Advanced Software Testing

Graduate Course

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Course Description

This course delves into advanced topics and cutting-edge techniques in software testing, empowering students to design and implement rigorous testing strategies for modern software systems. By covering methods such as automatic test data generation, metamorphic testing, fuzzing, hyper-property testing, and program analysis, the course equips students with tools to detect, isolate, and resolve complex software issues. Emphasis is placed on automation, scalability, and the theoretical foundations of testing to address real-world challenges in software quality assurance.

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Course Objectives

By the end of this course, students will: 1. Understand the theoretical underpinnings of advanced software testing methodologies.

1. Develop practical skills in automated testing, including test data generation and fuzzing.

2. Apply advanced techniques such as metamorphic testing and abstract interpretation to tackle testing challenges.

3. Analyze and verify software properties using program analysis and hyper-property testing.

4. Explore state-of-the-art tools and frameworks to enhance software reliability and security.

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Syllabus

Week 1-2: Fundamentals of Advanced Software Testing

• Recap of basic software testing concepts
• Challenges in modern software testing
• Introduction to test automation and advanced testing methodologies

Week 3-4: Automatic Test Data Generation

• Theory and algorithms for test data generation
• Symbolic execution and constraint solving
• Tools for automated test generation

Week 5-6: Metamorphic Testing

• Addressing the oracle problem in software testing
• Designing and applying metamorphic relations
• Applications of metamorphic testing in various domains

Week 7-8: Fuzz Testing

• Introduction to fuzzing techniques: black-box, gray-box, and white-box fuzzing
• Coverage-guided fuzzing and mutation-based testing
• Case studies of fuzzing tools (e.g., AFL, libFuzzer)

Week 9-10: Hyper-Property Testing

• Understanding hyper-properties and their significance
• Techniques for verifying and validating hyper-properties
• Applications in security, privacy, and concurrency testing

Week 11-12: Program Analysis and Abstract Interpretation

• Static and dynamic program analysis techniques
• Abstract interpretation and its role in bug detection
• Tools for program analysis (e.g., Clang Static Analyzer, CodeQL)

Week 13: Testing in the Real World

• Integration of advanced testing techniques in agile and DevOps environments
• Testing frameworks and automation pipelines
• Challenges and opportunities in adopting advanced testing practices

Week 14: Capstone Project and Review

• Designing and implementing a comprehensive testing strategy for a real-world software system
• Final presentations and peer reviews

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Course Assessment

• Assignments (25%): Hands-on exercises in test automation, fuzzing, and program analysis.
• Paper-based Exam (40%): Theoretical evaluation of advanced testing methodologies.
• Capstone Project (25%): Group project involving the application of advanced testing techniques.
• Participation (10%): Contributions to discussions, code reviews, and peer learning.

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Resources

• Textbooks:
• Fuzzing: Brute Force Vulnerability Discovery by Michael Sutton, Adam Greene, and Pedram Amini
• Introduction to Software Testing by Paul Ammann and Jeff Offutt
• Online Platforms:
• Tools and frameworks such as AFL, libFuzzer, Z3 (solver), and Clang Static Analyzer
• Open-source repositories for testing datasets
• Research Papers:
• Recent studies on advanced testing techniques from top-tier conferences (ICSE, FSE, ASE, ICPC, and ISSTA)

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Prerequisites

• Familiarity with basic software testing principles and techniques.
• Knowledge of programming languages (e.g., Java, Python, C++) and data structures.

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Contact Information

For inquiries, feel free to reach out via my webpage: www.m-zakeri.github.io.