SOFTWARE ENGINEERING blog & .lessons_learned
manuel aldana
Manuel Aldana

January 9th, 2011 · No Comments

Static typed programming/languages won’t die!

In recent years dynamic typed languages like Ruby, Groovy, JavaScript or Python rightly gained more popularity. Some even said they will soon replace their static typed counterparts. Though I am a big fan of dynamic typed and intepreted languages (for smaller tools/tasks they make life so much easier) my current bet is that the language-future it is not a question of either/or but a gain of diversity of your toolset. Static typed languages just have this big diverse plus when it comes to maintainability of big codebases.

Overview of differences

Because there still is some confusion about dynamic vs. static typing here a short overview of my perception:

  1. Dynamic typed programming: The types or variables are bound during runtime. This happens if you use languages which have dynamic typing in their core design (PHP, Ruby, Python). Be aware that you can still do dynamic typing with languages focusing more on static typing (like C# or Java): Simply have a look at the reflection APIs… Further more type saftey is deferred to runtime, if a programmer introduces typing errors they will pop up during runtime (e.g. ClassCastException, MethodNotFoundException, TypeError).
  2. Static typed programming: The types are resolved/bound during compile time. For this check to be possible your code needs to have typing information (e.g. when defining a variable or method signature). If you have obvious type errors in your code the compilation result will catch it and inform you.

Pros dynamic typing

If designed correctly into the language, dynamic typing offers a lot of advantages:

  • Code is much more compact. Small tools and scripts are a charm to write and some nice syntactic sugar constructs are possible. Programmers need less time to understand and extend code. Further more the proportion of functionality vs. lines-of-code is greater, you need to produce less code to solve a problem. Smaller codebases are a plus for maintenance.
  • Sometimes dynamic typing is a necessity of solving a problem (e.g. the calculated return value is dependant on the parameter’s type, which can differ for every caller).
  • Development feedback cycle tends to be shorter. Most languages offering dynamic typing are intepreted and a simple ‘Save file’ will do. In most cases you instantly will see the effect. For bigger server applications less restarts of the server are necessary.

Pros static typing: Maintainability

Above I mentioned compactness of code as a maintenance plus for dynamic typing. Still, on the same topic static typing scores significantly.

Analyzation of codebases

Typing information bloats code but also serves documentation. In many cases explicit typing helps a lot in reasoning the code’s semantics. Also the IDE can help to easily jump throughout the codebase. It doesn’t have to reason or guess but can directly guide you to the target code. Explicit typing information also does help tools like Structure101 or JDepend to automatically show you relationships, which can point to design or layering flaws.

Feedback of errors

You get faster feedback when you did a typing related coding-error, e.g. wrongly related a function/method or did a typo. The compliation phase does this for granted. Some argue that you anyway should do cover anything by automated tests and therefore can instantly catch typing related programming errors. This theoretically is true but in practice doesn’t hold, I’ve never seen convincing test suites which execute every code-path instantly uncovering such errors. Often you get such errors later by accident, in testing phase or worse during production. Compile time type safety is nothing to be neglected…

Safe refactorings/tooling

It is the “nature” of dynamic typing that you can’t find out typing just looking at the structure of the code. The opposite is true for static typing, therefore you can create tools for safe and automated refactorings (e.g. Rename method/function, Add/Remove parameters, general restructuring of classes/modules). If many refactorings wouldn’t be automated I would lose a lot(!) of time. Being able to refactor codebases in an efficient sensible time is a must have for me. The greater the codebase the greater the cost for unsupported automated/unsafe refactorings. Some people again argue that 100% test-coverage safety-net would suffice, for my point of view see above ;)

I purposely discarded the old performance comparison. It states that compiled binary-code is faster as interpreted code. It may have been true in older times, but nowadays, also with all the JIT compiling features, I haven’t seen convincing benchmarks that static typed languages binaries are better in performance in general. This doesn’t imply that you won’t hit scaling problems which are indeed bound to a language (see also podcast about facebook getting problems with PHP at some point)!


Dynamic typed languages are great but for bigger codebases I still would go for languages like Java or C# (haven’t tried out yet, but Scala seems to be a new alternative here). For very specific modules solving highly generic/dynamic problems you still can code in the “right” language. Modern runtime environments (like JVM or CLR) give you possibility to deploy common-libraries/APIs, which are written in dynamic typed language.

If you have case studies or other resources investigating dynamic vs. static typing and overall productivity or providing different opinions please comment.

Tags: Software Engineering · Software Maintenance

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