Choosing Your Programming Language – The Inside Scoop January 28, 2012

Posted by jeffvroom in Java/JEE, Software.
11 comments

Many programmers prefer typeless, interpreted languages like PHP and Ruby for several reasons. They are more concise and easier to read and write for a novice. They tend to be interpreted languages, not compiled, which are simpler to use and typically offer faster round-trip time between making a change and seeing the result. They support a “google, cut and paste” type workflow more easily which, frankly is how many programmers operate these days.

And yet still strongly typed languages are more wide used, particularly as the complexity of the project and the number of the developers grows. I have discussed this issue with a number of colleagues and wanted to write down my thoughts. It’s important to choose the right language for the right job and today unfortunately, there’s no one size fits all answer so knowing the details may help.  My opinions were formed by poking around into the guts of the JVM, Python, PHP, Ruby, and Flash interpreters, and from coding in Java, C, and C++ extensively.

Typeless versus Typed

One reason I believe typed languages are used is the robustness of the code itself. Typeless languages offer a single-point of failure with each code construct. If you misspell a variable name, you do not find out until runtime and only by debugging the problem or through code inspection. With a typed language, each misspelling is caught at compile time because every name must occur in the program at least twice, once for the type definition, once for the usage. This fact alone will often make up for the extra key strokes you need to use in a typed language.

With typed languags, more is known about the system during the code editing process. This makes the tooling opportunities richer and reduces keystrokes which can make it faster to write code in a typed language than an untyped one, even though the typed language is more verbose. For example, handling imports, completion of member or method names. The “find all usages” feature is extremely valuable at tracing code paths and doing refactoring. Typeless languages may offer such features but they are much less specific as they must do only name matching, not type+name matching. The ability to change a field or method name and reliably update all references is a big time saver when modifying a large existing project.

Another reason people prefer typed languages of course is runtime performance. But why exactly do typed languages run so much faster? The biggest reason is that they offer a much faster way to evaluate “a.b” expressions and do method lookups (a.b()) at runtime. With a dynamic language, every single indirection requires a hashtable or binary search which turns into dozens or 100s of instructions. With a typed language, a compiler can frequently generate an “a.b” with just a few instructions using a “load from fixed offset” pattern. That’s why a typeless language will run usually at least 10X slower than a typed language no matter how many engineers Facebook puts on the problem.

Some folks today are trying to infer types in typeless languages to improve runtime performance. In limited cases they could compile typeless code to use fixed offsets. That may well be an area of research which could improve the performance of some typeless code. I suspect though that the code which will speed up will need to be well organized around common types and so written a lot like a typed language.

It also perhaps poorly understood that even typed languages do not always realize the a.b speedup for using fixed offsets. For example, when you use a feature like interfaces in Java, you do end up with some searching to find the right method in the general case. You may not see this all the time because Java employs a trick to cache the offset for the last type seen which sometimes eliminates that search in many cases. I have a project in which changing one interface to an abstract class improved performance by over 50%.

One other poorly understood performance factor in comparing typeless and typed language is when interpreted code calls native code. For example when PHP or Java calls some C function. Native transitions are usually substantially slower than normal method calls because of the extra work they need to do in translating data types, pinning down memory used by the native code, copying memory from an unmanaged to managed environment etc.

Though both typed and typeless languages suffer the same problem, in general typeless languages use more, higher level C libraries. That’s probably because writing them in the language itself is too slow or just the effort involved in writing the code itself is too high given the limited commercial support for typeless languages. With more native transitions, the performance hit for this design increases so just moving more code into the native layer may not make things faster when you need to make lots of native method calls.

Of course more use of native code turns into an advantage when you have a small amount of typeless code which just strings together a few efficient but long running native methods, like copying a file. In these systems the typeless language is almost as fast as C.

In general typeless languages have faster round trip times between changing code and seeing the change. Because they are typeless, when you update a module, you do not have to update the entire application. Changed code constructs can co-exist with unchanged constructs. In a typed language however, you have to update the type in a way that preserves the stricter typing contracts. Since the code itself relies on fixed offsets, when those offsets change, you have to update all of the code atomically which is hard to do and get right. Most typed languages cannot do that seamlessly and worse still, there’s no way to know when it will or won’t work making “Class patching” useful only in special cases where you can isolate all dependencies on that class that is being changed.

Interpreted versus Compiled

To get good performance as a project grows, even interpreted languages these days must cache compiled descriptions of the code. They do however retain the ease of use benefits in most cases because this is all done transparently, by the browser or the runtime engine. When the code changes, these caches are updated automatically. Without such a feature, interpreted languages bog down as code sizes grow. Each time a process restarts, too much code must be interpreted before you can use the system.

Thread Architecture

Java, C, and C++ are all multithreaded using operating system thread scheduling. In general, this means that all code must be “thread aware” though in practice, frameworks try to reduce the likeklihood of thread conflicts. When a framework is well designed, the burden of synchronization is not imposed on application code.

You need a threaded architecture when you need to share a large pool of memory or efficiently perform I/O with a bunch of sockets or files. You can more easily leverage a multi CPU environment with OS threading.

In contrast, even multi-threaded VMs like Python may have a global interpreter lock or will do VM based thread scheduling. Either of these architectures eliminates opportunities to do parallel I/O unless you switch to a multi-process model. For example, PHP will run each HTTP request in a separate process and so achieves some form of parallelism that way. But in doing so, it eliminates the use of shared memory which reduces the efficiency of memory caching. It also means that any data structure used by all HTTP requests must be replicated across all PHP processes further increasing both computation and RAM usage.

So for PHP, you’ll need even more memory and more CPU to populate that memory. You do still benefit from OS level file caching of course.

What about the Future?

I tried to be neutral in my analysis but you can probably tell from the above that I like the benefits of typed languages. When you consider long term costs, and include modifications, enhancements, transfer of code between developers, runtime efficiency for either large scale or mobile deployments, strongly typed languages win out.

I agree however with Ruby and PHP developers that we are not there yet when any strongly typed language today will beat out PHP and Ruby for any given project. As long as the code is easier to read and edit for most people, the typed language advantages may easily be outweighed by availability of people, cost, and the poor workflows that exist between complex typed languages like Java, C, C++ for designers, analysts, and admins.

To bridge the gap, we need a strongly typed language which has:

• simplified tools – the Java IDE is too complex for entry level programmers and others who work with PHP and Ruby code today
• syntax improvements to eliminate imports, use inferred typing, and in general simplify the syntax will bring typed languages much closer to untyped languages in readability/brevity.
• mixed interpreted/compiled modes and a way to migrate code between them as it solidifies
• updating of types for the common cases for immediate code updates. When that’s not possible the ability to know as soon as the code is changed that a restart is required.
• built in compilation, dependency management for automated builds, updates, deployments. Maven, ant, and IDE configuration are too complex today.

What do you think? Did I miss any important issues that affect your choice of a language? Let me know in the comments!