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The Unix Programming Environment, by Brian Kemighan and Rob Pike (Prentice Hall, 1984), contains an extended discussion of the tool-based approach to computing that Unix supports so well 8 of that book presents a complete implementation, from yacc grammar to executable code, of a simple programming language TEX: The Program, by Don Knuth (Addison-Wesley, 1986), describes a complex document formatter by presenting the entire program, about 13,000 lines of Pascal, in a "literate programming" style that combines explanation with program text and uses programs to format documentation and extract compilable code A Retargetable C Compiler: Design and Implementation by Chris Fraser and David Hanson (AddisonWesley, 1995) does the same for an ANSI C compiler The Java virtual machine is described in The Java Virtual Machine Specification, 2nd Edition, by Tim Lindholm and Frank Yellin (Addison-Wesley, 1999)
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NOTATION
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Ken Thompson's algorithm (one of the earliest software patents) was described in "Regular Expression Search Algorithm," Communications of the ACM, 11, 6, pp 419-422, 1968 Jeffrey E F Friedl's Mastering Regular Expressions (O'Reilly, 1997) is an extensive treatment of the subject An on-the-fly compiler for two-dimensional graphics operations is described in "HardwareISoftware Tradeoffs for Bitmap Graphics on the Blit," by Rob Pike, Bart Locanthi, and John Reiser, Software-Practice and Experience, 15, 2, pp 131-152, February 1985
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Epilogue
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Ifmen could learn from history, what lessons it might teach us! But passion and party blind our eyes, and the light which experience gives is a lantern on the stem, which shines only on the waves behind us!
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Samuel Taylor Coleridge, Recollections The world of computing changes all the time, and the pace seems to accelerate Programmers must cope with new languages, new tools, new systems, and of course incompatible changes to old ones Programs are bigger, interfaces are more complicated, deadlines are shorter But there are some constants, some points of stability, where lessons and insight from the past can help with the future The underlying themes in this book are based on these lasting concepts Simplicity and clarity are first and most important, since almost everything else follows from them Do the simplest thing that works Choose the simplest algorithm that is likely to be fast enough, and the simplest data structure that will do the job; combine them with clean, clear code Don't complicate them unless performance measurements show that more engineering is necessary Interfaces should be lean and spare, at least until there is compelling evidence that the benefits outweigh the added complexity Generality often goes hand in hand with simplicity, for it may make possible solving a problem once and for all rather than over and over again for individual cases It is often the right approach to portability as well: find the single general solution that works on each system instead of magnifying the differences between systems Evolution comes next It is not possible to create a perfect program the first time The insight necessary to find the right solution comes only with a combination of thought and experience; pure introspection will not produce a good system, nor will pure hacking Reactions from users count heavily here; a cycle of prototyping, experiment user feedback, and further refinement is most effective Programs we build for
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EPILOGUE
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ourselves often do not evolve enough; big programs that we buy from others change too fast without necessarily improving Interfaces are a large part of the battle in programming and interface issues appear in many places Libraries present the most obvious cases but there are also interfaces between programs and between users and programs The desire for simplicity and generality applies especially strongly to the design of interfaces Make interfaces consistent and easy to learn and use; adhere to them scrupulously Abstraction is an effective technique: imagine a perfect component or library or program; make the interface match that ideal as closely as possible; hide implementation details behind the boundary, out of harm's way Automation is under-appreciated It is much more effective to have a computer do your work than to do it by hand We saw examples in testing, in debugging, in performance analysis, and notably in writing code, where for the right problem domain, programs can create programs that would be hard for people to write Notation is also under-appreciated, and not only as the way that programmers tell computers what to do It provides an organizing framework for implementing a wide range of tools and also guides the structure of the programs that write programs We are all comfortable in the large general-purpose languages that serve for the bulk of our programming But as tasks become so focused and well understood that programming them feels almost mechanical, it may be time to create a notation that naturally expresses the tasks and a language that implements it Regular expressions are one of our favorite examples, but there are countless opportunities to create little languages for specialized applications They do not have to be sophisticated to reap benefits As individual programmers, it's easy to feel like small cogs in a big machine, using languages and systems and tools imposed upon us, doing tasks that should be done for us But in the long run, what counts is how well we work with what we have By applying some of the ideas in this book, you should find that your code is easier to work with, your debugging sessions are less painful, and your programming is more confident We hope that this book has given you something that will make your computing more productive and more rewarding
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