Collaborative Research: CNS Core: Small: RUI: Intelligent Developer Infrastructure

软件工程师使用开发工具来帮助开发软件。这些工具可以将计算机代码编译成可运行的程序，调试程序以发现和修复错误，并跨系统部署软件。用于这些任务的现有工具非常复杂。误用工具可能会导致错误和效率低下。例如，一个流行的代码编译工具，称为“make”，使用用户提供的任务编码自动编译。“make”的用户必须要么生成简单但低效的编码，要么生成高效但复杂且错误风险增加的编码。该项目介绍了无需编程即可正确高效地自动执行编译、调试和部署任务的技术。该项目提出了一种基于依赖图的核心技术。依赖图是通过观察一段软件在运行时与其环境交互而生成的。这个项目提出了三个工具，它们利用依赖图来自动化软件开发任务。首先，Riker基于单个示例编译正确而高效地自动执行编译任务。其次，Scotty通过观察程序的执行来回答有关程序哪里出错的高级问题。第三，Locutus通过在示例部署过程中观察用户来自动执行软件部署任务。该项目有可能显著影响软件开发人员的日常工作。自动化支持任务，只需最少的开发人员投入即可降低软件开发成本，并确保支持任务按结构正确执行。这些变化使软件开发人员可以专注于他们的核心任务。该项目将为格林内尔学院和威廉姆斯学院的本科生提供参与研究的机会，并将通过纳入代表不足的群体的学生来扩大参与。该项目的所有产品将在https://github.com/curtsinger-lab/idi-grant.上托管在这个项目过程中产生的代码将在麻省理工学院的许可下发布。对现有软件的修改将在兼容的开源许可证下发布。任何非代码产品将仅包含公开可用的非机密信息，并将在知识共享许可下发布。该项目的所有产品将在项目结束后至少保存五年。该奖项反映了NSF的法定使命，并已通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Software engineers use development tools to help develop software. The tools may compile computer code into runnable programs, debug programs to find and fix errors, and deploy software across systems. Existing tools used for these tasks are complex. The misuse of tools can introduce errors and inefficiencies. For example, a popular tool for compiling code, called "make", automates compilation with a user-provided encoding of the task. Users of "make" must produce either a simple but inefficient encoding, or an efficient but complex encoding with an increased risk of error. This project introduces techniques that correctly and efficiently automate compilation, debugging, and deployment tasks without programming.This project proposes a core technique built on dependency graphs. A dependency graph is generated by observing a piece of software interacting with its environment as it runs. This project proposes three tools that leverage dependency graphs to automate software development tasks. First, Riker correctly and efficiently automates compilation tasks based on a single example compilation. Second, Scotty answers high-level queries about where a program went wrong by observing the program's execution. Third, Locutus automates software deployment tasks by observing the user during an example deployment.This project has the potential to impact the day-to-day work of software developers significantly. Automating support tasks with minimal developer input reduces the cost of software development and guarantees that support tasks are correct by construction. These changes free software developers to focus on their core tasks. This project will provide undergraduate students at Grinnell College and Williams College with opportunities to participate in research, and will broaden participation by including students from underrepresented groups.All products of this project will be hosted at https://github.com/curtsinger-lab/idi-grant. Code produced in the course of this project will be released under the MIT license. Modifications to existing software will be released under a compatible open source license. Any non-code products will comprise only publicly-available, non-confidential information, and will be released under a Creative Commons license. All products of this project will be preserved for at least five years after the conclusion of the project.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.