Aspect] is a simple and practical aspect-oriented extension to Java With just a few new constructs, AspectJ provides support for modular implementation of a range of crosscutting concerns. In AspectJ's dynamic join point model, join points are well-defined points in the execution of the program; pointcuts are collections of join points; advice are special method-like constructs that can be attached to pointcuts; and aspects are modular units of crosscutting implementation, comprising pointcuts, advice, and ordinary Java member declarations. AspectJ code is compiled into standard Java bytecode. Simple extensions to existing Java development environments make it possible to browse the crosscutting structure of aspects in the same kind of way as one browses the inheritance structure of classes. Several examples show that AspectJ is powerful, and that programs written using it are easy to understand.

An overview of AspectJ

A wide variety of media can be used in learning, including distance learning, such as print, lectures, conference sections, tutors, pictures, video, sound, and computers. Any one instance of distance learning will make choices among these media, perhaps using several.

Multimedia in Learning

From the Book:
“Clean code that works” is Ron Jeffries’ pithy phrase. The goal is clean code that works, and for a whole bunch of reasons:
Clean code that works is a predictable way to develop. You know when you are finished, without having to worry about a long bug trail.Clean code that works gives you a chance to learn all the lessons that the code has to teach you. If you only ever slap together the first thing you think of, you never have time to think of a second, better, thing. Clean code that works improves the lives of users of our software.Clean code that works lets your teammates count on you, and you on them.Writing clean code that works feels good.But how do you get to clean code that works? Many forces drive you away from clean code, and even code that works. Without taking too much counsel of our fears, here’s what we do—drive development with automated tests, a style of development called “Test-Driven Development” (TDD for short). 
In Test-Driven Development, you:
Write new code only if you first have a failing automated test.Eliminate duplication.

Two simple rules, but they generate complex individual and group behavior. Some of the technical implications are:You must design organically, with running code providing feedback between decisionsYou must write your own tests, since you can’t wait twenty times a day for someone else to write a testYour development environment must provide rapid response to small changesYour designs must consist of many highly cohesive, loosely coupled components, just to make testing easy

The two rules imply an order to the tasks ofprogramming:
1. Red—write a little test that doesn’t work, perhaps doesn’t even compile at first
2. Green—make the test work quickly, committing whatever sins necessary in the process
3. Refactor—eliminate all the duplication created in just getting the test to work


Red/green/refactor. The TDD’s mantra.

Assuming for the moment that such a style is possible, it might be possible to dramatically reduce the defect density of code and make the subject of work crystal clear to all involved. If so, writing only code demanded by failing tests also has social implications:
If the defect density can be reduced enough, QA can shift from reactive to pro-active workIf the number of nasty surprises can be reduced enough, project managers can estimate accurately enough to involve real customers in daily developmentIf the topics of technical conversations can be made clear enough, programmers can work in minute-by-minute collaboration instead of daily or weekly collaborationAgain, if the defect density can be reduced enough, we can have shippable software with new functionality every day, leading to new business relationships with customers


So, the concept is simple, but what’s my motivation? Why would a programmer take on the additional work of writing automated tests? Why would a programmer work in tiny little steps when their mind is capable of great soaring swoops of design? Courage.
Courage
Test-driven development is a way of managing fear during programming. I don’t mean fear in a bad way, pow widdle prwogwammew needs a pacifiew, but fear in the legitimate, this-is-a-hard-problem-and-I-can’t-see-the-end-from-the-beginning sense. If pain is nature’s way of saying “Stop!”, fear is nature’s way of saying “Be careful.” Being careful is good, but fear has a host of other effects:
Makes you tentativeMakes you want to communicate lessMakes you shy from feedbackMakes you grumpy

None of these effects are helpful when programming, especially when programming something hard. So, how can you face a difficult situation and:
Instead of being tentative, begin learning concretely as quickly as possible.Instead of clamming up, communicate more clearly.Instead of avoiding feedback, search out helpful, concrete feedback.(You’ll have to work on grumpiness on your own.) 

Imagine programming as turning a crank to pull a bucket of water from a well. When the bucket is small, a free-spinning crank is fine. When the bucket is big and full of water, you’re going to get tired before the bucket is all the way up. You need a ratchet mechanism to enable you to rest between bouts of cranking. The heavier the bucket, the closer the teeth need to be on the ratchet.

The tests in test-driven development are the teeth of the ratchet. Once you get one test working, you know it is working, now and forever. You are one step closer to having everything working than you were when the test was broken. Now get the next one working, and the next, and the next. By analogy, the tougher the programming problem, the less ground should be covered by each test.

Readers of Extreme Programming Explained will notice a difference in tone between XP and TDD. TDD isn’t an absolute like Extreme Programming. XP says, “Here are things you must be able to do to be prepared to evolve further.” TDD is a little fuzzier. TDD is an awareness of the gap between decision and feedback during programming, and techniques to control that gap. “What if I do a paper design for a week, then test-drive the code? Is that TDD?” Sure, it’s TDD. You were aware of the gap between decision and feedback and you controlled the gap deliberately.

That said, most people who learn TDD find their programming practice changed for good. “Test Infected” is the phrase Erich Gamma coined to describe this shift. You might find yourself writing more tests earlier, and working in smaller steps than you ever dreamed would be sensible. On the other hand, some programmers learn TDD and go back to their earlier practices, reserving TDD for special occasions when ordinary programming isn’t making progress.

