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Events for April 30, 2020

  • PhD Defense -

    Thu, Apr 30, 2020 @ 10:00 AM - 01:00 PM

    Thomas Lord Department of Computer Science

    University Calendar

    Title: Detecting SQL Antipatterns in Mobile Applications

    PhD Candidate: Yingjun Lyu


    William GJ Halfond (Chair)
    Neno Medvidovic
    Chao Wang
    Jyo Deshmukh
    Sandeep Gupta

    Local databases underpin important features in many mobile applications. However, bad programming practices of using database operations, also called SQL antipatterns, can introduce high resource consumption, affect the responsiveness, and undermine the security of a mobile application.
    In my dissertation, I designed and evaluated a framework, called SAND, to detect SQL antipatterns effectively and efficiently in mobile apps. The framework abstracts away the interactions between the application and the database. It provides a language that allows the framework users to query abstractions of application-database relationships and specify SQL antipattern detection tasks. To determine what kinds of application-database relationships should be abstracted, I first conducted a systematic literature review to collect a comprehensive list of SQL antipatterns and their detection approaches. I then analyzed the collected detection approaches and derived the abstractions from them. In order to extract the abstractions from the database access code, I developed a range of static analysis techniques that can analyze the database access code effectively and efficiently. Using experiments on the framework implementation for Android, I showed that SAND can be used to compactly (in 12-74 lines of code) specify SQL antipattern detection tasks previously reported in the literature. These detectors built on top of SAND precisely identified thousands of instances of SQL antipatterns with a precision of at least 99.4%. These detectors were also fast as applying eleven detectors only took an average of forty-one seconds per app. Overall, these results are positive and indicate that my framework can detect all kinds of SQL antipatterns effectively and efficiently in mobile apps.

    WebCast Link: https://usc.zoom.us/j/94586333967

    Audiences: Everyone Is Invited

    Contact: Lizsl De Leon

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  • Astani Civil and Environmental Engineering Seminar

    Thu, Apr 30, 2020 @ 02:00 PM - 03:00 PM

    Sonny Astani Department of Civil and Environmental Engineering

    Conferences, Lectures, & Seminars

    Speaker: Dr. Rui Huang, University of Texas, Austin

    Talk Title: TBA

    Host: Dr. Qiming Wang

    Audiences: Everyone Is Invited

    Contact: Evangeline Reyes

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  • Undergraduate Admission Virtual Information Session

    Thu, Apr 30, 2020 @ 02:00 PM - 03:00 PM

    Viterbi School of Engineering Undergraduate Admission

    Workshops & Infosessions

    Our virtual information session is a live presentation from a USC Viterbi admission counselor designed for prospective first-year students and their family members to learn more about the USC Viterbi undergraduate experience.Our session will cover an overview of our undergraduate engineering programs, the application process, and more on student life.Guests will be able to ask questions and engage in further discussion toward the end of the session.

    Please register here!

    Audiences: Everyone Is Invited

    Contact: Viterbi Admission

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  • CAIS++ Spring 2020 Projects Showcase

    Thu, Apr 30, 2020 @ 07:00 PM - 08:00 PM

    Thomas Lord Department of Computer Science

    Student Activity

    We are CAIS++, the undergraduate branch of USC's Center for Artificial Intelligence in Society (CAIS). Our mission is to advance AI for social good, and our group of 50+ students works with professors, startups, and community organizations to develop cutting-edge AI solutions for societal problems.

    We're inviting you to our Spring 2020 Projects Showcase on April 30 from 7-8:00 pm on Zoom (link below). Our student teams will be presenting the AI projects that they have worked on this semester. Some of the projects that will be presented at showcase include developing machine learning approaches for
    *Diagnosing Kawasaki disease
    *Generalized gene sequencing classification
    *Detecting deepfakes and manipulated media
    *Improving building security systems

    We will be recruiting a new cohort of undergraduates in Fall 2020, so coming to our showcase is a great way to learn about CAIS++ and see the type of work we do!

    If you're able to attend, please RSVP to our Facebook event:

    and join us on this Zoom link:
    (zoom link was emailed directly to CS community on April 20th)

    The CAIS++ Team

    Location: Zoom

    Audiences: Everyone Is Invited

    Contact: Ryan Rozan

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