Lecture: Empirical Software Engineering
Course Content
The development of software can be seen as a chain of design decisions. In modern software development, these decisions are increasingly made based on data (e.g., data about the usage). In addition, software itself is increasingly controlled by algorithms that are trained by data (e.g., using machine learning). Therefore, a sound understanding of empirical research methods and data analysis is becoming increasingly important for software developers. Empirical Software Engineering deals with the collection and analysis of data about software engineering artifacts in order to derive knowledge that can be used to improve the software or the software development process. This module teaches the foundation of Empirical Software Engineering. The topics include:
- What is empirical research and what forms of empirical studies exist in software engineering (e.g. interviews, surveys, case studies, experiments)?
- The structure of empirical studies
- Data collection
- Data analysis (theory building, validation of hypotheses)
- Validity of empirical results
The basics are taught in an open education manner, consisting of lectures, labs (programming examples) and self study phases. In an accompanying project, students design, conduct, and evaluate their own empirical study on a self-selected or provided research questions related to software engineering.
Time Schedule
The lecture is held every Thursday from 10:00 - 11:30 in Sibille-Hartmann-Str. 2-8, room 1.421. The addtional material and excercises will be updated throughout the semester.
| Date | Time | Topic |
|---|---|---|
| 06.04.2023 | 10:00 - 11:30 | Introduction and Lecture 1: Introduction to Empirical Software Engineering |
| 13.04.2023 | self study | Lecture 2 (recorded): Theories in Software Engineering and How to Create Knowledge |
| 20.04.2023 | self study | Lecture 3 (recorded): Research Strategies and Measurements |
| 26.04.2023 | 12:00 - 13:30 | Lecture 4: Descriptive Statistics |
| 03.05.2023 | 12:00 - 13:30 | Lecture 5: Controlled Experiments and Hypothesis Testing |
| 10.05.2023 | 12:00 - 13:30 | Study Marketplace |
| 17.05.2023 | Working on the project (no class) | |
| 24.05.2023 | 12:00 - 13:30 | Lab 1: Descriptive Statistics |
| 31.05.2022 | self study | Lecture 6 (recorded): Statistical Tests and How to Select the Right One |
| 07.06.2023 | Working on the project (no class) | |
| 14.06.2023 | 12:00 - 13:30 | Intermediate Presentations |
| 21.06.2023 | 12:00 - 13:30 | Lab 2: Hypothesis Testing |
| 28.06.2023 | 12:00 - 13:30 | Lab 3: How to write an Empirical Paper |
| 05.07.2023 | 12:00 - 13:30 | Open Session: Paper Discussions |
| 12.07.2023 | 12:00 - 13:30 | Final Presentation |
| 28.07.2022 | 23:59:59 | Paper Submission Deadline |
Team
- Prof. Dr. Andreas Vogelsang
- Dr. Mersedeh Sadeghi
Registration and Size Constraints
Due to the close supervision the lecture is currently limited to 20 participants. If you are interested in the lecture, please register for the repsective KLIPS course.
Workload
The lecture is designed for 2 SWS and is worth 6 ECTS points.