CS/SE 7301.501 - Software Analysis & Security

Fall 2020

Course Information

Location: MS Teams
Time: Monday & Wednesday 05:30PM - 06:45PM
Instructor: Wei Yang
Email: wei.yang@utdallas.edu
Office: ECSS 4.225
Office Hours: By Appointment
TA: Yufei Li
Email: Yufei.Li@utdallas.edu
Office: TBD
Office Hours: TBD

Course Style

This course is taught in a seminar-course style. Each student will be expected to:

Textbooks

We do not have textbooks but you can refering to following books for background knowledge.
Static Program Analysis
The Fuzzing Book
The Art and Science of Analyzing Software Data (using UTD email to access)
Dive into Deep Learning
Building Intelligent Systems: A Guide to Machine Learning Engineering (using UTD email to access)
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (using UTD email to access)

Course Project Topic and Grading Policy

Topic: Propose your own projects (Feel free to talk to the instructor about the proposed topic). A list of topics will be provided in the class.
Grading Policy:

Schedule and Lecture Slides

Week Dates Topic
1.1 Aug. 24th Course Overview [Slides] [Video]
1.2 Aug. 26th Software Analysis Foundation [Slides] [Reading1] [Reading2]
2.1 Aug. 31st Testing [Slides] [Reading1] [Reading2]
3.1 Machine Learning Basics[Slides] [Video] [Reading]
3.2 Automated Testing[Slides] [Reading1] [Reading2]
4.1 Automated Testing[Slides] [Reading1] [Reading2]
4.2 Symbolic Execution [Slides] [Reading1] [Reading2]
5.1 ML for Code Analysis [Presentation1] [Reading1] [Reading2]
5.2 Analysis for ML Software [Presentation1] [Presentation2] [Reading]
6.1 Symbolic Execution (cont.) [Slides] [Presentation1] [Reading1] [Reading2]
6.2 Embedding [Slides] [Reading]
7.1 Adversarial Machine Learning-Evasion Attacks [Slides] [Presentation1]
7.2 Adversarial Machine Learning-Other Attacks [Slides] [Reading]
8.1 Privacy of Machine Learning [Slides] [Reading]
8.2 Fairness of Machine Learning [Slides] [Reading]
9.1 Testing of Machine Learning Models [Slides] [Reading]
9.2 Debugging of Machine Learning Models [Slides] [Reading]
10.1 Detecting Issues in Deep Learning Applications [Slides] [Reading]
10.2 Trending Security Topics [Slides] [Reading]
11.1 Project Presentation [Slides] [Reading]