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Stuhlsatzenhaus 5
66123 Saarbrücken (Germany)


Selected Awards

2020: ISSTA 2020 Impact Paper Award for "Mutation-driven generation of unit tests and oracles" (with Gordon Fraser)

2017: MSR 10-Year Most Influential Paper Award for "How Long Will It Take to Fix This Bug?" (with Cathrin Weiß, Rahul Premraj, and
Thomas Zimmermann)

2015: MSR 10-Year Most Influential Paper Award for "When do Changes induce Fixes?" (with Jacek Sliwerski and Thomas Zimmermann)

2015: ICSE 10-Year Most Influential Paper Award, Official Runner-Up for "Locating Causes of Program Failures" isolating
cause-effect chains in failing programs (with Holger Cleve)

2014: ICSE 10-Year Most Influential Paper Award for "Mining Software Histories to Guide Software Changes" introducing mining
software repositories (with Thomas Zimmermann, Peter Weißgerber, and Stephan Diehl)

2009: ACM SIGSOFT 10-Year Impact Award for "Yesterday, my program worked. Today, it does not. Why?" introducing
Delta Debugging

Short Bio

Prof. Dr. Andreas Zeller is tenured faculty at CISPA and professor for Software Engineering at Saarland University. His research on automated debugging, mining software archives, specification mining, and security testing has been highly influential. Zeller is an ACM Fellow and holds an ACM SIGSOFT Outstanding Research Award.


CV: Last four stations

Since 2019
Faculty at CISPA Helmholtz Center for Information Security
Since 2003
Full Professor, Computer Science, Saarland University, Germany
2001 – 2003
Associate Professor (C3), Computer Science, Saarland University, Germany
1999 – 2001
Post-Doc Researcher (C1), Computer Science, Passau University, Germany

Publications by Andreas Zeller

Year 2020

Conference / Medium

1st IEEE/ACM International Conference on Automation of Software Test

Conference / Medium

ICSE'20: International Conference onSoftware EngineeringICSE 2020: Proceedings of the International Conference on Software Engineering

Year 2019

Conference / Medium

Automated Software EngineeringASE 2019

Conference / Medium

PETS 2019 - The 19th Privacy Enhancing Technologies SymposiumPETS 2019 - The 19th Privacy Enhancing Technologies Symposium

Conference / Medium

ACM SIGSOFT International Symposium on Software Testing and Analysis

Conference / Medium

40th ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2019)

Conference / Medium

2019 IEEE/ACM 41st International Conference on Software Engineering: Companion Proceedings (ICSE-Companion)

Teaching by Andreas Zeller

Winter 2021/22

Automated Testing and Debugging

It is estimated that programmers spend half of their time testing and debugging their code.  Wouldn't it be great if computers could help automating these boring tasks?

In this proseminar, we explore and evaluate automated techniques for testing and debugging software.  We look at a number of classic approaches for generating software tests automatically, for finding errors and locating faults, and for having these two interact with each other.  You will be 

  • reading the associated papers,
  • presenting the associated work,
  • possibly even with a demonstration of the technique.

For every technique, we will be providing you with the papers (and a reference or textbook implementation, if available).  For the presentation, we use standard presentation software; for demonstrations, Python and Jupyter Notebooks have shown to be practical.  During the seminar, you will refine your presentation and demonstration skills with us up to the final (and decisive) presentation.

The first part of the seminar consists of ~10 virtual (Zoom) sessions of one hour, with at most one session per week. In each of these sessions, we will have two short presentations and a feedback and discussion round.

In the second part of the seminar, participants will give their final, graded presentations. This part consists of several (at most three) block sessions, which might be held virtually or on-site.

Attendance in all (virtual and on-site) proseminar meetings is mandatory.

Requirements: Programming skills will be required for demonstrations.  Knowledge of Python and experience with Jupyter Notebooks is helpful, but can be acquired during the proseminar.

Registration: To register, use the central system of the CS department.

Winter 2021/22

Security Testing

Software has bugs, and catching bugs can involve lots of effort. This course addresses this problem by automating software testing, specifically by generating tests automatically. Recent years have seen the development of novel techniques that lead to dramatic improvements in test generation and software testing.  In this course, we explore these techniques – in theory and in code.

Course Organization

Every week, you will be provided with Jupyter Notebooks that teach a particular topic and illustrate it using plenty of runnable Python code.  These notebooks come from The Fuzzing Book, a textbook on how to generate software tests written by yours truly.

In the notebook, you can edit the code as you like, run your own experiments, and re-use and extend the code to your liking.  Your task will be to use these techniques (and their code) to build a series of fuzzers (i.e. test generators) that find bugs in a number of challenging settings.


This course uses the "inverted classroom" principle – you learn at home, and discuss issues with your instructor.  In our weekly meeting, we use the gathering in the lecture hall to

  • discuss the assignment of last week
  • discuss the assignment of next week
  • discuss ongoing projects as well as general questions.

These meetings come with live coding, so we can explore ideas right on the go.


During this course, you apply the techniques learned in weekly exercises and two projects which form your coursework. Projects are graded for effectiveness, efficiency, elegance, and creativity. Projects offer special challenges which allow you to gain bonus points.


Every week, you get a simple exercise assignment covering the material of the last lecture. Performance in these exercises will make 33% of the final grade.  Note that there is no final exam.


Advanced programming skills (such as obtained after two years of successfully studying CS) are required. Knowledge in Python is useful, but can easily be acquired along the course.

Passing Criteria and Grading

To pass this course, you need to have

  • at least 50% of the points in each of the projects, and 
  • at least 50% of the total exercise points.

Your final grade is determined by 66% projects and 33% exercises (see above).

Lecture Plan

The course is organized as "inverted classroom": Every week, we discuss a chapter of the book, which will be supplied with an introduction video; we meet once a week to discuss the material, the associated exercises, and the ongoing projects.

The lecture plan may be subject to changes; these will be announced in time.

Date, Time, Location

  • 14 lectures
  • 6 Credit Points
  • In-presence tutorial and discussion every Tuesday 16:15–17:45, CISPA, Lecture Hall 0.05
  • Optional attendance via Zoom:
  • Start: Tuesday October 19
Summer 2020

Proseminar: Automated Testing and Debugging

In this proseminar, we explore and evaluate automated techniques for testing and debugging software. We look at a number of classic approaches for generating software tests automatically, for finding errors and locating faults, and for having these two interact with each other.

More information

Summer 2020

Seminar: Advanced Fuzzing Techniques

In this seminar, we explore and evaluate automated test generation techniques (fuzzers) and related techniques for their effectiveness and efficiency. We discuss and design evaluation criteria and apply them on a number of techniques from the "Fuzzing Book" ( Apart from reporting and presenting your results in the seminar, your evaluation results will be included in the book. If the results or techniques are novel (many of them are), we will also strive to publish them as a scientific paper, with you as co-author.

More information

Winter 2019/20

Advanced Lecture: Generating Software Tests

Software has bugs, and catching bugs can involve lots of effort. This course addresses this problem by automating software testing, specifically by generating tests automatically.