The normal phases of a development project are requirements specification, logical design, detailed system design, implementation, final testing, deployment, and post-deployment maintenance and enhancement. Different methodologies may call these phases by different names, but they are always present. Each phase has its own products, which may be documents, code, or test results.
Sometimes in large projects the requirements phase is also separated into a userview phase, producing use cases or their equivalent, and a requirements specification phase, in which the requirements embedded in the use cases are recast as a features list. The main justification for doing this is that the features list embodies a checklist which can be used as a basis for test plan development and acceptance testing. Also, if a domain team produces the use cases, and a separate development team produces the requirements list, it is a way of forcing the developers to digest and understand the system requirements, by expressing them in their own terms.
A logical design partitions the system into conceptual components and specifies their behavior. It is important that as much information about the problem domain be reflected, and that minimal attention be paid to considerations having to do with performance, platform, or technology choices, unless these things are constants and known ahead of time, or are key choices that affect the functional capabilities. The reason is that this postponement allows choices of platform and technology to be deferred and left for implementation experts. The important goal of the logical design phase is to synergize the knowledge of application experts and implementation experts to produce a logical model of the system which could be implemented and would work, but perhaps not optimally. If the system has transactional behavior, transaction partitioning should be addressed in a logical sense (what are the transactions), but not the implementation (e.g. whether DBMS locking is to be used, or implemented with an optimistic policy or checkout). This does not mean that no thought should be given to such issues; in fact, judgment about the likely technical challenges of the alternative logical designs is crucial to coming up with a design that can be built within the project’s budget. Pinning down specific implementations is probably premature, however, since at this point a prototype has not even been built, and regardless the focus should be on making sure all the application’s functionality is addressed. A prototype should be developed during the logical design phase if possible. If there are new technologies involved—which is almost inevitable nowadays— what are their limitations? Do they perform as advertised? What surprises do they have in store? Scale prototyping and testing should also be performed in an investigatory manner during this stage. Note that bugs such as memory leaks in key third-party components may not show up until the system is tested at scale. The detailed design phase modifies the logical design and produces a final detailed design, which includes technology choices, specifies a system architecture, meets all system goals for performance, and still has all of the application functionality and behavior specified in the logical design. If a database is a component of the system, the schema that results from the detailed design may be radically different in key places from the one developed in the logical design phase, although an effort should be made to use identical terminology and not change things that do not need to be changed. The detailed design process should document all design decisions that require schema changes, or in general any changes to the logical design, and the reasons for the change. The project manager’s challenge will be to again disseminate understanding of the new design, which is replacing a logical design that had achieved credibility and consensus. This is the reason why all changes need to be well documented, so there is a clear migration, and the changes do not seem radical or arbitrary.
If a features list approach is used, it is easy to separate the project into builds, and make the detailed design and implementation phases of each build iterative. The systems’s features can be analyzed for dependencies and resource requirements, and assigned to project builds based on these dependencies, critical path, and priority. The minimum set of features for a testable bootstrap system can then be determined. For each build, additional features are added, and all tests are rerun, resulting in a working system after each build with increasing functionality and reliability. During each build, a detailed design of each feature can be performed, identifying the packages and classes affected, and with roughcut and then detailed updates to the specifications being produced, possibly in an iterative manner, and finally actual implementation in code. I have seen this technique work extremely successfully on many compiler and other projects with which I have been involved, and it is directly applicable to all kinds of systems. Once a detailed design for a build is agreed upon, the implementation phase should make very few changes to the system design, although some changes are inevitable. It is critical for maintainability that all changes be incorporated back into the design specifications. Otherwise, the value of the system design will be lost as soon as the system is released, and the only design documentation will be the code. A system documented only by its code is very hard for management to understand and upgrade, outsource, or disseminate. A Java-specific reason to incorporate changes back into specifications is that JDK 1.2 introduces the concept of package versioning. A package is viewed as a fieldreplaceable unit, and besides its name has two identifying pieces of information associated with it: its specification version and its implementation version. Two versions of a package that have the same specification version are implemented according to the same specifications, and should therefore be field-replaceable; the only difference between them should be that one has bug fixes which perhaps the other does not. A user might choose one implementation version over another if the user has instituted workarounds for certain known bugs; otherwise, the latest implementation version should be the most desired one. You can see that in order for this methodology to work, there must exist a well-defined set of specifi- cations for every package, and those specifications should have a version number associated with them.
Some methodologies view final QA testing as a separate phase of its own. This is a legitimate way of looking at final testing. However, developers are still busy during this period. They are not adding new functionality; instead, they are responding to bug reports from the QA group. The workflow is not any different, and all feedback mechanisms for changes and notification must still be in place. It is not clear, then, if distinguishing between development and final testing is of much value, except to clearly mark a cutoff point for adding new features and begin testing the packaging and deployment system. The QA group will likely make a “frozen” copy of the project code and test it in complete isolation, but testing of “frozen” code in this way still does not obviate feedback to the developers to subsequently fix reported problems. In fact, generating frozen releases is part of the normal build process, even though it may receive increased emphasis in the final build. Throughout all these phases, continuity is essential. A project that assigns domain analysis tasks to analysts and then reassigns those analysts during the implementation phase is operating with a severe handicap, if not doomed to failure. Domain expertise must remain within the project throughout its lifecycle. The dilemma is that once up-front analysis is complete, the analysts have less work, and their role becomes more passive. Often this cannot be justified, and these people are valuable to the business and are needed elsewhere. A solution that often works well is to keep a few domain experts assigned full time, and give them the permanent role of facilitator. In this capacity, they perform domain analysis, and execute all change requests to requirements specifications. They also develop user-oriented test plans, and construct system documentation. Their role therefore remains an active one, and their knowledge about the application, and contacts within the organization, can still be tapped when questions arise during development.
Extract from "Advanced Java Development for Enterprise Application" written by Clifford J. Berg Published by Prentice Hall PTR New Jersey 1998