Functional programming languages are free of side effects which makes programs written in them easy to verify, parallelize and optimize. However, to maintain this model, naive execution may involve an excessive amount of copying which consumes both space and time. Optimizing the compilers for such languages with an algorithm that minimizes copies improves their performance without losing the side effect free feature. In this thesis we present a O(TlogT + V Ew + V2) greedy in-placeness algorithm that reduces the amount of copying in such languages. We have implemented a prototype of the in-placeness algorithm for the widely used graphical programming language LabVIEW and compared its performance to the performance of the ad-hoc in-placeness heuristic used in the current LabVIEW compiler. Our in-placeness algorithm achieves promising improvements to LabVIEW performance in a uniform and systematic approach. National Instruments anticipates incorporating our algorithm in the next published version of the LabVIEW compiler.
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机译：函数式编程语言没有副作用，这使得用它们编写的程序易于验证，并行化和优化。但是，要维护此模型，天真的执行可能会涉及大量复制，这会占用空间和时间。使用最小化副本的算法针对此类语言优化编译器可提高其性能，而不会失去无副作用的功能。在本文中，我们提出了一种O（TlogT + V Ew + V2）贪婪就地算法，该算法减少了此类语言的复制量。我们为广泛使用的图形编程语言LabVIEW实现了就地算法的原型，并将其性能与当前LabVIEW编译器中使用的即席就地启发式算法的性能进行了比较。我们的就位算法以统一，系统的方法实现了LabVIEW性能的有希望的提高。 National Instruments希望将我们的算法纳入LabVIEW编译器的下一个发行版本。
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