Monday, January 21, 2008

Programming Language Continuum

Introduction

Ever since I started getting into less-than-mainstream programming languages, I've pondered how to go about classifying them according to their attributes in the hopes that it would yield insight into what an ideal programming language would be. There is the genealogical way that traces roots and influences, but that doesn't break down attributes or make any qualitative judgements. Here I intend to mostly frame the context for debate, rather than draw significant conclusions. I believe bringing some more structure to the discussion is necessary before much more can be gleaned from it.

So what I've done is attempt to break the essence of a programming language down into two dimensions:

  1. Enforced Structure / Dynamism
  2. Engineered Foundations / Mathematical Foundations

Here's a loose attempt at classifying some languages:

Enforced Structure vs Dynamism

Recent debates have focused heavily on the difference between statically typed and dynamically typed languages. I believe that this is a specific case of the more general issue of "how much structure should the programming language force on the programmer?" Today we see Java versus Ruby, but it could just as easily be Ada versus Lisp. On you side of the debate you have people who believe that heavily structured languages are essential for scaling and helping ensure correctness. One of my college professors once said (paraphrased) "the compiler is your friend, help it catch your errors for you." Also, a well defined and compiler checked structure can help scale programming projects up to large teams by ensuring that all team members are working to the same program structure. Finally, they point out the sophisticated tools that available for many statically typed languages, particularly refactoring tools, but also code generators and static validators.

On the other side of the debate you have dynamic language advocates. They claim that statically typed languages are too constraining and require more up-front design than is practical, especially given the vague and changing requirements typical of software development projects. Furthermore, robust code an be achieved through automated testing and by significantly reducing the amount of code required to deliver the required functionality. Finally, they point out the quicker feedback cycles that dynamic languages enable by shortening the change->compile->deploy->test loop to change->test. There was a time when this loop was actually figured into software development cost and schedule estimates, but today outside of very large projects it is simply a cognitive disruption.

Engineered vs Mathematical Foundations

Most of the mainstream programming languages have been "engineered" or "designed" to better enable some group of programmers to better achieve some objective. For example, Ada was engineered to enable the development of very large, complicated and highly reliable systems by huge teams. SmallTalk was designed to enable the construction of modular software in a more natural or "human" manner. COBOL was designed to enable business analysts to program. The list goes on and on, but the common theme is that most of these languages were designed or engineered with very specific design goals, and those goals were largely disconnected from strong mathematical foundations.

On the other side of the spectrum you see languages that are very strongly influenced by computer science theory. Lisp started out as an executable implementation of the untyped lambda calculus and has stayed fairly true to that origin. Haskell combines the typed lambda calculus with category theory and focuses on functional purity. Prolog is based on logic, and SQL on relational theory. What these languages offer, especially strongly typed ones like Haskell, is that they enable computer programs to be much more easily reasoned about by theorem provers (and similar) and therefore can provide a much higher degree of safety. To the initiated, they also provide much more natural and elegant abstractions.

Hybrid Languages

The idea of dynamic languages with option type annotations is often raised as a potential means to bridge the divide between the advocates of static and dynamic languages. Common Lisp provides optional compile-time type checking, but in practice is seems to be used mostly as an optimization in special cases rather than as a means of ensuring correctness. Some touted StrongTalk as an answer, especially when Sun released it as open source, but it seems to have sputtered out. There was much talk about adding optional type annotations to Python, but I believe (please correct me if I am wrong) it is still absent from Python 3000. So while optional static typing is a favorite debate topic, its not popular in the languages that have it and attempts to add it to languages that don't have yet to reach fruition, despite considerable effort.

A recent phenomena, or perhaps simply recently receiving attention, are hybrid languages that attempt to blend concepts from strongly-typed functional languages such as Haskell with more mainstream object-oriented underpinnings. In my opinion, Scala is probably the best of these, as it offers innovative OO features in addition to functional ones, but others such as F# and OCaml certainly deserve mentioning, as do no doubt countless others that I am unfortunately going to neglect.

Conclusion

I think that hybrid static/dynamic languages will never really become popular - or more accurately that the capability will not be extensively used in the languages that offer it. There are a couple reasons for this. Primarily, I think that making static typing optional almost completely eliminates the benefits of static typing. Second, I think the primary advantage of dynamic languages is that they allow partially formed thoughts to be quickly expressed in "working" (meaning running, not correct) code, and that static typing is a major barrier to this. I personally find doing exploratory programming in dynamic languages to be much more pleasant and productive, but once ideas are concrete I prefer the compile-time checks and completeness of static typing.

I personally believe that languages that blend the engineered structure of OO with mathematical formalism represent the future of programming. Scala and F# are here, and both Java and C# are gradually acquiring features from strongly typed functional languages. What's going to be interesting is how it shakes out. If you peruse the Scala mailing list archives, you will notice that there is a marked tension between those from an object-oriented (engineered) perspective who enjoy the extra power that functional programming provides them, versus those from a more pure functional programming background (mathematical). Ultimately, at least from a popularity perspective, I think the more OO approach will win, as historically languages engineered to provide specific advantages have won out over languages with robust mathematical underpinnings.

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