II-EN: Collaborative Research: Positioning MLton for Next-Generation Programming Languages Research

MLton是标准ML编程语言的开源、全程序、优化编译器。与任何大型和成熟的软件系统一样，需要评估MLton软件项目的设计和架构，并进行持续研究和开发所需的任何实质性更改。 这个计算研究基础设施项目支持增强定位MLton作为一种工具，在编程语言的设计和实现的研究。 这些增强功能将直接支持研究，同时为学生和下一代研究人员提供生产级编译器背景下的软件开发体验，这是一个复杂的软件系统，汇集了计算机科学教育的许多主题，并鼓励批判性思维。 最后，这些增强将间接支持更广泛的编程语言研究社区和使用函数式编程语言的行业软件开发人员。该项目更广泛的影响将是培训各级学生研究助理，使用MLton基础设施开发用于教学编译器相关主题的文档和课程材料，以及继续支持MLton的工业和学术用户。具体的基础设施增强将包括开发类型检查和优化基础设施，线程和垃圾收集框架，配置和基准测试支持系统，以及包括课程材料在内的文档。这些增强将直接支持探索下一代语言功能（如第一类多态性，广义代数数据类型和高阶多态性）的全程序编译的研究，以及探索下一代执行平台（如多核并行系统，实时嵌入式系统和基于云的分布式系统）编程的研究。一个重要的目标是提供一个单一的研究工具，可以轻松配置，以科学地比较和对比研究结果，从而使研究人员能够根据更有意义的比较做出更有力的主张，而不是依赖于多个系统堆栈中的较弱主张。

MLton is an open-source, whole-program, optimizing compiler for the Standard ML programming language. As with any large and mature software system, there is a need to evaluate the design and architecture of the MLton software project, and to make any substantive changes required for continued research and development. This Computing Research Infrastructure project supports enhancements to position MLton as a vehicle for research in programming-language design and implementation. These enhancements will directly support research, while providing students and next-generation of researchers with a software development experience in the context of a production-level compiler, a complex software system that draws together many themes of Computer Science education, and encourages critical thinking. Finally, these enhancements will indirectly support both the broader programming-languages research community and industry software developers that use functional programming languages. The broader impacts of the project will be in training of student research assistants at all levels, the development of documentation and course materials for teaching compiler-related topics using the MLton infrastructure, and the continued support for MLton's industrial and academic users.Specific infrastructure enhancements will include development of type-checking and optimization infrastructures, threading and garbage collection frameworks, configuration and benchmarking support systems, and documentation including course material. These enhancements will directly support research exploring whole-program compilation of next-generation language features (such as first-class polymorphism, generalized algebraic data types, and higher-order polymorphism) and research exploring programming for next-generation execution platforms (such as multi-core parallel systems, real-time embedded systems, and cloud-based distributed systems). One significant goal is to provide a single research vehicle that is easily configurable to scientifically compare and contrast research results, thereby enabling researchers to make stronger claims based on more meaningful comparisons, rather than relying on weaker claims across multiple system stacks.