构建与演化的代码生成器模型驱动和服务导向方法

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《代码生成器的构建与进化:模型驱动和服务导向方法》是一篇发表在1973年LectureNotesinComputerScience系列中的论文,编者包括Gerhard Goos、Juris Hartmanis和Jan van Leeuwen等知名学者。该研究论文主要关注代码生成器的发展历程及其核心原理。作者Sven Jörge在文中探讨了代码生成器的构造方法,强调了在计算机科学领域,随着技术的进步,这些工具如何从最初的简单设计逐步演变为更加复杂且高度适应性、服务导向的模型驱动系统。 早期的代码生成器主要负责将高级语言的抽象语法树转换为机器语言,以实现程序的高效执行。随着软件工程的兴起,它们开始采用模块化和自动生成的策略,以提高编程效率和可维护性。论文可能讨论了模板方法、解析技术(如词法分析和语法分析)、类型检查和优化策略等关键技术在代码生成器中的应用。 模型驱动的方法在此背景下引入,它强调通过模型来描述系统的结构和行为,进而自动化生成符合特定规范的代码。这种方法有助于降低人为错误,同时支持跨平台和异构环境下的代码生成。服务导向架构也被提及,可能意味着代码生成器可以作为独立的服务组件与其他系统交互,根据需求动态提供相应的代码生成功能。 论文还可能涵盖了代码生成器在软件开发生命周期中的角色变化,如在持续集成和自动化测试中的角色,以及在现代软件开发中的微服务和云计算环境中,如何利用代码生成器来加速部署和扩展。此外,随着人工智能和机器学习的兴起,代码生成器可能会结合这些技术,如自动代码完成和自动生成优化算法。 论文的最后部分可能会对未来的趋势进行展望,比如利用深度学习和人工智能技术改进代码生成的质量,或者探索新的编程范式下代码生成的新挑战和解决方案。这篇文章深入剖析了代码生成器的历史演变,以及如何通过模型驱动和服务导向的方法来适应不断发展的IT行业需求。

## Problem 5: Remainder Generator Like functions, generators can also be higher-order. For this problem, we will be writing `remainders_generator`, which yields a series of generator objects. `remainders_generator` takes in an integer `m`, and yields `m` different generators. The first generator is a generator of multiples of `m`, i.e. numbers where the remainder is 0. The second is a generator of natural numbers with remainder 1 when divided by `m`. The last generator yields natural numbers with remainder `m - 1` when divided by `m`. Note that different generators should not influence each other. > Hint: Consider defining an inner generator function. Each yielded generator varies only in that the elements of each generator have a particular remainder when divided by m. What does that tell you about the argument(s) that the inner function should take in? ```python def remainders_generator(m): """ Yields m generators. The ith yielded generator yields natural numbers whose remainder is i when divided by m. >>> import types >>> [isinstance(gen, types.GeneratorType) for gen in remainders_generator(5)] [True, True, True, True, True] >>> remainders_four = remainders_generator(4) >>> for i in range(4): ... print("First 3 natural numbers with remainder {0} when divided by 4:".format(i)) ... gen = next(remainders_four) ... for _ in range(3): ... print(next(gen)) First 3 natural numbers with remainder 0 when divided by 4: 4 8 12 First 3 natural numbers with remainder 1 when divided by 4: 1 5 9 First 3 natural numbers with remainder 2 when divided by 4: 2 6 10 First 3 natural numbers with remainder 3 when divided by 4: 3 7 11 """ "*** YOUR CODE HERE ***" ``` Note that if you have implemented this correctly, each of the generators yielded by `remainder_generator` will be infinite - you can keep calling next on them forever without running into a `StopIteration` exception.

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