+publisher:"University of Texas – Austin" +contributor:("Dillig, Isil")

1. Harrison, Amelia J. Formal methods for answer set programming.

Degree: PhD, Computer Science, 2018, University of Texas – Austin

► Answer set programming (ASP) is a declarative programming paradigm for the design and implementation of knowledge-intensive applications, particularly useful for modeling problems involving combinatorial search.… (more)

Subjects/Keywords: Logic programming; Formal methods

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APA (6^th Edition):

Harrison, A. J. (2018). Formal methods for answer set programming. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/63692

Chicago Manual of Style (16^th Edition):

Harrison, Amelia J. “Formal methods for answer set programming.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed January 26, 2021. http://hdl.handle.net/2152/63692.

MLA Handbook (7^th Edition):

Harrison, Amelia J. “Formal methods for answer set programming.” 2018. Web. 26 Jan 2021.

Vancouver:

Harrison AJ. Formal methods for answer set programming. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Jan 26]. Available from: http://hdl.handle.net/2152/63692.

Council of Science Editors:

Harrison AJ. Formal methods for answer set programming. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/63692

2. Wang, Xinyu. An efficient programming-by-example framework.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/5854

► Due to the ubiquity of computing, programming has started to become an essential skill for an increasing number of people, including data scientists, financial analysts,… (more)

Subjects/Keywords: Programming languages; Program synthesis

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APA (6^th Edition):

Wang, X. (2019). An efficient programming-by-example framework. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/5854

Chicago Manual of Style (16^th Edition):

Wang, Xinyu. “An efficient programming-by-example framework.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed January 26, 2021. http://dx.doi.org/10.26153/tsw/5854.

MLA Handbook (7^th Edition):

Wang, Xinyu. “An efficient programming-by-example framework.” 2019. Web. 26 Jan 2021.

Vancouver:

Wang X. An efficient programming-by-example framework. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Jan 26]. Available from: http://dx.doi.org/10.26153/tsw/5854.

Council of Science Editors:

Wang X. An efficient programming-by-example framework. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/5854

University of Texas – Austin

3. -7819-4835. Automatic static analysis of software performance.

Degree: PhD, Computer science, 2016, University of Texas – Austin

URL: http://hdl.handle.net/2152/40279

► Performance is a critical component of software quality. Software performance can have drastic repercussions on an application, frustrating its users, breaking the functionality of its… (more)

Subjects/Keywords: Static analysis; Security; Performance; Program analysis; Denial-of-service; Privacy

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APA (6^th Edition):

-7819-4835. (2016). Automatic static analysis of software performance. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/40279

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Author name may be incomplete

Chicago Manual of Style (16^th Edition):

-7819-4835. “Automatic static analysis of software performance.” 2016. Doctoral Dissertation, University of Texas – Austin. Accessed January 26, 2021. http://hdl.handle.net/2152/40279.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-7819-4835. “Automatic static analysis of software performance.” 2016. Web. 26 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7819-4835. Automatic static analysis of software performance. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2016. [cited 2021 Jan 26]. Available from: http://hdl.handle.net/2152/40279.

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Author name may be incomplete

Council of Science Editors:

-7819-4835. Automatic static analysis of software performance. [Doctoral Dissertation]. University of Texas – Austin; 2016. Available from: http://hdl.handle.net/2152/40279

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Author name may be incomplete

4. -5365-808X. An experimental evaluation and possible extensions of SyPet.

Degree: MSin Engineering, Electrical and Computer Engineering, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/62665

► Program synthesis is an automated programming technique that automatically constructs a program which satisfies given specifications. SyPet is a recently published novel component-based synthesis tool… (more)

Subjects/Keywords: Program synthesis; Program repair

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APA (6^th Edition):

-5365-808X. (2017). An experimental evaluation and possible extensions of SyPet. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/62665

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Chicago Manual of Style (16^th Edition):

-5365-808X. “An experimental evaluation and possible extensions of SyPet.” 2017. Masters Thesis, University of Texas – Austin. Accessed January 26, 2021. http://hdl.handle.net/2152/62665.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-5365-808X. “An experimental evaluation and possible extensions of SyPet.” 2017. Web. 26 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-5365-808X. An experimental evaluation and possible extensions of SyPet. [Internet] [Masters thesis]. University of Texas – Austin; 2017. [cited 2021 Jan 26]. Available from: http://hdl.handle.net/2152/62665.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-5365-808X. An experimental evaluation and possible extensions of SyPet. [Masters Thesis]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/62665

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

University of Texas – Austin

5. Feng, Yu, Ph. D. Program synthesis using statistical models and logical reasoning.

Degree: PhD, Computer Science, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/68452

► Complex APIs in new frameworks (Spark, R, TensorFlow, etc) have imposed steep learning curves on everyone, especially for people with limited programming backgrounds. For instance,… (more)

Subjects/Keywords: Program synthesis; Logical reasoning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6^th Edition):

Feng, Yu, P. D. (2018). Program synthesis using statistical models and logical reasoning. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68452

Chicago Manual of Style (16^th Edition):

Feng, Yu, Ph D. “Program synthesis using statistical models and logical reasoning.” 2018. Doctoral Dissertation, University of Texas – Austin. Accessed January 26, 2021. http://hdl.handle.net/2152/68452.

