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

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

From the Publisher:
Designing application and middleware software to run in concurrent and networked environments is a significant challenge to software developers The patterns catalogued in this second volume of Pattern-Oriented Software Architectures (POSA) form the basis of a pattern language that addresses issues associated with concurrency and networking
The book presents 17 interrelated patterns ranging from idioms through architectural designs They cover core elements of building concurrent and network systems: service access and configuration, event handling, synchronization,
and concurrency All patterns present extensive examples and known uses in multiple programming languages, including C++, C, and Java
The book can be used to tackle specific software development problems or read from cover to cover to provide a fundamental understanding of the best practices for constructing concurrent and networked applications and middleware
About the Authors
This book has been written by the award winning team responsible for the first POSA volume "A System of Patterns", joined in this volume by Douglas C Schmidt from University of California, Irvine (UCI), USA
Visit our Web Page

/pdf/pattern-oriented-software-architecture-patterns-for-53algdjkkg.pdf

Pattern-Oriented Software Architecture, Patterns for Concurrent and Networked Objects

Self-adaptation is typically realized using a control loop. One prominent approach for organizing a control loop in self-adaptive systems is by means of four components that are responsible for the primary functions of self-adaptation: Monitor, Analyze, Plan, and Execute, together forming a MAPE loop. When systems are large, complex, and heterogeneous, a single MAPE loop may not be sufficient for managing all adaptation in a system, so multiple MAPE loops may be introduced. In self-adaptive systems with multiple MAPE loops, decisions about how to decentralize each of the MAPE functions must be made. These decisions involve how and whether the corresponding functions from multiple loops are to be coordinated (e.g., planning components coordinating to prepare a plan for an adaptation). To foster comprehension of self-adaptive systems with multiple MAPE loops and support reuse of known solutions, it is crucial that we document common design approaches for engineers. As such systematic knowledge is currently lacking, it is timely to reflect on these systems to: (a) consolidate the knowledge in this area, and (b) to develop a systematic approach for describing different types of control in self-adaptive systems. We contribute with a simple notation for describing interacting MAPE loops, which we believe helps in achieving (b), and we use this notation to describe a number of existing patterns of interacting MAPE loops, to begin to fulfill (a). From our study, we outline numerous remaining research challenges in this area.

https://homepage.lnu.se/staff/daweaa/papers/2012SefSAS.pdf

On Patterns for Decentralized Control in Self-Adaptive Systems

This article presents a critical review of patterns and pattern languages in human-computer interaction (HCI). In recent years, patterns and pattern languages have received considerable attention in HCI for their potential as a means for developing and communicating information and knowledge to support good design. This review examines the background to patterns and pattern languages in HCI, and seeks to locate pattern languages in relation to other approaches to interaction design. The review explores four key issues: What is a pattern? What is a pattern language? How are patterns and pattern languages used? and How are values reflected in the pattern-based approach to design? Following on from the review, a future research agenda is proposed for patterns and pattern languages in HCI.

/pdf/pattern-languages-in-hci-a-critical-review-543xcv44mj.pdf

Pattern Languages in HCI: A Critical Review

Providing a guide to the best practices in key areas of distributed computing, this book describes a single pattern language that links many patterns relevant to distributed computing.

Pattern-Oriented Software Architecture, a Pattern Language for Distributed Computing

Pattern Oriented Software Architecture: On Patterns and Pattern Languages (Wiley Software Patterns Series)

