New in Guava 12: TypeToken, a better Class or TypeLiteral

I'm slow to read up on the Guava 12 release — it came out in April.

Among the changes is this gem: TypeToken.

Guava provides TypeToken, which uses reflection-based tricks to allow you to manipulate and query generic types, even at runtime. Think of a TypeToken as a way of creating, manipulating, and querying Type (and, implicitly Class) objects in a way that respects generics.

Note to Guice users: TypeToken is similar to Guice's TypeLiteral class, but with one important difference: it supports non-reified types such as T, List<T> or even List<? extends Number>; while TypeLiteral does not. TypeToken is also serializable and offers numerous additional utility methods.

I look forward to giving this a spin next time the need arises.

Emacs, your makefile friend

After long hiatus I find myself against writing (editing) makefiles. Using Emacs compile command makes all the difference. Emacs runs make in another process, sending output to an independent buffer (window, tab, panel) default named *compilation*.

In the *compilation* buffer, Emacs colorizes make's output. This greatly aids comprehension. As icing, Emacs recognizes output patterns from dozens of popular tools, and highlights them as information, warning or error as appropriate.

Emacs simplifies navigation with hyperlinking. The TAB key in *compilation* steps through warnings and errors. Magic.

As a bonus, I looked up common patterns stored in the Emacs variable, compilation-error-regexp-alist. The info page for this variable includes a link to "compilation.txt", a complete list of sample output for each supported tool. It was trivial for me to find right at the top:

* GNU style

symbol: gnu

foo.c:8: message
../foo.c:8: W: message
/tmp/foo.c:8: warning: message

That last line was my ticket. I arrange to echo similar text when something needs attention in my shell command, but without failing the entire build. I take care to break the output into separate shell echo commands so Emacs does not match prematurely when make displays executed commands. I could have prefixed my shell line with "@" (ampersand) to suppress make from printing it, but coding standards here discourage that.

a-file:
        if $(some_bad_condition_set_in_makefile) ; then \
        echo -n $@ ; \
        echo :1: warning: $@ is foobar. >&2 ; fi

I emulate the output of one of the tools Emacs groks, and I get the same magical colorizing and hyperlinking with my output:

making in /some/path
if true ; then \
 echo -n a-file ; \
 echo :1: Warning: a-file is foobar. >&2 ; fi
a-file:1: warning: a-file is foobar.

In *compilation* the TAB key jumps me to the start of a-file when it exists.

The generic getter idiom in Java

In our code base we represent Google protobuf messages as rooted trees, informally just trees. Nodes are necessarily heterogeneous: some are value nodes—strings, numbers, etc.—, some are roots of more trees, that is, node collections.

I recently replaced code like this:

StringNode childA = (StringNode) parent.get("child A's name");
Int32Node childB = (Int32Node) parent.get("child B's name");

With code like this:

StringNode childA = parent.get("child A's name");
Int32Node childB = parent.get("child B's name");

How did I do this? I changed the definition of "get" from:

public Node get(final String name) {
    // Clever implementation
}

To:

public <N extends Node> N get(final String name) {
    // Same implementation with some "(N)" casts
}

When the compiler can infer the return type of "get", it will, saving you writing now and reading later. In those cases where it cannot infer the type, you still help:

final String valueA = (String) ((StringNode) parent).get("child A's name").getValue();
final Integer valueB = (Integer) ((Int32Node) parent).get("child B's name").getValue();

Becomes:

final String valueA = parent.<StringNode>get("child A's name").getValue();
final Integer valueB = parent.<Int32Node>get("child B's name").getValue();

There is still a type cast, but you spell it differently using the generics system. Note "getValue" uses the same idiom as "get"; the return type can be inferred, no extra writing needed.

I'm going to call this pattern the Generic Getter Idiom until I find a good reference.

Related: Crossing generics and covariant returns

The view of things to come Java

Lukas Eder notes the possibility of collection and structural literals in Java. A man can dream, can't he? Happily, this dream is built on more than wisps of fancy, just. I don't hold my breath.

Krumins does Bash one-liners

Beginning of a series on Bash one-liners from Peter Krumins. If it's from Peter, you know it'll be good.

Picture GCC mangling

Matt Godbolt posts GCC Explorer - an interactive take on compilation.

One of the things I spend a fair amount of time doing at work is compiling my C/C++ code and looking at the disassembly output. Call me old-fashioned, but I think sometimes the only way to really grok your code is to see what the processor will actually execute. Particularly with some of the newer features of C++11 — lambdas, move constructors, threading primitives etc — it’s nice to be able to see how your elegant code becomes beautiful (and maybe even fairly optimal) machine code.

I’d managed to get my pipeline for taking small snippets of C code, building them with GCC, de-mangling the output, musing on the assembly, tweaking the input and then repeating over and over again.

See github for sources.

Uncle Bob on No DB

Another beautiful rant from Uncle Bob:

Here’s what an application should look like. The use cases should be the highest level and most visible architectural entities. The use cases are at the center. Always! Databases and frameworks are details! You don’t have to decide upon them up front. You can push them off until later, once you’ve got all the use cases and business rules figured out, written, and tested.

