CAREER: Differential Types and Declarative Hypothesis Testing for Software Evolution

在第一个版本发布之后很久，软件仍在继续发展。在演化过程中对源代码进行的更改可能没有预期的语义(修复错误、添加功能)，这对软件生产者和软件消费者都有负面影响，并具有高昂的经济成本。更广泛地说，软件演化过程并没有被很好地理解。为了纠正这种情况，这项工作将以两种方式使用从分析软件历史中获得的信息。首先，开发一种基于类型系统的方法，称为差异类型，它允许对源代码在进行更改之前和之后的属性进行推理，并揭示开发时源代码更改的语义。第二，构建一个说明性假设检验框架，以自动化和简化软件进化和软件工程的实证研究过程。这项工作的跨学科基础将催化编程语言和软件工程这两个主要群体之间的互动。这项研究的结果将有助于更好地理解软件是如何进化的，并改进软件进化过程。通过在部署软件之前使软件改变的语义显式并揭示某些类型的错误，降低了软件错误和错误软件更新的发生率和与之相关联的成本。该项目将改变研究人员进行经验性软件进化研究的方式，将重点从如何测试假设转移到什么是正确的假设。这些贡献将公之于众，这不仅将使研究界受益，也将使软件开发界受益。来自这项工作的想法将被纳入教育，以便明天的毕业生更好地准备应对软件发展的挑战。

Software continues to evolve long after the first version is released. Changes made to source code in the course of evolution might not have the intended semantics (fix bugs, add features), which negatively impacts both software producers and software consumers, and has high economic costs. More generally, the software evolution process is not very well understood. To remedy this situation, this work will use information derived from analyzing software history in two ways. First, to develop a type systems-based approach named differential typing, that enables reasoning about the properties of source code before and after a change has been made, and reveals the semantics of source code changes at development time. Second, to construct a framework for declarative hypothesis testing that automates and simplifies the process of conducting empirical studies in software evolution, and software engineering in general.The interdisciplinary foundation of this work will catalyze interaction between two primary communities, programming languages and software engineering. The results of this research will lead to a better understanding of how software evolves, and to improvements in the software evolution process. By making the semantics of software changes explicit and revealing certain kinds of errors before software is deployed, the incidence of, and costs associated with, software bugs and incorrect software updates are reduced. The project will transform the way researchers conduct empirical software evolution studies by shifting the focus from how hypotheses are tested to what the right hypotheses are. The contributions will be made publicly available, which will benefit not only the research community, but also the software development community. Ideas from this work will be incorporated into education, so that tomorrow's graduates are better prepared to tackle software evolution challenges.