Posts

Breakthroughs in DNN Verification to tackle richer properties, bigger and more complex DNNs, ...

Program Analysis Meets Autonomous Robots - ICSE 2020 technical briefing

I was invited to give a technical briefing at ICSE 2020 on the work our team has been doing at the intersection of robotics and software engineering. The video offers a good summary of our progress and directions.

FSE Test of Time Award

The Foundations of Software Engineering Test of Time Award recognizes highly influential papers published ten years ago in ESEC or FSE. …

State of ICSE

My last Report as ICSE Steering Committee Chair …

Adios to UNL

I am leaving UNL to join the University of Virginia in the Fall 2018. I have only gratitude to my colleagues and staff at the …

Think Like an Immigrant

I was honored to give the UNL graduate commencement speech in December 2016. Perhaps not good enough to make it to the “Best …

Teaching

Fall 2021: CS6888: Program Analysis and its Applications

This course explores state-of-the-art automated analysis techniques and their application. Topics include dynamic and static program analysis techniques, test generation, fault localization and debugging, model inferencing, and model checking. The course includes the utilization of tools and the development of a class project that builds and improves on existing techniques.

Spring 2021: Robotics for Software Engineers

Developing software for robot systems is challenging as they must sense, actuate, and represent the physical world. Sensing the physical world is usually noisy, actuating in and on the world is often inaccurate, and the knowledge and representation of the world is incomplete and uncertain. In this class we explore basic approaches to cope with those challenges. You will learn abstractions, architectures, libraries, verification and validation approaches, simulation, and frameworks and tools to perform robot activities like motion, navigation, perception, planning, and interaction. The expectation is that his course opens up new career options in robotics for computer science students.

Fall 2020: Program Analysis and its Applications
Covid-19 Adjustments (subject to change): this class will be online, mostly with synchronous lectures and labs.

This course explores state-of-the-art automated analysis techniques and their application. Topics include dynamic and static program analysis techniques, test generation, fault localization and debugging, model inferencing, and model checking. The course includes the utilization of tools and the development of a class project that builds and improves on existing techniques.

Spring 2020: Robotics for Software Engineers
Covid-19 Adjustments (subject to change): check course website for revised schedule and expectations.

Developing software for robot systems is challenging as they must sense, actuate, and represent the physical world. Sensing the physical world is usually noisy, actuating in and on the world is often inaccurate, and the knowledge and representation of the world is incomplete and uncertain. In this class we explore basic approaches to cope with those challenges. You learn to use abstractions, architectures, libraries, verification and validation approaches, simulation, and frameworks and tools to perform robot activities like motion, navigation, perception, planning, and interaction. The expectation is that his course opens up new career options in robotics for computer science students.

Fall 2019: Analysis of Software Engineering Artifacts

This course explores state-of-the-art automated techniques that make the analysis of various software artifacts, from models to code, cost-effective. Topics include dynamic and static program analysis techniques, test generation, fault localization and debugging, model inferencing, and model checking. The course includes the utilization of the latest research tools and the development of a class project that builds and improves on existing techniques.

Spring 2019: Software Engineering for Robotics

This was the first offering of this course covering specialized software engineering approaches, techniques, and tools for the development of robotic systems. Topics included domain-specific architectures and design principles, modeling robot and environmental states, abstractions for mapping, localization, and navigation, planning, control structures and properties, filtering mechanisms for sensors and actuators, and analysis, verification, and simulation for dependability.

Students

References: (A) Advisor, (CA) Co-Advisor

Current Students

PhDs
  • Carl Hildebrandt (A)
  • David Shriver (CA)
  • Meriel Stein (A)
  • Trey Woodlief (CA)
  • Felipe Toledo (A)
  • Chris Morse (A)

Alumni

If you should be a part of this list please send me an email!

PhDs
  1. Ajay Shankar (CA, Ph.D:) 821)
  2. John-Paul Ore (CA, Ph.D:) 819)
  3. Wei Sun (CA, PhD: 1217)
  4. Katie Stolee (A, PhD: 82013)
  5. Pingyu Zhang (A, PhD: 82013)
  6. Rahul Purandare (Post Doc CA, 52013)
  7. Zhimin Wang (A: 82008)
  8. Mark Fisher (CA: 82008)
  9. Joe RuthRuff (CA: 52008)
  10. Madeleine Hardojo(A: 52004)
MS
  1. Andrew Elsey (CA, 521)
  2. Balaji Balasubrmanian (CA, 1218)
  3. Jingjing Liang (CA, 518)
  4. David Shriver (A, 518)
  5. Evan Beachly (CA, 1217)
  6. Nishant Sharma (CA, 1017)
  7. Matias Waterloo (A, 816)
  8. Adam Taylor (A, 122015)
  9. Eric Rizzi (CA, 82015)
  10. Hengle Jiang (A, 52014)
  11. Heath Roehr (CA, MS: 52013)
  12. Lucy Wang (CA, MS: 82012)
  13. Javier Darsie (A, 82012)
  14. Rahul Purandare (CM, Phd 42011)
  15. Xin Guo (REU, 52011)
  16. Katie Stolee (A, MS: 82010)
  17. Madeleine Diep (A: 42009)
  18. Matt Jorde (A: 52008)
  19. Padma Ashokumar (CA: 122007)
  20. Hui Nee Chin (A: 82007)
  21. Andhy Koesnandar (CA: 52007)
  22. Sandeep Lingam (A: 52006)
  23. Bhuvana Gopal (A: 12006)
  24. Fidel Knowcha (A: 82004)
  25. Ram Kalyan Chilakamarri (A: 52004)
  26. Sameera Reddy(A:72004)
  27. Satya Kanduri (A: 72003)
  28. Praveen Kallakuri (A: 122002)
  29. Srikanth Karre (A: 112002)
  30. Xin Liu (A: 52002)
  31. Smita Narla (A: 82001)
  32. David Gable (A: 42001)
  33. Jian Tang (P: 52001)
  34. Lingyun Wang (P: 52001)
  35. Luyin Zhao (P: 52001)

Undergraduate Research or Project Advising

  1. Avaneen Pinninti
  2. Joanna Zhao
  3. Michael Chinn
  4. Nate Olsen
  5. Derek Tan
  6. Ethan Butt
  7. Mark Nail
  8. Chris Laney
  9. Daniel Lobos
  10. Josh Reed
  11. Nick Steinbaugh
  12. Jon Dokulil
  13. Khoa Le
  14. Tuan Duc Dao
  15. David Friberg
  16. Jared Bakewell
  17. Binh Huynh
  18. Shane Geiger
  19. Ted Whaler
  20. Eric Gruber

Contact