8th light must be something else.

Is Continuous Delivery agile?

Keif Morris thoughtfully compares/contrasts Agile to Continuous Delivery (CD).

Of course the answer to the question posed in the post title is Yes, Continuous Delivery is agile. Very agile, in fact.

Keif raises several concerns traditional Agile has with Continuous Delivery. I admit to being from the old school, XP, and am a little nervous around CD. But I embrace its spirit.

With Agile leaving small release messes to clean up each iteration, or for Waterfall one giant mess to clean up in the release phase, is bad for the nerves too. At least CD picks up after itself in an ongoing basis.

As a daily Java programmer Maven makes a hash of this as Keif points out. But as with many things related to Maven, you gain a few pains and lose several others for net betterment. How does CD treat the snapshot ailment?

ESR on "C" portability across time

ESR posts on portability of "C" across time. Most times you port across machines and operating systems. "C" is rare in making straight-forward the task of porting from the past into the future.

sed is Turing complete

My command line tool is cooler than your command line tool. Thank you, Peteris Krumins, for linking. And don't forget his book.

UPDATE: A testament to my typing skills, the original title of this post was "sed is Turning complete".

Mythryl: Another great language introduction

Another great language introduction, this one for Mythryl:

Howdy! I’m Cynbe, lead Mythryl developer.

Why do I do it?

Let me tell you.

I spent the first four years of this millennium doing eighty-hour weeks at a Fortune 5 company in a division internally famous for producing more revenue per employee than the IRS.

I remember arriving home at three AM Christmas Day, sleeping thirty-six hours straight, and then driving right back to work.

It was a cool trip in its way, but over time the stress does get to you. By four years in, vomiting blood in the wee hours was starting to seem entirely normal.

It was time for a change.

By then I had written well over a million lines in C plus substantial amounts in other languages. I felt ready to take it to the next level.

“A language that doesn’t affect the
way you think about programming
is not worth knowing.”
—Alan Perlis

So I looked around to see what was new and improved. I’d learned APL, assembly, C, Fortran, Lisp, Pascal, Smalltalk, Snobol, SQL and so Forth in the 1970s, but after that there had been a long dry spell. C++, J, Java, Perl, Python, Ruby, sure, but they hardly catapult us into a new era of butterflies and rainbows. They did not expand my mind like Lisp and Smalltalk.

Happily, mostly-functional programming languages had just reached the Ready For Prime Time point.

My favorite was SML/NJ, from the nice folks who gave us the laser, the transistor, and Unix.

Unfortunately, it was research-grade code cloaked in academic jargon which hadn’t seen an end-user release that millennium.

Fortunately, I was looking for something to do.

So I set about hammering this magnificent raw material into a modern production quality open source software development platform.

To my mind Mythryl deftly combines C speed, Lisp power, and Ruby convenience with the critical new ingredients of Hindley-Milner typing, state of the art generics and just the right level of side effects.

I’m in love!

Real Options

Shane Hastie interviews Chris Matts and Olav Maassen on Real Options, an agile technique to improve IT decision making.

Do read it all. A taste:

InfoQ: Please can you briefly explain Real Options. 

Olav: Options have value, options expire, never commit early unless you know why.

Options are a way of looking at decision making. Financial options work in very narrow areas, in the financial marketplace they entail paying a fee to defer making a choice about purchasing a share or financial instrument until a later date. Our thinking about Real Options was inspired by financial options, but they are much broader in application.

Real Options are more to do with the psychology of how people make decisions than with the choices available to them. 

InfoQ: Please explain. 

Chris: People hate uncertainty, so much so that they would rather be wrong than uncertain. In a “rational preference” the hierarchy of decision making would be:

1. Have the right answer
2. Be uncertain about the answer
3. Have the wrong answer

The reality is we prefer to be wrong rather than be uncertain, so the hierarchy is:

1. Have the right answer
2. Have the wrong answer
3. Be uncertain about the answer

We can tell this because when people are faced with uncertainty, they would rather make any decision, even if it is the wrong one.

Generally people would rather have a definite wrong answer than be unsure about an answer.

Real Options is about understanding when to make a decision, rather than how to make decisions. By adding the “when” to the decision making process we remove the uncertainty and enable people to make better decisions.

Like financial options have a fixed contractual expiry date, real options have a conditional expiry date.

Jline moves forward

One of my favorite Java libraries, jline, released 2.6 recently. Among the goodies is support for ~/.inputrc. This is as close to readline as Java gets.

The science of cloud computing

The physics arXiv blog at MIT Technology Review posts The Hidden Risk of a Meltdown in the Cloud.

As with anytime you bet the farm on a technology, try to have a backup plan.

re: Romans, rubies and the D

Kajetan Rzepecki posts Romans, rubies and the D, a clever comparison of Ruby missing method look up and the compile-time equivalent in D. (It's short, please read.)

This is a clean example in favor of proper macros (not the "CPP" sort).

