SHF: Small: Find and Fix Similar Software Bugs

在开发可靠和高质量软件的过程中，发现和修复错误至关重要。软件开发人员可以根据自己的经验与他们的程序，或有效地发现错误，通过咨询类似的错误和修复从其他人在过去的相同或不同的系统。然而，软件工程中的知识体系仍然非常有限的性质，原因和影响，以及这些反复出现的错误的特征。从先前已知的错误中学习的过程仍然是临时的、手动的和非系统的。在这个项目中，引入了一种全面的方法来捕获以前的错误和相应的修复程序的知识，并利用这些知识来构建自动化工具，以检测在相同或不同系统中的其他位置的潜在重复出现的错误代码。这些工具将有助于在开发过程的早期发现错误，从而提高软件质量，并提高软件开发人员在错误修复实践中的生产力。在本项目中，将进行实证研究，以收集，分析和了解在一个和多个系统中重复出现的和类似的错误的性质和特征。该项目预计将在理论基础，概念，实用技术和自动化工具方面推进软件工程知识，以（1）捕获先前已知的已修复错误中涉及的代码单元的特征并测量其相似性，（2）识别潜在错误单元的位置并通过将其与已知错误的相关对等代码单元进行匹配来获得修复它们的指南，（3）支持类似的bug检测和修复过程。该项目的教学模块和验证工作将涉及学生和专业人员，促进教学和培训软件质量保证。

Finding and fixing bugs are crucial in the process of developing reliable and high-quality software. Software developers could base on their own experience with their programs, or effectively find bugs by consulting the similar bugs and fixes from others in the past for the same or different systems. However, the body of knowledge in software engineering is still very limited on the nature, the causes and effects, and the characteristics of such recurring bugs. The learning process from prior known bugs is still ad-hoc, manually, and un-systematically. In this project, a comprehensive approach is introduced to capture the knowledge of prior bugs and corresponding fixes, and to leverage such knowledge to build automated tools to detect potential recurring buggy code at other locations in the same or different systems. Such tools will help to detect bugs early in the development process, leading to higher-quality software and the improvement in productivity of software developers in the bug fixingpractice.In this project, an empirical study will be conducted to collect, analyze, and understand the nature and characteristics of recurring and similar bugs within one and across multiple systems. This project is expected to advance software engineering knowledge on the theoretical foundation, concepts, practical techniques, and automated tools to (1) capture the characteristics and measure the similarity of code units involved in prior known fixed bugs, (2) identify the locations of potential buggy units and derive the guidelines to fix them by matching them to the relevant peer code units of the known bugs, and (3) support the similar bug detection and fixing process. The teaching modules and validation efforts in this project will involve students and professionals, promoting teaching and training software quality assurance.