Disciplined Meta-Programming

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Computer scientists have been writing programs which manipulate programs (such as compilers) for a very long time. Software engineers, on the other hand, have been much slower to use this particular technique, mostly because standard design methodologies do not embrace such techniques. This has recently started to change, and there are a variety of reasons for this, amongst which: 1. the increasing popularity of Domain Specific Languages, 2. the fact that writing parallel software by hand is difficult and error-prone, and 3. that current programming languages offer poor "higher-level" abstraction mechanisms. Unfortunately, few meta-programs (as programs which manipulate programs are called) encountered "in the wild" are as well-structured as "regular" programs. In other words, there does not seem to be good development models for writing such programs. This is rather unfortunate, as meta-programs allow standard software engineering concepts (such as design choices) to become first-class software artifacts. Furthermore, in the case of mature domains (like scientific computation), higher-order structure can be effectively captured and leveraged to both drastically shorten source programs as well as to generate more efficient run-time programs. Our objective is to rectify this situation, in the context of statically-typed, purely functional meta-programming. We will continue our successful work on finding and inventing the techniques necessary for writing disciplined and modular meta-programs. One very successful approach has been to take program families, and engineer non ad hoc abstractions which appropriately capture the design choices of those families. These abstractions form the core of generators for the family members. Through writing larger generative libraries of reusable components (for scientific computation and for games), we will leverage our ongoing foundational work on mechanized mathematics (the MathScheme project), as well as our expertise in advanced meta-programming techniques, to distill our experience-driven design knowledge into an effective development methodology which can appropriately encompass the design of principled meta-programs.