There are certainly programming tasks that can’t be driven solely by tests (or at least, not yet). Security software and concurrency, for example, are two topics where TDD is not sufficient to mechanically demonstrate that the goals of the software have been met. Security relies on essentially defect-free code, true, but also on human judgement about the methods used to secure the software. Subtle concurrency problems can’t be reliably duplicated by running the code.

Once you are finished reading this book, you should be ready to:
Start simplyWrite automated testsRefactor to add design decisions one at a time

This book is organized into three sections.
An example of writing typical model code using TDD. The example is one I got from Ward Cunningham years ago, and have used many times since, multi-currency arithmetic. In it you will learn to write tests before code and grow a design organically.An example of testing more complicated logic, including reflection and exceptions, by developing a framework for automated testing. This example also serves to introduce you to the xUnit architecture that is at the heart of many programmer-oriented testing tools. In the second example you will learn to work in even smaller steps than in the first example, including the kind of self-referential hooha beloved of computer scientists.Patterns for TDD. Included are patterns for the deciding what tests to write, how to write tests using xUnit, and a greatest hits selection of the design patterns and refactorings used in the examples.

I wrote the examples imagining a pair programming session. If you like looking at the map before wandering around, you may want to go straight to the patterns in Section 3 and use the examples as illustrations. If you prefer just wandering around and then looking at the map to see where you’ve been, try reading the examples through and refering to the patterns when you want more detail about a technique, then using the patterns as a reference.

Several reviewers have commented they got the most out of the examples when they started up a programming environment and entered the code and ran the tests as they read.

A note about the examples. Both examples, multi-currency calculation and a testing framework, appear simple. There are (and I have seen) complicated, ugly, messy ways of solving the same problems. I could have chosen one of those complicated, ugly, messy solutions to give the book an air of “reality.” However, my goal, and I hope your goal, is to write clean code that works. Before teeing off on the examples as being too simple, spend 15 seconds imagining a programming world in which all code was this clear and direct, where there were no complicated solutions, only apparently complicated problems begging for careful thought. TDD is a practice that can help you lead yourself to exactly that careful thought.

Test Driven Development: By Example

[서평]「Component Software」 - Beyond Object-Oriented Programming -

Kaizen: The key to Japan‚s competitive success

In component-based software development, it is necessary to measure the reusability of components in order to realize the reuse of components effectively. There are some product metrics for measuring the reusability of object-oriented software. However, in application development with reuse, it is difficult to use conventional metrics because the source codes of components cannot be obtained, and these metrics require analysis of source codes. We propose a metrics suite for measuring the reusability of such black-box components based on limited information that can be obtained from the outside of components without any source codes. We define five metrics for measuring a component's understandability, adaptability, and portability, with confidence intervals that were set by statistical analysis of a number of JavaBeans components. Moreover, we provide a reusability metric by combining these metrics based on a reusability model. As a result of evaluation experiments, it is found that our metrics can effectively identify black-box components with high reusability.

/pdf/a-metrics-suite-for-measuring-reusability-of-software-txkxi8f71m.pdf

A metrics suite for measuring reusability of software components

Social insects perform complex tasks without top-down-style control, by sensing and depositing chemical markers called "pheromone". We have examined applications of this pheromone paradigm towards realizing intelligent transportation systems (ITS). Many of the current traffic management approaches require central processing with the usual risks of overload, bottlenecks and delay. Our work points towards a more decentralized approach that may overcome those risks. We use new category of the ITS infrastructure called the probe-car system. The probe-car system is an emerging data collection method, in which a number of vehicles are used as moving sensors to detect actual traffic situations. In this paper, a car is regarded as a social insect that deposits multi-semantics of (digital) pheromone on the basis of sensed traffic information. We have developed a basic model for predicting traffic congestion in the immediate future using pheromone. In the course of our experimentation, we have identified the need to properly tune the model to achieve acceptable performance. Therefore, we refined the model for practical use. We evaluate our method using real-world traffic data and results indicate applicability to prediction. Furthermore, we describe the practical implications of this method in the real world.

Performance of pheromone model for predicting traffic congestion

Static analysis tools such as bug pattern tools are useful to detect bugs early in software development. However, existing tools sometimes yield so many warnings that developers tend to ignore such warnings. To deal with this problem, we propose a gamified tool for motivating developers to remove such warnings. Our tool employs the gamification technique that calculates points by counting removed warnings with respect to each developer and each team. The points give developers feedback and urge them to compete with each other. We confirmed that developers removed about 150% warnings with our tool in comparison with the case where they did not use our tool through an experiment.

A Gamified Tool for Motivating Developers to Remove Warnings of Bug Pattern Tools

A technique for automatic component extraction from object-oriented programs by refactoring

Patterns combine experience and good practices to develop basic models that can be used for new designs. Security patterns join the extensive knowledge accumulated about security with the structure provided by patterns to provide guidelines for secure system design and evaluation. In addition to their value for new system design, security patterns are useful to evaluate existing systems. They are also useful to compare security standards and to verify that products comply with some standard. A variety of security patterns has been developed for the construction of secure systems and catalogs of them are appearing. However, catalogs of patterns are not enough because the designer does not know when and where to apply them, especially in a large complex system. We discuss here several ways to classify patterns. We show a way to use these classifications through pattern diagrams where a designer can navigate to perform her pattern selection.

Yoshiaki Fukazawa

Papers

A metrics suite for measuring reusability of software components

Performance of pheromone model for predicting traffic congestion

A Gamified Tool for Motivating Developers to Remove Warnings of Bug Pattern Tools

A technique for automatic component extraction from object-oriented programs by refactoring

Classifying security patterns