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Figure 34-1 Programs can be divided into levels of abstraction. A good design will allow you to spend much of your time focusing on only the upper layers and ignoring the lower layers.
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Level 0: Operating System Operations and Machine Instructions
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If you re working in a high-level language, you don t have to worry about the lowest level your language takes care of it automatically. If you re working in a low-level language, you should try to create higher layers for yourself to work in, even though many programmers don t do that.
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34. Themes in Software Craftsmanship
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Level 1: Programming-Language Structures and Tools
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Programming-language structures are the language s primitive data types, control structures, and so on. Most common languages also provide additional libraries, access to operating system calls, and so on. Using these structures and tools comes naturally since you can t program without them. Many programmers never work above this level of abstraction, which makes their lives much harder than they need to be.
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Level 2: Low-Level Implementation Structures
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Low-level implementation structures are slightly higher-level structures than those provided by the language itself. They tend to be the operations and data types you learn about in college courses in algorithms and data types stacks, queues, linked lists, trees, indexed files, sequential files, sort algorithms, search algorithms, and so on. If your program consists entirely of code written at this level, you ll be awash in too much detail to win the battle against complexity.
Level 3: Low-Level Problem-Domain Terms
At this level, you have the primitives you need in order to work in terms of the problem domain. It s a glue layer between the computer-science structures below and the high-level problem-domain code above. To write code at this level, you need to figure out the vocabulary of the problem area and create building blocks you can use to work with the problem the program solves. In many applications, this will be the business objects layer or a services layer. Classes at this level provide the vocabulary and the building blocks. The classes might be too primitive to be used to solve the problem directly at this level, but they provide an Erector set that higher-level classes can use to build a solution to the problem.
Level 4: High-Level Problem-Domain Terms
This level provides the abstractive power to work with a problem on its own terms. Your code at this level should be somewhat readable by someone who s not a computer-science whiz perhaps even by your non-technical customer. Code at this level won t depend much on the specific features of your programming language because you ll have built your own set of tools to work with the problem. Consequently, at this level your code depends more on the tools you ve built for yourself at Level 3 than on the capabilities of the language you re using. Implementation details should be hidden two layers below this one, in a layer of computer-science structures, so that changes in hardware or the operating system don t affect this layer at all. Embody the user s view of the world in the program at this level because when the program changes, it will change in terms of the user s view. Changes in the problem domain should affect this layer a lot, but
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34. Themes in Software Craftsmanship
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they should be easy to accommodate by programming in the problem-domain building blocks from the layer below. In addition to these conceptual layers, many programmers find it useful to break a program up into other layers that cut across the layers described here. For example, the typical 3-tier architecture cuts across the levels described here, and provides further tools for making the design and code intellectually manageable.
Low-Level Techniques for Working in the Problem Domain
Even without a complete, architectural approach to working in the problem area s vocabulary, you can use many of the techniques in this book to work in terms of the real-world problem rather than the computer-science solution: Use classes to implement structures that are meaningful in problem-domain terms. Hide information about the low-level data types and their implementation details. Use named constants to document the meanings of strings and of numeric literals. Assign intermediate variables to document the results of intermediate calculations. Use boolean functions to clarify complex boolean tests.
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