Reyhaneh Jabbarvand

2107 Siebel Center
201 N Goodwin Avenue
Urbana, IL 61801



Welcome to the Intelligent CAT lab! We love to make Code Analysis and Testing more effective by combining recent advances in Artificial Intelligence and symbolic techniques. Here, we don’t just solve problems, but we solve them in a novel, creative, and impactful ways.

Are you interested to purr with us? If so, send an email to the Director of the lab ( to inquiry about open positions.

UIUC students:

  • Advising students
    • Ali Reza Ibrahimzada (PhD, Fall 2022-)
    • Yang Chen (PhD, co-advised with Darko Marinov, Fall 2022-)
    • Changshu Liu (PhD, Fall 2023-)
    • Yuxuan Zhu (PhD, Fall 2023-)

  • Lab visitors
    • Sri Ram Eswaran (MS, Fall 2023-)
    • Nancy Wang (Undergrad, CS STARS program, Fall 2023-)
    • Dylan Zhang (PhD, Fall 2023)
    • Hossein Arjomandi (MS, Fall 2022-Spring 2023)
    • Palak Kotwani (Undergrad, Summer 2022)
    • Eesha Ramkumar (Undergrad, Summer 2022)
    • Anthony Huerta (Undergrad, GearUP program, Summer 2021)
    • Swathi Ram (Undergrad, Spring 2021)


Visiting students (UIUC Software Engineering Summer Research Program):

  • Undergrad students
    • Alperen Yildiz (Sabanci Unievrsity, Turkey, Summer 2021-present)
    • Daim Armaghan (Lahore University of Management Sciences, Pakistan, Summer 2022)
    • Süleyman Ateş (Middle East Technical University, Turkey, Summer 2022)
    • Emirhan Bayar (Middle East Technical University, Turkey, Summer 2022)
    • Emin Cihangeri (Middle East Technical University, Turkey, Summer 2022)
    • Furkan Genç (Middle East Technical University, Turkey, Summer 2022)
    • Chung-En Ho (National Taiwan University, Taiwan, Summer 2022)
    • Yung-Wen Huang (National Taiwan University, Taiwan, Summer 2022)
    • Mustafa Mert Köse (Middle East Technical University, Turkey, Summer 2022)
    • Selim Kuzuku (Middle East Technical University, Turkey, Summer 2022)
    • Julfikar Mahbub (BRAC University, Bangladesh, Summer 2022)
    • Manami Mondal (IIT Kharagpur, India, Summer 2022)
    • Mohamed Moustafa (German Internation University, Egypt, Summer 2022)
    • Onat Özdemir (Middle East Technical University, Turkey, Summer 2022)
    • Eren Polat (Bilkent University, Turkey, Summer 2022)
    • Trusha Talati (Sardar Patel Institute of Technology, India, Summer 2022)
    • Zelin Wang (UC Berkeley/Nanjiang University, China, Summer 2022)
    • Lily Yang (University of Waterloo, CA, Summer 2022)
    • Gorkay Aydemir (Middle East Technical University, Turkey, Summer 2021)-Next: PhD at EPFL
    • Oussama Bezzad (Al Akhawayn University, Morocco, Summer 2021)
    • Mehmet Arif Demirtas (Istanbul Technical University, Turkey, Summer 2021)
    • Said Gurbuz (Middle East Technical University, Turkey, Summer 2021)
    • Ali Reza Ibrahimzada (Marmara University, Turkey, Summer 2021-Summer 2022)-Next: PhD at UIUC
    • Elif Ecem Samlioglu (Sabanci University, Turkey, Summer 2021)
    • Hui Li Tao (Zhejiang University, China, Summer 2021): MS at Cornell Tech
    • Dilara Tekinoglu (Sabanci University, Turkey, Summer 2021)-Next: PhD at UMass Amherst
    • Yigit Varli (Middle East Technical University, Turkey, Summer 2021)
    • Qinchen Yang (NYU, Summer 2021)-Next: PhD at Rutgers
    • Aral Yekta Yarimca (Middle East Technical University, Turkey, Summer 2021)
  • High School students
    • Ryan Rong (Peddie High School, NJ, Summer 2022)
    • Ansh Gupta (Washington High School, CA, Summer 2021)-Next: Undergrad at Georgia Tech


Current Projects:

  • Test Oracle Automation

Given an input to the software, the challenge of distinguishing the expected, correct behavior from the incorrect one is called test oracle problem. Absence of automated test oracles demands human to decide whether observed behavior and generated output is correct, increasing the cost of testing to a great extent. Intelligent CATs are working on several projects to advance the research and practice of test oracle automation.

Papers: [FSE'20], [FSE'22]


Past Projects:

  • Energy testing of Android apps

The rising popularity of mobile apps deployed on battery-constrained devices has motivated the need for effective and efficient energy-aware testing techniques. However, currently there is a lack of test generation tools for exercising the energy properties of apps. Automated test generation is not useful without tools that help developers to measure the quality of the tests. Additionally, the collection of tests generated for energy testing could be quite large, as it may involve a test suite that covers all the energy-greedy parts of the code under different use cases. Thereby, there is a need for techniques to manage the size of test suite, while maintaining its effectiveness in revealing energy defects. This research proposes a four-pronged approach to advance energy testing for mobile applications, including techniques for energy-aware test input generation, energy-aware test oracle construction, energy-aware test-suite adequacy assessment, and energy-aware test-suite minimization.
Papers: [FSE'20], [ICSE'19], [ICSE'18], [FSE'17], [ISSTA'16]

  • Permission analysis of Android apps

Permissions are the cornerstone for Android security model, as they enable secure access to sensitive resources of the phone. Consequently, improper use of Android permission model can lead to permission-induced issues that disrupt the functional and non-functional behavior of the apps. However, due to the lack of automated tools for detecting such issues, many of those defects are shipped with the final product, which not only dissatisfies end users but also poses security risks to their phones. Without considering the temporal aspects of an attack, state-of-the-art techniques aimed at protecting the users against permission-induced attacks, are prone to have low-coverage in detection and high-disruption in prevention of such attacks. Project Terminator addresses this shortcoming by incorporating the notion of time in both detection and prevention of the attacks. Terminator leverages temporal logic model checking to detect permission-induced threats, and then relies on Android’s dynamic permission mechanism to thwart the identified threats by revoking unsafe permissions. However, such countermeasure, i.e., permission revocation, could itself result in other defects, such as crash, if the target app suffers from dynamic-permission-compatibility issue. To identify such permission-induced compatibility defects, developers need to exhaustively re-execute tests for all possible permission combinations, thereby increasing the time and resources required to test apps. Project PATDroid, is intended to help app developers with this challenge. PATDroid can significantly reduce the testing effort by performing a hybrid program analysis that determines which tests should be executed on what permission combinations.
Papers: [FSE'17], [ICSE'18]

  • Android testing in general

GUI-based testing has been primarily used to examine the functionality and usability of mobile apps. Despite the numerous GUI-based test input generation techniques proposed in the literature, these techniques are still limited by (1) lack of context-aware text inputs; (2) failing to generate expressive tests; and (3) absence of test oracles. To address these limitations, CRAFTDROID leverages information retrieval, along with static and dynamic analysis techniques, to extract the human knowledge from an existing test suite for one app and transfer the test cases and oracles to be used for testing other apps with the similar functionalities. Evaluation of CRAFTDROID on real-world commercial Android apps corroborates its effectiveness by achieving 73% precision and 90% recall on average for transferring both the GUI events and oracles. In addition, 75% of the attempted transfers successfully generated valid and feature-based tests for popular features among apps in the same category.
Papers: [ASE'19]