CSC/ECE 517 Fall 2010/ch2 S24 sk

What is Metaprogramming

Metaprogramming is in essence using programs to manipulate other programs. the concept is actually a classic UNIX principle on writing code and is far from new. In fact, its technical beginning probably starts with Konrad Zuse's insight almost 70 years ago that a computer could prepare its own instructions. Metaprogramming has been garnering the attention of developers and software engineers in recent years, first with dynamic languages such as Ruby and more recently with static languages such as Java and C++.

Metaprogramming is also called generative programming. The idea is that instead of modifying simple data elements, you modify symbols (or patterns) that represent complex operations. This is achieved through three key components. A metalanguage where we define a generalization or pattern. A generator which is an expression of that generalization. And finally an instance which is the output from the evaluation of that generator. The goal is to generalize a set of concrete instances that can be evaluated and generated as a static representation of what we wish our code to accomplish. This takes polymorphism variation out of the code level and moves it up to the metalevel where it can be interpreted by Domain Specific Languages (DSLs) which describe how a system should be generated.

Metaprogramming in Practice

Before we elaborate to much on metaprogramming, here is some fundamental terminology to become familiar with.

• A Metaprogram represents a program that has the ability to modify another program or itself
• Reflection is the ability of a program to manipulate the state of a program during execution. This manipulation comes in two aspects: introspection and intercession
• Introspection is the ability of a program to observe and reason about its own state
• Intercession is the ability of a program to alter its own execution state or alter its own interpretation or meaning
• A Metaobject represents an object during reflection as well as execution stacks, the processor, and nearly all elements of the language and its exectution environment
• Metalevel Architecture provides information about selected system properties that helps enables generated code members to become self aware
• Partial Evaluation Evaluating a system while one part is varying or in the process of generation and another is constant

Even though metaprogramming in static languages has been getting a lot of attention from software creators recently, the capability has been around quite some time. In C for example, the preprocessor acts as the vehicle for generating code. This type of metaprogramming was mostly limited to simple macros due to the preprocessors lack of recursion and lack of type checking. This made generating code rather dangerous and complicated (a trait that has plagued metaprogramming). Still, it showed the need was there and as time went on the tools for building metaprograms became more robust.

In todays environment the generation of code in static programming infrastructures is handled by templates that extend the static language. To put it simply, a template has a name, a type, and a body. when the template executes, syntactiically correct code is generated. there are several different types of templates and depending on which you use the validity of the code at runtime will vary.

Code generators come in a couple of different flavors and depending on the task at hand one may be favored over another. Multistage templating offers control and well defined legalities. With this type of templating we get static safety checking that ensures type-correctness. MetaML, MetaCaml, and MetaD are examples of multistage metaprogramming template languages. The issue with multistage templates are that the well defined legalities decrease flexibility and add complexity to the language. This means that the specificity of the program it can match becomes more and more fine. remember we are tying to generalize our generation of code to make it applicable to many different situations. Single stage generators offer increased flexibility at the cost of less stringent type checking. They also allow for the generation of arbitrary code. SafeGen is an example of a single state metaprograming template language.

There are also several different categories of templates including expression templates for developing embedded domain specific languages, metafunctions for computing types and numbers, and also trait templates, and nested templates for representing metainformation.

Some key applications of metaprogamming are the translation of a program from one language to another, to transform a program , to refactor a program, to optimize a program, verification of a program, type checking a program, and to apply design patters to a program. A visual representation of how template metaprogramming can be applied is shown below.

Applications of template metaprogramming

Drawbacks of Metaprogramming

To talk about the challenges that occur when working with metaprograms I want to first start off with an example. Ruby is a dynamic language wher ecode generation is a key focus of its design. If we look at the example below:

class Person
   attr_accessor :name
end

is equivalent to:

class person
   def name
      @name
   end
   def name=(new_name)
      @name = new_name
   end
end

This is a basic metaprogramming construct that is used every day in Ruby. There is one minor drawback however. The instance variable is not initialized until we set its value from the given attribute. This means it is possible to receive a NIL value if we try to read this attribute of this class before writing to it. Now while this is a rather simple example that isn't going to cause anyone too many headaches, it does show that it is very easy to introduce bugs into your code through metaprogramming if you are not careful. It can also be the case that these bugs will stay hidden for quite some time before being discovered, usually by the end user of the system and not by the developer. Here is a list of the most common challenges encountered with metaprogramming:

• Debugging: Debugging is difficult in template metaprograms because it is challenging to verify for all possible inputs. Another issue is that typenames in the template generation can easily get into the thousands of characters due to nesting.
• Error Reporting: Error reporting is lacking because small changes or mistakes to a template can generate vastly differing code with a long list of errors that do not address the actual template that was written.
• Readability: Because there are no agreed upon standards for metaprogramming structure and static languages typically were not built with metaprogramming as a key focus, template code tends to not be readable (generated code even less so).
• Compilation Time: Template metacode is interpreted, not compiled. This may extend compilation time by orders of magnitude.
• Compiler Size: Compiler sizes vary but when generating code that is doing complex computations, it is something to be careful of.
• Portability: Template metaprogramming is evolving at a rapid pace. A particular compiler may not support what the metaprogrammer is trying to do.

Addressing the Drawbacks

Reflex Structural Model

Conclusions

References