I've long been impressed by D. It makes up for many of the faults in C++, which impresses me less as time goes on. What is impressive about D? I appreciate that the first thing it says about itself is:

D is a systems programming language. Its focus is on combining the power and high performance of C and C++ with the programmer productivity of modern languages like Ruby and Python. Special attention is given to the needs of quality assurance, documentation, management, portability and reliability.

And that, therefore, this comes only second:

The D language is statically typed and compiles directly to machine code. It’s multiparadigm, supporting many programming styles: imperative, object oriented, and metaprogramming. It’s a member of the C syntax family, and its appearance is very similar to that of C++.

That says something good about taste in my book.

Showing test failure name for JUnit parameterized tests

A popular complaint against JUnit is lack of human-readable names for parameterized test cases. There are several solutions, this is mine.

/**
 * {@code ParameterizedTest} simplifies parametered JUnit tests by including a "case label" to
 * identify the failing branch.  (JUnit only provides an index).  The failure message format
 * becomes "descriptive string from JUnit: case label: assertion failure message".
 * <p/>
 * Fully preserves the stack trace of failing tests.
 * <p/>
 * Example: <pre>
 * public class MyTest {
 *     &#64;Parameters
 *     public static Collection<Object[]> parameters() {
 *         return ...; // See JUnit documentation for parameterized tests
 *     }
 *
 *     public MyTest(final String caseLabel, final X x, final Y y) {
 *         super(caseLabel);
 *         this.x = x;
 *         this.y = y;
 *     }
 *
 *     &#64;Test
 *     public void shouldWork() {
 *         // Body of test method ...
 *     }
 * }
 * </pre>
 * When {@code shouldWork()} fails the failure message is more meaningful, including the
 * {@link #caseLabel "case label"} in the JUnit error message.
 *
 * @author <a href="mailto:binkley@alumni.rice.edu">B. K. Oxley (binkley)</a>
 */
@RunWith(Parameterized.class)
public abstract class ParameterizedTest {
    private final String caseLabel;

    /**
     * The JUnit test rule (test extension) which fails bad parameterized cases but provides a
     * {@link #caseLabel case label} identifing the failed test branch.
     */
    @Rule
    public final TestRule parameterizedTestRule = new TestWatcher() {
        @Override
        protected void failed(final Throwable e, final Description description) {
            final AssertionError x = new AssertionError(
                    description.getDisplayName() + ": " + caseLabel + ": " + e.getMessage());
            x.setStackTrace(e.getStackTrace());
            throw x;
        }
    };

    /**
     * Constructs a new {@code ParameterizedTest} for the given <var>caseLabel</var>.
     *
     * @param caseLabel the case label, never missing
     */
    protected ParameterizedTest(@Nonnull final String caseLabel) {
        this.caseLabel = caseLabel;
    }
}

Testing thread affinity

Peter Lawrey posts on thread affinity with Java. This is a post full of numbers, good numbers. If you write low latency code in Java, this is for you.

More git: moving modules between repos

Not the coolest merge, EVER! but much more grokable, Greg Bayer provides Moving Files from one Git Repository to Another, Preserving History.

The problem: I want to move repo-A/module1 to repo-B/module1 while preserving history. Bayer to the rescue. Thanks, Greg!

How to introduce a new programming language

The Julia folks provide show the way to introduce a new programming language:

We are greedy: we want more.

We want a language that’s open source, with a liberal license. We want the speed of C with the dynamism of Ruby. We want a language that’s homoiconic, with true macros like Lisp, but with obvious, familiar mathematical notation like Matlab. We want something as usable for general programming as Python, as easy for statistics as R, as natural for string processing as Perl, as powerful for linear algebra as Matlab, as good at gluing programs together as the shell. Something that is dirt simple to learn, yet keeps the most serious hackers happy. We want it interactive and we want it compiled.

(Did we mention it should be as fast as C?)

Thanks to Michael J. Simoni for pointing out Julia. More here.

Losing malloc, gaining the world

At work we've dropped the malloc that comes with GCC in favor of tcmalloc from Google. Our creaking, monolithic C++ backend gains 10-20% performance, unsurprising given the history of malloc.

Concatenative Programming

Jon Purdy on concatenative programming, which I had never heard of before. Basically it is purer functional programming for those of you who think Haskell is too corporate. (Actually, I enjoyed the read.)

P.S. — A remark from a clever fellow, no slouch he: That made my head hurt and reminded me of, when I was a freshman, trying to do a few chapters of Abelson & Sussman on my HP 28S calculator, which had RPN and (I realized) first-class functions.. I miss RPN calculators.

Beating the PyPy drum

Laurie Tratt beats the PyPy drum in Fast Enough VMs in Fast Enough Time. Want to know more about VMs? Writing your own language or mini-language? Read on.

Here comes Kotlin

Here comes Kotlin and Guice! Thank you Alex Tkachman.

Type Theory for the Uninitiated

Kalani Thielen presents The Algebra of Data, and the Calculus of Mutation, or Type Theory for the Uninitiated. Fine calculus a bit soft, algebra a little dull, programming a walk in the park? Type theory is for you.