to use have already been implemented by some nice people. If, however, you find yourself in the position to write a mock class, relax - Google Mock turns this task into a fun game! (Well, almost.)

## How to Define It ##
Using the `Turtle` interface as example, here are the simple steps you need to follow:

  1. Derive a class `MockTurtle` from `Turtle`.
  1. Take a _virtual_ function of `Turtle` (while it's possible to [mock non-virtual methods using templates](CookBook.md#mocking-nonvirtual-methods), it's much more involved). Count how many arguments it has.
  1. In the `public:` section of the child class, write `MOCK_METHODn();` (or `MOCK_CONST_METHODn();` if you are mocking a `const` method), where `n` is the number of the arguments; if you counted wrong, shame on you, and a compiler error will tell you so.
  1. Now comes the fun part: you take the function signature, cut-and-paste the _function name_ as the _first_ argument to the macro, and leave what's left as the _second_ argument (in case you're curious, this is the _type of the function_).
  1. Repeat until all virtual functions you want to mock are done.

After the process, you should have something like:

```
#include "gmock/gmock.h"  // Brings in Google Mock.
class MockTurtle : public Turtle {
 public:
  ...
  MOCK_METHOD0(PenUp, void());
  MOCK_METHOD0(PenDown, void());
  MOCK_METHOD1(Forward, void(int distance));
  MOCK_METHOD1(Turn, void(int degrees));
  MOCK_METHOD2(GoTo, void(int x, int y));
  MOCK_CONST_METHOD0(GetX, int());
  MOCK_CONST_METHOD0(GetY, int());
};
```

You don't need to define these mock methods somewhere else - the `MOCK_METHOD*` macros will generate the definitions for you. It's that simple! Once you get the hang of it, you can pump out mock classes faster than your source-control system can handle your check-ins.

**Tip:** If even this is too much work for you, you'll find the
`gmock_gen.py` tool in Google Mock's `scripts/generator/` directory (courtesy of the [cppclean](http://code.google.com/p/cppclean/) project) useful.  This command-line
tool requires that you have Python 2.4 installed.  You give it a C++ file and the name of an abstract class defined in it,
and it will print the definition of the mock class for you.  Due to the
complexity of the C++ language, this script may not always work, but
it can be quite handy when it does.  For more details, read the [user documentation](../scripts/generator/README).

## Where to Put It ##
When you define a mock class, you need to decide where to put its definition. Some people put it in a `*_test.cc`. This is fine when the interface being mocked (say, `Foo`) is owned by the same person or team. Otherwise, when the owner of `Foo` changes it, your test could break. (You can't really expect `Foo`'s maintainer to fix every test that uses `Foo`, can you?)

So, the rule of thumb is: if you need to mock `Foo` and it's owned by others, define the mock class in `Foo`'s package (better, in a `testing` sub-package such that you can clearly separate production code and testing utilities), and put it in a `mock_foo.h`. Then everyone can reference `mock_foo.h` from their tests. If `Foo` ever changes, there is only one copy of `MockFoo` to change, and only tests that depend on the changed methods need to be fixed.

Another way to do it: you can introduce a thin layer `FooAdaptor` on top of `Foo` and code to this new interface. Since you own `FooAdaptor`, you can absorb changes in `Foo` much more easily. While this is more work initially, carefully choosing the adaptor interface can make your code easier to write and more readable (a net win in the long run), as you can choose `FooAdaptor` to fit your specific domain much better than `Foo` does.

# Using Mocks in Tests #
Once you have a mock class, using it is easy. The typical work flow is:

  1. Import the Google Mock names from the `testing` namespace such that you can use them unqualified (You only have to do it once per file. Remember that namespaces are a good idea and good for your health.).
  1. Create some mock objects.
  1. Specify your expectations on them (How many times will a method be called? With what arguments? What should it do? etc.).
  1. Exercise some code that uses the mocks; optionally, check the result using Google Test assertions. If a mock method is called more than expected or with wrong arguments, you'll get an error immediately.
  1. When a mock is destructed, Google Mock will automatically check whether all expectations on it have been satisfied.

Here's an example:

```
#include "path/to/mock-turtle.h"
#include "gmock/gmock.h"
#include "gtest/gtest.h"
using ::testing::AtLeast;                     // #1

TEST(PainterTest, CanDrawSomething) {
  MockTurtle turtle;                          // #2
  EXPECT_CALL(turtle, PenDown())              // #3
      .Times(AtLeast(1));

  Painter painter(&turtle);                   // #4

  EXPECT_TRUE(painter.DrawCircle(0, 0, 10));
}                                             // #5

int main(int argc, char** argv) {
  // The following line must be executed to initialize Google Mock
  // (and Google Test) before running the tests.
  ::testing::InitGoogleMock(&argc, argv);
  return RUN_ALL_TESTS();
}
```

As you might have guessed, this test checks that `PenDown()` is called at least once. If the `painter` object didn't call this method, your test will fail with a message like this:

```
path/to/my_test.cc:119: Failure
Actual function call count doesn't match this expectation:
Actually: never called;
Expected: called at least once.
```

**Tip 1:** If you run the test from an Emacs buffer, you can hit `<Enter>` on the line number displayed in the error message to jump right to the failed expectation.

**Tip 2:** If your mock objects are never deleted, the final verification won't happen. Therefore it's a good idea to use a heap leak checker in your tests when you allocate mocks on the heap.

**Important note:** Google Mock requires expectations to be set **before** the mock functions are called, otherwise the behavior is **undefined**. In particular, you mustn't interleave `EXPECT_CALL()`s and calls to the mock functions.

This means `EXPECT_CALL()` should be read as expecting that a call will occur _in the future_, not that a call has occurred. Why does Google Mock work like that? Well, specifying the expectation beforehand allows Google Mock to report a violation as soon as it arises, when the context (stack trace, etc) is still available. This makes debugging much easier.

Admittedly, this test is contrived and doesn't do much. You can easily achieve the same effect without using Google Mock. However, as we shall reveal soon, Google Mock allows you to do _much more_ with the mocks.

## Using Google Mock with Any Testing Framework ##
If you want to use something other than Google Test (e.g. [CppUnit](http://sourceforge.net/projects/cppunit/) or
[CxxTest](http://cxxtest.tigris.org/)) as your testing framework, just change the `main()` function in the previous section to:
```
int main(int argc, char** argv) {
  // The following line causes Google Mock to throw an exception on failure,
  // which will be interpreted by your testing framework as a test failure.
  ::testing::GTEST_FLAG(throw_on_failure) = true;
  ::testing::InitGoogleMock(&argc, argv);
  ... whatever your testing framework requires ...
}
```

This approach has a catch: it makes Google Mock throw an exception
from a mock object's destructor sometimes.  With some compilers, this
sometimes causes the test program to crash.  You'll still be able to
notice that the test has failed, but it's not a graceful failure.

A better solution is to use Google Test's
[event listener API](../../googletest/docs/AdvancedGuide.md#extending-google-test-by-handling-test-events)
to report a test failure to your testing framework properly.  You'll need to
implement the `OnTestPartResult()` method of the event listener interface, but it
should be straightforward.

If this turns out to be too much work, we suggest that you stick with
Google Test, which works with Google Mock seamlessly (in fact, it is