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Integrating Declarative Static Analysis With Neural Models of Code / Pardis Pashakhanloo.
- Format:
- Book
- Thesis/Dissertation
- Author/Creator:
- Pashakhanloo, Pardis, author.
- Language:
- English
- Subjects (All):
- Computer science.
- Information science.
- Computer and Information Science--Penn dissertations.
- Penn dissertations--Computer and Information Science.
- Local Subjects:
- Computer science.
- Information science.
- Computer and Information Science--Penn dissertations.
- Penn dissertations--Computer and Information Science.
- Physical Description:
- 1 online resource (132 pages)
- Distribution:
- Ann Arbor : ProQuest Dissertations & Theses, 2023
- Contained In:
- Dissertations Abstracts International 84-12A.
- Place of Publication:
- [Philadelphia, Pennsylvania] : University of Pennsylvania, 2022.
- Language Note:
- English
- Summary:
- In recent years, deep learning techniques have made remarkable strides in solving a variety of program understanding challenges. The successful application of these techniques to a given task depends heavily on how the source code is represented by the deep neural network. Designing a suitable representation for a newly created task involves many challenges. It is necessary, among other things, to understand the implementation of other functions or modules in a project that may be spread out across a large lexical area. In addition, determining which components and features to include in order to enrich the representation is a challenge. In this dissertation, the challenges of code representation are addressed by proposing to systematically represent programs as relational databases, introducing a graph walk mechanism to remove unrelated context from large relational graphs, and describing a language for specifying tasks and program analysis queries to tailor neural code-reasoning models. A detailed analysis shows the presented techniques are superior to state-of-the-art in a variety of aspects, such as performance, robustness, and interpretability.
- Notes:
- Source: Dissertations Abstracts International, Volume: 84-12, Section: A.
- Advisors: Naik, Mayur; Committee members: Bastani, Osbert; Thau Loo, Boon; Lee, Insup; Maniatis, Petros.
- Department: Computer and Information Science.
- Ph.D. University of Pennsylvania 2023.
- Local Notes:
- School code: 0175
- ISBN:
- 9798379754686
- Access Restriction:
- Restricted for use by site license.
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