Monomorphic

The Gregorian calendar has been in use since 1582. Among its features is a moderately complicated rule for leap years: if n mod 4 is 0, then n is a leap year. However, if n mod 100 is 0, then n is not a leap year, unless n is a multiple of 400.

In addition, we live in a world with timezones and regional differences in when countries go on and off daylight savings time, if they have such a system. As yet another example of Japanese rationality, Japan does not have a DST system.

Implementing date and time computations correctly can be very hard for computer programmers and is invariably a source of many hidden bugs that may take a long time to discover. Yesterday, a large amount of Sony’s Playstation 3 game consoles stopped working normally.  This was later fixed. There was speculation the error was due to incorrect leap year handling. It wouldn’t be the first time this occurred if this was indeed the reason.

In a software company where I used to work, there would usually be massive troubles every time some country went on or off daylight savings time, or any other time calculation hit a sensitive spot. I’m fairly sure that the world’s software systems, including government, finance, insurance, health care, suffer untold billions of damage every year due to the complexity of the system. Maybe we should simplify it.

I suggest having “years” with 365 x 4 + 1 = 1461 days instead of the usual year for starters. This would move the leap year problem ahead until year 2100, when the next special rule comes in. By that time, software engineering technology should have improved enough that this should no longer be an issue, I hope. If not, we can invent another system by then. Let’s also scrap all daylight savings time everywhere. It’s easy to do and the savings would be huge.

Scala is a little wonderland sprinkled with useful things you can mix and match as you like to improve your coding experience while staying on the Java platform. The Option classes, the structural case matching, the compact declarations, lazy evaluation… the list goes on. But at the heart of it is the decision to mix freely the functional and imperative programming styles.

How does this work in practice?

• Statements can have side effects, like in Java
• The final statement evaluated in a function is its return value by default
• Every statement evaluates to a value, even control flow statements like if… else, unlike in Java

The bottom line is that some problems call for a functional programming style, and others for an imperative one. Scala doesn’t force you into a mold, it just gives you what you need to express what you’d like to express. This can lead to very compact code. Here’s a function that recursively finds all files ending in .java starting in a given directory. The File class here is the standard Java java.io.File!

Remember, the last expression evaluated is the return value.

 def findJavaFiles(dir: File): List[File] = {
    val files = dir.listFiles()
    val javaFiles = files.filter({_.getName.endsWith(".java")})
    val dirs = files.filter({_.isDirectory})
    javaFiles.toList ++ dirs.flatMap{findJavaFiles(_)}
  }

But we can write it even more compactly at the expense of some clarity:

 def findJavaFiles(dir: File) = {
    val files = dir.listFiles()
    files.filter(_.getName.endsWith(".java")).toList ++
 files.filter(_.isDirectory).flatMap{findJavaFiles(_)}
  }

Now write this function in Java and see how many lines you end up with.