MLA Handbook (7^th Edition):

Feng, Yu, Ph D. “Program synthesis using statistical models and logical reasoning.” 2018. Web. 26 Jan 2021.

Vancouver:

Feng, Yu PD. Program synthesis using statistical models and logical reasoning. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2018. [cited 2021 Jan 26]. Available from: http://hdl.handle.net/2152/68452.

Council of Science Editors:

Feng, Yu PD. Program synthesis using statistical models and logical reasoning. [Doctoral Dissertation]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68452

6. Yaghmazadeh, Navid. Automated synthesis of data extraction and transformation programs.

Degree: PhD, Computer Science, 2017, University of Texas – Austin

URL: http://hdl.handle.net/2152/68138

► Due to the abundance of data in today’s data-rich world, end-users increasingly need to perform various data extraction and transformation tasks. While many of these… (more)

▼ Due to the abundance of data in today’s data-rich world, end-users increasingly need to perform various data extraction and transformation tasks. While many of these tedious tasks can be performed in a programmatic way, most end-users lack the required programming expertise to automate them and end up spending their valuable time in manually performing various data- related tasks. The field of program synthesis aims to overcome this problem by automatically generating programs from informal specifications, such as input-output examples or natural language. This dissertation focuses on the design and implementation of new systems for automating important classes of data transformation and extraction tasks. It introduces solutions for automating data manipulation tasks on fully- structured data formats like relational tables, or on semi-structured formats such as XML and JSON documents. First, we describe a novel algorithm for synthesizing hierarchical data transformations from input-output examples. A key novelty of our approach is that it reduces the synthesis of tree transformations to the simpler problem of synthesizing transformations over the paths of the tree. We also describe a new and effective algorithm for learning path transformations that combines logical SMT-based reasoning with machine learning techniques based on decision trees. Next, we present a new methodology for learning programs that migrate tree-structured documents to relational table representations from input-output examples. Our approach achieves its goal by decomposing the synthesis task to two subproblems of (A) learning the column extraction logic, and (B) learning the row extraction logic. We propose a technique for learning column extraction programs using deterministic finite automata, and a new algorithm for predicate learning which combines integer linear programing and logic minimization. Finally, we address the problem of automating data extraction tasks from natural language. Specifically, we focus on data retrieval from relational databases and describe a novel approach for learning SQL queries from English descriptions. The method we describe is fully automatic and database-agnostic (i.e., does not require customization for each database). Our method combines semantic parsing techniques from the NLP community with novel programming languages ideas involving probabilistic type inhabitation and automated sketch repair. Advisors/Committee Members: Dillig, Isil (advisor), Pingali, Keshav (committee member), Mooney, Raymond (committee member), Solar-Lezama, Armando (committee member).

Subjects/Keywords: Program synthesis; Programming-by-examples; Programming-by-natural-language; Databases

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APA (6^th Edition):

Yaghmazadeh, N. (2017). Automated synthesis of data extraction and transformation programs. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68138

Chicago Manual of Style (16^th Edition):

Yaghmazadeh, Navid. “Automated synthesis of data extraction and transformation programs.” 2017. Doctoral Dissertation, University of Texas – Austin. Accessed January 26, 2021. http://hdl.handle.net/2152/68138.

MLA Handbook (7^th Edition):

Yaghmazadeh, Navid. “Automated synthesis of data extraction and transformation programs.” 2017. Web. 26 Jan 2021.

Vancouver:

Yaghmazadeh N. Automated synthesis of data extraction and transformation programs. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2017. [cited 2021 Jan 26]. Available from: http://hdl.handle.net/2152/68138.

Council of Science Editors:

Yaghmazadeh N. Automated synthesis of data extraction and transformation programs. [Doctoral Dissertation]. University of Texas – Austin; 2017. Available from: http://hdl.handle.net/2152/68138

University of Texas – Austin

7. -7290-5050. Broad-based side-channel defenses for modern microprocessors.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/2661

► Private or confidential information is used in a wide variety of applications, not just including implementations of cryptographic algorithms but also including machine-learning libraries, databases,… (more)

▼ Private or confidential information is used in a wide variety of applications, not just including implementations of cryptographic algorithms but also including machine-learning libraries, databases, and parsers. However, even after using techniques such as encryption, authentication, and isolation, it is difficult to maintain the privacy or confidentiality of such information due to so-called side channels, with which attackers can infer sensitive information by monitoring program execution. Various side channels exist such as execution time, power consumption, exceptions, or micro-architectural components such as caches and branch predictors, and such side channels have been used to steal intellectual property, financial information, and sensitive document contents. Although numerous solutions exist for closing side channels, they are point solutions, since each solution closes an isolated set of side channels. In this dissertation, we present three compiler-based solutions – Raccoon, Escort, and Vantage – for closing digital side channels (such as the cache, address trace, and branch predictor side channels) that carry information over discrete bits, and for mitigating the a non-digital side channel, specifically, the power side channel. Additionally, our compilers are customizable, since they permit the defense to be tailored to the threat model, to the program, and to the microarchitecture. More broadly, our solutions augment the compiler with information about the lower layers of the computing stack, so that the compiler is aware of potential side channels and so that the compiler can rewrite programs to avoid leaking information through those side channels. In doing so, our solutions define new abstractions that enable the compiler to reason about the program's impact on timing, power consumption, and other similar side channels. Through such abstractions, our compilers detect and prevent a broad set of digital and non-digital leakage on modern microarchitectures. Advisors/Committee Members: Lin, Yun Calvin (advisor), Tiwari, Mohit (advisor), Dillig, Isil (committee member), Witchel, Emmett (committee member), Evans, David (committee member).

