物件導向軟體之架構(Object-Oriented Software Construction)探討

An Introduction to MultiAgent Systems.

Criticism and the Growth of Knowledge. Edited by I. Lakatos and A. Musgrave. Pp. viii, 282. £3·50, paperback £1. 1970. (Cambridge University Press.)

Essentially a software system's utility is determined by both its functionality and its non-functional characteristics, such as usability, flexibility, performance, interoperability and security. Nonetheless, there has been a lop-sided emphasis in the functionality of the software, even though the functionality is not useful or usable without the necessary non-functional characteristics. In this chapter, we review the state of the art on the treatment of non-functional requirements (hereafter, NFRs), while providing some prospects for future directions.

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On Non-Functional Requirements in Software Engineering

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

Information systems of the future will have to perform well within ever-changing organizational enviromnents. Unfortunately, existing software development methodologies (object-oriented, structured or otherwise) have traditionally been inspired by programming concepts, not organizational ones, leading to a semantic gap between the software system and its operational enviromnent. To reduce this gap, we propose a software development methodology named Tropos which is founded on concepts used to model early requirements. Our proposal adopts the i organizational modeling framework, which offers the notions of actor, goal and (actor) dependency, and uses these as a foundation to model early and late requirements, architectural and detailed design. The paper outlines Tropos phases through an e-business example, and sketches a formal language which underlies the methodology and is intended to support formal analysis. The methodology seems to complement well proposals for agent-oriented programming platforms.

/pdf/towards-requirements-driven-information-systems-engineering-2pzoyjspx9.pdf

Towards requirements-driven information systems engineering: the Tropos project

Information systems of the future will have to better match their operational organizational environment. Unfortunately, development methodologies have traditionally been inspired by programming concepts, not organizational ones, leading to a semantic gap between the system and its environment. To reduce as much as possible this gap, this paper proposes a development methodology named Tropos which is founded on concepts used to model early requirements. Our proposal adopts the i* organizational modeling framework [18], which offers the notions of actor, goal and (actor) dependency, and uses these as a foundation to model early and late requirements, architectural and detailed design. The paper outlines Tropos phases through an e-business example. The methodology seems to complement well proposals for agent-oriented programming platforms.

/pdf/a-requirements-driven-development-methodology-4iwkpwmqof.pdf

A Requirements-Driven Development Methodology

A Multi-Agent System (hereafter MAS) is an organization of coordinated autonomous agents that interact in order to achieve common goals. Considering real world organizations as an metaphor, this paper proposes architectural styles for MAS which adopt concepts from organizational theories. The styles are modeled in i*/Tropos, using the notions of actor, goal and actor dependency and are intended to capture needs/wants, delegations and obligations. The proposed architectural styles are evaluated with respect to a set of software quality attributes, such as predictability and adaptability. In addition, we report on a comparative study of organizational and conventional software architectures using a mobile robot control example from the Software Engineering literature. The research reported here was conducted within the scope of the Tropos project, whose objective is to develop a comprehensive agent-oriented software development methodology.

http://www.isys.ucl.ac.be/descartes/download/posters/org-mas-ijcis.pdf

Multi-Agent Architectures as Organizational Structures

A Multi-Agent System (MAS) is an organization of coordinated autonomous agents that interact in order to achieve common goals. Considering real world organizations as an analogy, this paper proposes architectural styles for MAS which adopt concepts from organization theory and strategic alliances literature. The styles are intended to represent a macro-level architecture of a MAS, and they are modeled using the i* framework which offers the notions of actor, goal and actor dependency for modeling multi-agent settings. The styles are also specified as metaconcepts in the Telos modeling language. Moreover, each style is evaluated with respect to a set of software quality attributes, such as predictability and adaptability. The paper also explores the adoption of micro-level patterns proposed elsewhere in order to give a finer-grain description of a MAS architecture. These patterns define how goals assigned to actors participating in an organizational architecture will be fulfilled by agents. An e-business example illustrates both the styles and patterns proposed in this work. The research is being conducted within the context of Tropos, a comprehensive software development methodology for agent-oriented software.

Manuel Kolp

Papers

Towards requirements-driven information systems engineering: the Tropos project

A Requirements-Driven Development Methodology

Multi-Agent Architectures as Organizational Structures

A goal-based organizational perspective on multi-agent architectures

Multi-Agents Architectures as Organizational Structures