Master Seminar - Fall 2019
List of papers that were assigned in the first lecture.
Basic Information
- READ: Course description, how it works
- Course number: 263-2100, 2 credits
- Fall 2019, lectures: T 13:15-15:00, CHN G46
- Instructors:
- Peter Müller
- Markus Püschel
- Zhendong Su
- Martin Vechev
- TAs (and associated instructor):
- Gagandeep Singh, gsingh@inf.ethz.ch (MPü)
- Alexandra Bugariu, alexandra.bugariu@inf.ethz.ch (PM)
- Federico Poli, federico.poli@inf.ethz.ch (PM)
- Pinjia He, pinjia.he@inf.ethz.ch (ZS)
- Ting Su, tingsu@ethz.ch (ZS)
- Pavol Bielik, pavol.bielik@inf.ethz.ch (MV)
- Mislav Balunovic, mislav.balunovic@inf.ethz.ch (MV)
Lectures
Date | Content | TA advisor | Instructor |
---|---|---|---|
17.09. | Organization, small guide to making presentations | MPü | |
24.09. | no lecture | ||
01.10. | no lecture | ||
08.10. | no lecture | ||
15.10. | no lecture | ||
22.10. | Moritz K.: Parser-Directed Fuzzing | AB | PM |
Zak M. C.: Interactive Metamorphic Testing of Debuggers | AB | ||
29.10. | David A. R.: Semantic Fuzzing with Zest | TS | ZS |
Noël J. R.: Bug Synthesis: Challenging Bug-Finding Tools with Deep Faults | TS | ||
05.11. | Lowis A. E.: Lazy counterfactual symbolic execution | FP | PM |
Bernhard P. K.: Model-Based Testing of Breaking Changes in Node.js Libraries | AB | ||
12.11. | no lecture | ||
19.11. | Romina J.: code2vec: Learning Distributed Representations of Code | PB | MV |
Jan D. S.: Synthesizing Datalog Programs using Numerical Relaxation | MB | ||
26.11. | Cédric N.: SMOKE: Scalable Path-Sensitive Memory Leak Detection for Millions of Lines of Code | PH | ZS |
Patrick J. S.: Testing Probabilistic Programming Systems | TS | ||
03.12. | Kaïko G.: Resource-aware program analysis via online abstraction coarsening | GS | MPü |
Jakob R.: Evaluating design tradeoffs in numeric static analysis for Java | GS | ||
10.12. | no lecture | ||
17.12. | Arthur L. D.: SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver | PH | ZS |
Kosta S.: Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition | PH |