Foreword. About This Book. About The Authors. Guide To The Reader. PART I. SOME CONCEPTS. 1. On Patterns and Pattern Languages. 1.1 Patterns Introduced. 1.2 Inside Patterns. 1.3 In Between Patterns. 1.4 Into Pattern Languages. 1.5 Patterns Connected. 2. On Distributed Systems. 2.1 Benefits of Distribution. 2.2 Challenges of Distribution. 2.3 Technologies for Supporting Distribution. 2.4 Limitations with Middleware. 3. On the Pattern Language. 3.1 Intent, Scope, and Audience. 3.2 Origins and Genesis. 3.3 Structure and Content. 3.4 Presentation. 3.5 Practical Use. PART. II A STORY. 4. Warehouse Management Process Control. 4.1 System Scope. 4.2 Warehouse Management Process Control. 5. Base-line Architecture. 5.1 Architecture Context. 5.2 Partitioning the Big Ball of Mud. 5.3 Decomposing the Layers. 5.4 Accessing Domain Object Functionality. 5.5 Bridging the Network. 5.6 Separating User Interfaces. 5.7 Distributing Functionality. 5.8 Supporting Concurrent Domain Object Access. 5.9 Achieving Scalable Concurrency. 5.10 Crossing the Object-Oriented/Relational Divide. 5.11 Configuring Domain Objects at Run-Time. 5.12 Base-line Architecture Summary. 6. Communication Middleware. 6.1 A Middleware Architecture for Distributed Systems. 6.2 Structuring the Internal Design of the Middleware. 6.3 Encapsulating Low-level System Mechanisms. 6.4 Demultiplexing ORB Core Events. 6.5 Managing ORB Connections. 6.6 Enhancing ORB Scalability. 6.7 Implementing a Synchronized Request Queue. 6.8 Interchangeable Internal ORB Mechanisms. 6.9 Consolidating ORB Strategies. 6.10 Dynamic Configuration of ORBs. 6.11 Communication Middleware Summary. 7. Warehouse Topology. 7.1 Warehouse Topology Base-line. 7.2 Representing Hierarchical Storage. 7.3 Navigating the Storage Hierarchy. 7.4 Modeling Storage Properties. 7.5 Varying Storage Behavior. 7.6 Realizing Global Functionality. 7.7 Traversing the Warehouse Topology. 7.8 Supporting Control Flow Extensions. 7.9 Connecting to the Database. 7.10 Maintaining In-Memory Storage Data. 7.11 Configuring the Warehouse Topology. 7.12 Detailing the Explicit Interface. 7.13 Warehouse Topology Summary. 8. The Story Behind The Pattern Story. PART III. THE LANGUAGE. 9. From Mud To Structure. Domain Model . Layers . Model-View-Controller . Presentation-Abstraction-Control. Microkernel . Reflection . Pipes and Filters . Shared Repository . Blackboard. Domain Object . 10. Distribution Infrastructure. Messaging . Message Channel . Message Endpoint . Message Translator . Message Router . Publisher-Subscriber . Broker . Client Proxy . Requestor . Invoker . Client Request Handler . Server Request Handler . 11. Event Demultiplexing and Dispatching. Reactor . Proactor. Acceptor-Connector . Asynchronous Completion Token . 12. Interface Partitioning. Explicit Interface . Extension Interface . Introspective Interface . Dynamic Invocation Interface . Proxy . Business Delegate . Facade . Combined Method . Iterator . Enumeration Method . Batch Method . 13. Component Partitioning. Encapsulated Implementation . Whole-Part . Composite . Master-Slave . Half-Object plus Protocol . Replicated Component Group . 14. Application Control. Page Controller . Front Controller . Application Controller . Command Processor . Template View . Transform View . Firewall Proxy . Authorization . 15. Concurrency. Half-Sync/Half-Async . Leader/Followers . Active Object . Monitor Object . 16. Synchronization. Guarded Suspension . Future . Thread-Safe Interface . Double-Checked Locking. Strategized Locking . Scoped Locking . Thread-Specific Storage. Copied Value . Immutable Value . 17. Object Interaction. Observer . Double Dispatch . Mediator . Command . Memento . Context Object . Data Transfer Object . Message . 18. Adaptation and Extension. Bridge . Object Adapter . Chain of Responsibility . Interpreter. Interceptor . Visitor . Decorator. Execute-Around Object . Template Method . Strategy . Null Object . Wrapper Facade . Declarative Component Configuration . 19. Modal Behavior. Objects for States . Methods for States . Collections for States . 20. Resource Management. Container . Component Configurator . Object Manager . Lookup . Virtual Proxy . Lifecycle Callback . Task Coordinator . Resource Pool . Resource Cache . Lazy Acquisition . Eager Acquisition . Partial Acquisition . Activator . Evictor . Leasing . Automated Garbage Collection . Counting Handle . Abstract Factory . Builder . Factory Method . Disposal Method . 21. Database Access. Database Access Layer . Data Mapper . Row Data Gateway . Table Data Gateway . Active Record. 22. A Departing Thought. Glossary. References. Index of Patterns. Index of Names. Index.

A pattern language for distributed computing

For more than a decade, patterns have influenced how software architects and developers create computing systems. Design-focused patterns provide a vocabulary for expressing architectural visions and clear, concise representative designs and detailed implementations. Presenting software pieces in terms of their constituent patterns also lets developers communicate more effectively, with greater conciseness and less ambiguity. Software patterns influence how developers design and implement computing systems. This paper examine the software patterns' past, present, and future trends, which can help developers improve their projects.

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Past, Present, and Future Trends in Software Patterns

The skill of writing is to create a context in which other people can think.

Kevlin Henney

Papers

Pattern-Oriented Software Architecture, a Pattern Language for Distributed Computing

Pattern Oriented Software Architecture: On Patterns and Pattern Languages (Wiley Software Patterns Series)

A pattern language for distributed computing

Past, Present, and Future Trends in Software Patterns

Context Encapsulation - Three Stories, a Language, and Some Sequences.