Subjects/Keywords: Side-channel defenses

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APA (6^th Edition):

-7290-5050. (2019). Broad-based side-channel defenses for modern microprocessors. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/2661

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Chicago Manual of Style (16^th Edition):

-7290-5050. “Broad-based side-channel defenses for modern microprocessors.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed January 26, 2021. http://dx.doi.org/10.26153/tsw/2661.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

MLA Handbook (7^th Edition):

-7290-5050. “Broad-based side-channel defenses for modern microprocessors.” 2019. Web. 26 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-7290-5050. Broad-based side-channel defenses for modern microprocessors. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Jan 26]. Available from: http://dx.doi.org/10.26153/tsw/2661.

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Author name may be incomplete

Council of Science Editors:

-7290-5050. Broad-based side-channel defenses for modern microprocessors. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/2661

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Author name may be incomplete

8. -2178-1988. Program analysis techniques for algorithmic complexity and relational properties.

Degree: PhD, Computer Science, 2019, University of Texas – Austin

URL: http://dx.doi.org/10.26153/tsw/2181

► Analyzing standard safety properties of a given program has traditionally been the primary focus of the program analysis community. Unfortunately, there are still many interesting… (more)

Subjects/Keywords: Complexity testing; Optimal program synthesis; Fuzzing; Genetic programming; Performance bug; Vulnerability detection; Side channel; Static analysis; Relational verification; Reinforcement learning; Policy gradient

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APA (6^th Edition):

-2178-1988. (2019). Program analysis techniques for algorithmic complexity and relational properties. (Doctoral Dissertation). University of Texas – Austin. Retrieved from http://dx.doi.org/10.26153/tsw/2181

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Chicago Manual of Style (16^th Edition):

-2178-1988. “Program analysis techniques for algorithmic complexity and relational properties.” 2019. Doctoral Dissertation, University of Texas – Austin. Accessed January 26, 2021. http://dx.doi.org/10.26153/tsw/2181.

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MLA Handbook (7^th Edition):

-2178-1988. “Program analysis techniques for algorithmic complexity and relational properties.” 2019. Web. 26 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-2178-1988. Program analysis techniques for algorithmic complexity and relational properties. [Internet] [Doctoral dissertation]. University of Texas – Austin; 2019. [cited 2021 Jan 26]. Available from: http://dx.doi.org/10.26153/tsw/2181.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-2178-1988. Program analysis techniques for algorithmic complexity and relational properties. [Doctoral Dissertation]. University of Texas – Austin; 2019. Available from: http://dx.doi.org/10.26153/tsw/2181

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University of Texas – Austin

9. -3724-0839. Zero-One Integer Linear Programming for program synthesis: 0-1 Integer Linear Programming for program synthesis.

Degree: MSin Computer Sciences, Computer Science, 2018, University of Texas – Austin

URL: http://hdl.handle.net/2152/68193

► Program synthesis techniques generate code automatically for a given specification, while code reuse techniques adapt existing code to suit the user's requirements. These methods can… (more)

Subjects/Keywords: Program synthesis; Code reuse; ILP; Integer Linear Programming

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APA (6^th Edition):

-3724-0839. (2018). Zero-One Integer Linear Programming for program synthesis: 0-1 Integer Linear Programming for program synthesis. (Masters Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/68193

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Chicago Manual of Style (16^th Edition):

-3724-0839. “Zero-One Integer Linear Programming for program synthesis: 0-1 Integer Linear Programming for program synthesis.” 2018. Masters Thesis, University of Texas – Austin. Accessed January 26, 2021. http://hdl.handle.net/2152/68193.

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MLA Handbook (7^th Edition):

-3724-0839. “Zero-One Integer Linear Programming for program synthesis: 0-1 Integer Linear Programming for program synthesis.” 2018. Web. 26 Jan 2021.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Vancouver:

-3724-0839. Zero-One Integer Linear Programming for program synthesis: 0-1 Integer Linear Programming for program synthesis. [Internet] [Masters thesis]. University of Texas – Austin; 2018. [cited 2021 Jan 26]. Available from: http://hdl.handle.net/2152/68193.

Note: this citation may be lacking information needed for this citation format:
Author name may be incomplete

Council of Science Editors:

-3724-0839. Zero-One Integer Linear Programming for program synthesis: 0-1 Integer Linear Programming for program synthesis. [Masters Thesis]. University of Texas – Austin; 2018. Available from: http://hdl.handle.net/2152/68193

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