Introduction to scripting in Java, Part 2

Find out what else you need to know about scripting in this second half of the JavaWorld excerpt from Dejan Bosanac's Scripting in Java: Languages, Frameworks, and Patterns (Addison Wesley Professional, August 2007)

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Development Speed

I already mentioned dynamic languages lead to faster development processes. A few facts support this assertion.

For one, a statement in a system-programming language executes about five machine instructions. However, a statement in a scripting language executes hundreds or even thousands of instructions. Certainly, this increase is partially due to the presence of the interpreter, but more important is the fact that primitive operations in scripting languages have greater functionality. For example, operations for matching certain patterns in text with regular expressions are as easy to perform as multiplying two integers.

These more powerful statements and built-in data structures lead to a higher level of abstraction that language can provide, as well as much shorter code.

Of course, dynamic typing plays an important role here too. The need to define each variable explicitly with its type requires a lot of typing, and this is time consuming from a developer's perspective. This higher level of abstraction and dynamic typing allows developers to spend more time writing the actual business logic of the application than dealing with the language issues.

Another thing speeding up the scripting development process is the lack of a compile (and linking) phase. Compilation of large programs could be time consuming. Every change in a program written in a system-programming language requires a new compile/link process, which could slow down development a great deal. In scripting, on the other hand, immediately after the code is written or changed, it can be executed (interpreted), leaving more time for the developer to actually write the code.

As you can see, all the things that increase runtime performance, such as compilation and static typing, tend to slow down development and increase the amount of time needed to build the solution. That is why you hear scripting languages are more human oriented than machine oriented (which isn't the case with system-programming languages).

To emphasize this point further, here is a snippet from David Ascher's article titled "Dynamic Languages—ready for the next challenges, by design," which reflects the paradigm of scripting language design:

The driving forces for the creation of each major dynamic language centered on making tasks easier for people, with raw computer performance a secondary concern. As the language implementations have matured, they have enabled programmers to build very efficient software, but that was never their primary focus. Getting the job done fast is typically prioritized above getting the job done so that it runs faster. This approach makes sense when one considers that many programs are run only periodically, and take effectively no time to execute, but can take days, weeks, or months to write. When considering networked applications, where network latency or database accesses tend to be the bottlenecks, the folly of hyper-optimizing the execution time of the wrong parts of the program is even clearer. A notable consequence of this difference in priority is seen in the different types of competition among languages. While system languages compete like CPU manufacturers on performance measured by numeric benchmarks such as LINPACK, dynamic languages compete, less formally, on productivity arguments and, through an indirect measure of productivity, on how "fun" a language is. It is apparently widely believed that fun languages correspond to more productive programmers—a hypothesis that would be interesting to test.


Many proponents of the system-programming approach say dynamic typing introduces more bugs in programs because there is no type checking at compile time. From this point of view, it is always good to detect programming errors as soon as possible. This is certainly true, but as we discuss in a moment, static typing introduces some drawbacks, and programs written in dynamically typed languages could be as solid as programs written in purely statically typed environments. This way of thinking leads to the theory that dynamically typed languages are good for building prototypes quickly, but they are not robust enough for industrial-strength systems.

On the other side stand proponents of dynamic typing. From that point of view, type errors are just one source of bugs in an application, and programs free of type-error problems are not guaranteed to be free of bugs. Their attitude is static typing leads to code much longer and much harder to maintain. Also, static typing requires the developer to spend more of his time and energy working around the limitations of that kind of typing.

Another implication we can glean from this is the importance of testing. Because a successful compilation does not guarantee your program will behave correctly, appropriate testing must be done in both environments. Or as best-selling Java author Bruce Eckel wrote in his book Thinking in Java (Prentice Hall):

If it's not tested, it's broken.

Because dynamic typing allows you to implement functionality faster, more time remains for testing. Those fine-grained tests could include testing program behavior for type misuse.

Despite all the hype about type checking, type errors are not common in practice, and they are discovered quickly in the development process. Look at the most obvious example. With no types declared for method parameters, you could easily find yourself calling a method with the wrong order of parameters. But these kinds of errors are obvious and are detected immediately the next time the script is executed. It is highly unlikely this kind of error would make it to distribution if it was tested appropriately.

Another extreme point of view says even statically typed languages are not typed. To clarify this statement, look at the following Java code:

List list = new ArrayList();
list.add(new String("Hello"));
list.add(new Integer(77));

Iterator it = list.iterator();
while (it.hasNext()) {
    String item = (String);

This code snippet would be compiled with no errors, but at execution time, it would throw a java.lang.ClassCastException. This is a classic example of a runtime type error. So what is the problem?

The problem is objects lose their type information when they are going through more-generic structures. In Java, all objects in the container are of type java.lang.Object, and they must be converted to the appropriate type (class) as soon as they are released from the container. This is when inappropriate object casting could result in runtime type errors. Because many objects in the application are actually contained in a more-generic structure, this is not an irrelevant issue.

Of course, there is a workaround for this problem in statically typed languages. One solution recently introduced in Java is called generics. With generics, you would write the preceding example as follows:

List list<String> = new ArrayList<String>();
list.add(new String("Hello"));
list.add(new Integer(77));

Iterator<String> it = list.iterator();
while (it.hasNext()) {
    String item =;

This way, you are telling the compiler only String objects can be placed in this container. An attempt to add an Integer object would result in a compilation error. This is a solution to this problem, but like all workarounds, it is not a natural approach.

The fact that scripting programs are smaller and more readable by humans makes them more suitable for code review by a development team, which is one more way to ensure your application is correct. Guido van Rossum, the creator of the Python language, supported this view when he was asked in an interview whether he would fly an airplane controlled by software written in Python:

You'll never get all the bugs out. Making the code easier to read and write, and more transparent to the team of human readers who will review the source code, may be much more valuable than the narrow-focused type checking that some other compiler offers. There have been reported anecdotes about spacecraft or aircraft crashing because of type-related software bugs, where the compilers weren't enough to save you from the problems.

This discussion is intended just to emphasize one thing: Type errors are just one kind of bug in a program. Early type checking is a good thing but it is certainly not enough, so conducting appropriate quality assurance procedures (including unit testing) is the only way to build stable and robust systems.

Many huge projects written purely in Python prove the fact that modern scripting languages are ready for building large and stable applications.

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