Not all web applications require a full stack framework (like Grails, Rails, Spring MVC, etc).

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The question of how to test for exceptions comes up quite frequently. While there’s more than one way to skin a cat, so to speak, man, I’ve found that documenting intent is often more helpful in quickly conveying behavior.

Case in point, with the advent of JUnit 4’s expected attribute of the @Test annotation, it’s quite easy to concisely specify which exception a given test case should throw.

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easyb has been nominated as a 2008 Jolt award finalist, baby! I know I speak for the entire easyb team when I say we are truly honored to have been considered for such prestigious award.

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I’ve been asked on more than one occasion if easyb supports code coverage. The answer is a copasetic yes and here’s how (using Cobertura and Ant). Code coverage, regardless of your desired tool, essentially entails three steps, namely:

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Not long ago, I had the distinct pleasure of chatting with Sebastien Arbogast regarding OSGi for JavaWorld’s Java Technology Insider. In this hip fat-chewing session, Sebastien introduces the concepts behind OSGi and explains why its contribution to Java modularity is copasetic news for Java community.

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I recently had the pleasure of chatting with Rod Johnson for JavaWorld’s Java Technology Insider regarding all things Spring, baby.

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I had such a hip time at last year’s CodeMash that I can’t wait to attend this year’s bash; what’s more, I’ll be presenting a talk entitled “Executable documentation with easyb” (hopefully with my good fri

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JavaFX 1.0 made its debut a few days back amid high hopes and a sea of doubt — some in the Java community believe JavaFX could become “the application environment for the Java platform,” while others say Sun has made nothing but mistakes on the client side, and JavaFX is too little, too late.

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I have long admired highscalability.com for its focus on interesting techniques, libraries, and case studies all related to the hip art of scaling; indeed, this website has some super cool articles regarding YouTube, Amazon, and Google to name a few high profile websites that appear to have scaled quite copasetically.

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The software industry has a cyclic love-hate relationship with code metrics. At times, metrics appear to be quite helpful and at other times, doubt regarding their efficacy casts a short-lived shadow, which, once gone, the cycle starts over.  Because it’s my bag, baby, it appears that closing in on 2009, we’re entering a period of disco-induced code metrics love.

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Every once in a while the topic of code coverage surfaces, which invariably leads to a number of interesting views and comments. Recently, my friend Meera Subbarao mused about the subject by rhetorically questioning “Is Code Coverage Important?”

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Ranges in Groovy represent a collection of hip sequential values; as such, they facilitate looping in a concise manner. In truth, they function exactly like a for loop; however, they are significantly more terse. For example, the typical for loop in Java looks like this:

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I’m a big fan of writing as little code as possible and borrowing everything else.

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There are various statistics related to the average defect density (i.e. how many defects one can expect to find in a code base); suffice to say, the numbers point to unhip ranges like

20 to 30 bugs for every 1,000 lines of code

and even

100–250 defects per thousand lines of code

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The tangible disconnect between stakeholders who define requirements and developers who implement them has long plagued software development. In recent years, however, frameworks based on dynamic languages and domain-specific languages (hint– easyb!) are bridging the stakeholder-developer gap by making code read more like normal language.

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