• Login
    View Item 
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    •   SMARTech Home
    • Georgia Tech Theses and Dissertations
    • Georgia Tech Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Combining logical and probabilistic reasoning in program analysis

    Thumbnail
    View/Open
    ZHANG-DISSERTATION-2017.pdf (2.493Mb)
    Date
    2017-08-23
    Author
    Zhang, Xin
    Metadata
    Show full item record
    Abstract
    Software is becoming increasingly pervasive and complex. These trends expose masses of users to unintended software failures and deliberate cyber-attacks. A widely adopted solution to enforce software quality is automated program analysis. Existing program analyses are expressed in the form of logical rules that are handcrafted by experts. While such a logic-based approach provides many benefits, it cannot handle uncertainty and lacks the ability to learn and adapt. This in turn hinders the accuracy, scalability, and usability of program analysis tools in practice. We seek to address these limitations by proposing a methodology and framework for incorporating probabilistic reasoning directly into existing program analyses that are based on logical reasoning. The framework consists of a frontend, which automatically integrates probabilities into a logical analysis by synthesizing a system of weighted constraints, and a backend, which is a learning and inference engine for such constraints. We demonstrate that the combined approach can benefit a number of important applications of program analysis and thereby facilitate more widespread adoption of this technology. We also describe new algorithmic techniques to solve very large instances of weighted constraints that arise not only in our domain but also in other domains such as Big Data analytics and statistical AI.
    URI
    http://hdl.handle.net/1853/59200
    Collections
    • College of Computing Theses and Dissertations [1191]
    • Georgia Tech Theses and Dissertations [23877]

    Browse

    All of SMARTechCommunities & CollectionsDatesAuthorsTitlesSubjectsTypesThis CollectionDatesAuthorsTitlesSubjectsTypes

    My SMARTech

    Login

    Statistics

    View Usage StatisticsView Google Analytics Statistics
    facebook instagram twitter youtube
    • My Account
    • Contact us
    • Directory
    • Campus Map
    • Support/Give
    • Library Accessibility
      • About SMARTech
      • SMARTech Terms of Use
    Georgia Tech Library266 4th Street NW, Atlanta, GA 30332
    404.894.4500
    • Emergency Information
    • Legal and Privacy Information
    • Human Trafficking Notice
    • Accessibility
    • Accountability
    • Accreditation
    • Employment
    © 2020 Georgia Institute of Technology