[COURSE] Add CMU17-803 Empirical Methods (#596)

docs/软件工程/17803.en.md

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+# CMU 17-803: Empirical Methods
+
+## Descriptions
+
+- Offered by: CMU
+- Prerequisites: solid foundations of computer science
+- Programming Languages: Any
+- Difficulty: 🌟🌟🌟
+- Class Hour: 100 hours
+
+This course focuses on a relatively "unfamiliar" area — empirical research in software engineering. It is taught by Bogdan Vasilescu, who has extensive expertise in empirical studies and open-source software research.
+
+The course is offered by CMU for PhD students pursuing research in this field. It covers a range of qualitative and quantitative research methods, such as interviews, qualitative coding, survey design, and various statistical analysis methods, helping students understand, learn, and engage in empirical research. The course also introduces the extraction and integration of data from software repositories like GitHub and Stack Overflow, applying statistical modeling, social network analysis, and other data analytics techniques.
+
+Although the field of computer science traditionally focuses more on engineering technology, empirical research is essential for the design, evaluation, and potential social value of tools and technologies. For example, it involves evaluating new algorithms or new technological frameworks, analyzing relevant data within a field, and understanding challenges that practitioners might face. This course can expand and complement a focus on technical aspects. For those interested in pursuing research involving empirical studies in the field of software engineering, this course could be an excellent introduction.
+
+## Course Resources
+
+- Course Website: [Spring 2024](https://bvasiles.github.io/empirical-methods/), [Fall 2022](https://bvasiles.github.io/empirical-methods/fall-2022/), [Spring 2021](https://bvasiles.github.io/empirical-methods/spring-2021/), [Fall 2018](https://bvasiles.github.io/empirical-methods/fall-2018/)
+- Recordings: [Spring 2024](https://www.youtube.com/playlist?list=PLuPUOEODcOmsiOxD7LK5EcQcj34Y9NwYg), [Fall 2022](https://www.youtube.com/watch?v=IDtePCle3Qc)
+- Textbooks: Reading materials before each lecture.
+- Assignments: Not open-source.
+
+## Personal Resources
+
+All the resources and assignments in this course are maintained in [bvasiles/empirical-methods - GitHub](https://github.com/bvasiles/empirical-methods).

docs/软件工程/17803.md

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+# CMU 17-803: Empirical Methods
+
+## 课程简介
+
+- 所属大学：CMU
+- 先修要求：面向从事软件工程实证研究的博士生开设，虽然没有硬性先修要求但最好有一定的计算机基础
+- 编程语言：不限
+- 课程难度：🌟🌟🌟
+- 预计学时：100 小时
+
+这门课专注于一个相对“陌生”的领域——包括但不限于软件工程领域的实证研究，由 [Bogdan Vasilescu](https://bvasiles.github.io/) 讲授，他在实证研究和开源软件研究方面非常深入。
+
+这门课是 CMU 为从事该方向研究的博士生开设的，涵盖一系列定性与定量研究方法，如访谈、定性编码、调查设计以及多种数据统计分析方法，帮助学生了解、学习与从事实证研究。课程还会介绍挖掘和整合 GitHub 和 Stack Overflow 等软件存储库中的数据，并运用统计建模、社交网络分析等数据分析技术。
+
+尽管计算机领域在传统上更注重工程技术，但对于工具、技术的设计、评估以及其可能的社会价值来说，实证研究是必需的。例如评估新算法或新技术框架，对某个领域进行相关数据分析，去了解从业者可能面临的挑战。这门课可以扩展和补充专注于技术领域视角。对于想要从事涉及软件工程领域实证研究的科研方向的朋友，这门课可能是一个很好的入门课程。
+
+## 课程资源
+
+- 课程网站：[Spring 2024](https://bvasiles.github.io/empirical-methods/), [Fall 2022](https://bvasiles.github.io/empirical-methods/fall-2022/), [Spring 2021](https://bvasiles.github.io/empirical-methods/spring-2021/), [Fall 2018](https://bvasiles.github.io/empirical-methods/fall-2018/)
+- 课程视频：[Spring 2024](https://www.youtube.com/playlist?list=PLuPUOEODcOmsiOxD7LK5EcQcj34Y9NwYg), [Fall 2022](https://www.youtube.com/watch?v=IDtePCle3Qc)
+- 课程教材：未公开，每节课前会有阅读材料
+- 课程作业：未公开
+
+## 资源汇总
+
+这门课中用到的所有资源都汇总在 [bvasiles/empirical-methods - GitHub](https://github.com/bvasiles/empirical-methods) 中。

mkdocs.yml

@@ -193,6 +193,7 @@ nav:
   - 软件工程:
       - "MIT 6.031: Software Construction": "软件工程/6031.md"
       - "UCB CS169: software engineering": "软件工程/CS169.md"
+      - "CMU 17-803: Empirical Methods": "软件工程/17803.md"
   - 计算机系统基础:
       - "CMU 15-213: CSAPP": "计算机系统基础/CSAPP.md"
       - "Stanford CS110: Principles of Computer Systems": "计算机系统基础/CS110.md"