Angello Astorga Angello Astorga

PhD Student
Department of Computer Science
University of Illinois at Urbana-Champaign
Email: aastorg2 AT illinois DOT edu

I am a PhD student in the department of computer science at the University of Illinois at Urbana-Champaign within the Programming Languages, Formal Methods, and Software Engineering (PL-FM-SE) area. I am co-advised by professor Tao Xie and professor Madhusudan Parthasarathy. My research interests are in software testing, program synthesis and machine learning. My current research focuses on building robust testing-based learning frameworks for synthesizing specifications.     

I obtained a Bachelor of Science (B.S.) in Computer Science and Engineering with Magna Cum Laude Honors from The Ohio State University. During my time as an undergraduate, I participated in the Summer Research Opportunities Program (SROP) where I engaged in rigourous research experiences. This includes a stint at Purdue University with Professor Xiangyu Zhang and at the University of Iowa with Professor Aaron Stump.

  1. Yi Qin, Tao Xie, Chang Xu, Angello Astorga, and Jian Lu.
    CoMID: Context-based Multi-invariant Detection for Monitoring Cyber-Physical Software.
    IEEE Transactions on Reliability (TR), To appear.
    Download: [PDF]
  2. Angello Astorga, Madhusudan Parthasarathy, Shambwaditya Saha, and Tao Xie.
    Learning Stateful Preconditions Modulo a Test Generator.
    In Proceedings of ACM SIGPLAN Conference on Programming Language Design and Implementation
    (PLDI 2019), Phoenix, Arizona, June 2019.
    Download: [PDF]
  3. Angello Astorga, Siwakorn Srisakaokul, Xusheng Xiao, and Tao Xie.
    Preinfer: Automatic Inference of Preconditions via Symbolic Analysis.
    In Proceedings of the 48th IEEE/IFIP International Conference on Dependable Systems and Networks
    (DSN 2018), Luxemborg, June 2018.
    Download: [PDF]

  4. Siwakorn Srisakaokul, Zhengkai Wu, Angello Astorga, Oreoluwa Alebiosu, and Tao Xie.
    Multiple-Implementation Testing of Supervised Learning Software.
    In Proceedings of the AAAI-18 Workshop on Engineering Dependable and Secure Machine Learning Systems
    (EDSMLS 2018) , co-located with AAAI 2018, co-located with , New Orleans, LA, Feburary 2018.
    Download: [PDF]

  5. Adrian Clark, Jonathan Wells, Angello Astorga, Andrew Xie, Jalen Coleman-Lands, and Tao Xie.
    Preliminary Analysis of Contestant Performance for a Code Hunt Contest.
    In Proceedings of the 8th Workshop on Evaluation and Usability of Programming Languages and Tools
    (PLATEAU 2017), Vancouver, Canada, October 2017.
    Download: [PDF] [Slides]