About

T Smith (they/them) is the inaugural Postdoctoral Fellow in Racial Politics at Johns Hopkins University. Their research and writing interests include Black politics, queer theory, Black Feminism, and social movements. They are a scholar of Black political behavior and futurity, with a focus on young Black activists and organizers.

Research topics

• Computer science
• Programming language
• Theoretical computer science
• Algorithm
• Mathematics

Selected publications

• Semantic-Type-Guided Bug Finding

  Proceedings of the ACM on Programming Languages · 2024-10-08 · 2 citations

  articleOpen access

  In recent years, there has been an increased interest in tools that establish incorrectness rather than correctness of program properties. In this work we build on this approach by developing a novel methodology to prove incorrectness of semantic typing properties of functional programs, extending the incorrectness approach to the model theory of functional program typing. We define a semantic type refuter which refutes semantic typings for a simple functional language. We prove our refuter is co-recursively enumerable, and that it is sound and complete with respect to a semantic typing notion. An initial implementation is described which uses symbolic evaluation to efficiently find type errors over a functional language with a rich type system.

  PublisherDOI

• A Pure Demand Operational Semantics with Applications to Program Analysis

  Proceedings of the ACM on Programming Languages · 2024-04-29

  articleOpen access1st authorCorresponding

  This paper develops a novel minimal-state operational semantics for higher-order functional languages that uses only the call stack and a source program point or a lexical level as the complete state information: there is no environment, no substitution, no continuation, etc. We prove this form of operational semantics equivalent to standard presentations. We then show how this approach can open the door to potential new applications: we define a program analysis as a direct finitization of this operational semantics. The program analysis that naturally emerges has a number of novel and interesting properties compared to standard program analyses for higher-order programs: for example, it can infer recurrences and does not need value widening. We both give a formal definition of the analysis and describe our current implementation.

  PublisherDOI

• A Pure Demand Operational Semantics with Applications to Program Analysis

  arXiv (Cornell University) · 2023-10-24

  preprintOpen access1st authorCorresponding

  This paper develops a novel minimal-state operational semantics for higher-order functional languages that uses only the call stack and a source program point or a lexical level as the complete state information: there is no environment, no substitution, no continuation, etc. We prove this form of operational semantics equivalent to standard presentations. We then show how this approach can open the door to potential new applications: we define a program analysis as a direct finitization of this operational semantics. The program analysis that naturally emerges has a number of novel and interesting properties compared to standard program analyses for higher-order programs: for example, it can infer recurrences and does not need value widening. We both give a formal definition of the analysis and describe our current implementation.

  PublisherOA PDFDOI

• Higher-order demand-driven symbolic evaluation

  Proceedings of the ACM on Programming Languages · 2020-08-02 · 5 citations

  articleOpen access

  Symbolic backwards execution (SBE) is a useful variation on standard forward symbolic evaluation; it allows a symbolic evaluation to start anywhere in the program and proceed by executing in reverse to the program start. SBE brings goal-directed reasoning to symbolic evaluation and has proven effective in e.g. automated test generation for imperative languages. In this paper we define DDSE, a novel SBE which operates on a functional as opposed to imperative language; furthermore, it is defined as a natural extension of a backwards-executing interpreter. We establish the soundness of DDSE and define a test generation algorithm for this toy language. We report on an initial reference implementation to confirm the correctness of the principles.

  PublisherOA PDFDOI

• A Set-Based Context Model for Program Analysis

  Lecture notes in computer science · 2020-01-01 · 2 citations

  book-chapter
  PublisherDOI

• Higher-Order Demand-Driven Symbolic Evaluation

  Zenodo (CERN European Organization for Nuclear Research) · 2020-06-29 · 1 citations

  paratextOpen access

  The artifact for the paper includes the source code and a ready-to-use qemu image.

  PublisherDOI

• Higher-order Demand-driven Program Analysis

  ACM Transactions on Programming Languages and Systems · 2019-07-02 · 6 citations

  articleSenior author

  Developing accurate and efficient program analyses for languages with higher-order functions is known to be difficult. Here we define a new higher-order program analysis, Demand-Driven Program Analysis (DDPA), which extends well-known demand-driven lookup techniques found in first-order program analyses to higher-order programs. This task presents several unique challenges to obtain good accuracy, including the need for a new method for demand-driven lookup of non-local variable values. DDPA is flow- and context-sensitive and provably polynomial-time. To efficiently implement DDPA, we develop a novel pushdown automaton metaprogramming framework, the Pushdown Reachability automaton. The analysis is formalized and proved sound, and an implementation is described.

  PublisherDOI

• Joint Training Technical Interoperability (JTTI) Strategy

  2018-08-01

  article
  Publisher

• Erratum to: Formal Methods for Open Object-Based Distributed Systems IV

  IFIP advances in information and communication technology · 2017-01-01 · 1 citations

  erratum1st authorCorresponding
  PublisherDOI

• Relative Store Fragments for Singleton Abstraction

  Lecture notes in computer science · 2017-01-01 · 5 citations

  book-chapterSenior author
  PublisherDOI

Frequent coauthors

• Christian Skalka

  University of Vermont

  17 shared

• Carolyn Talcott

  13 shared

• Yu David Liu

  Binghamton University

  12 shared

• Zachary Palmer

  Swarthmore College

  9 shared

• R. Zhang

  8 shared

• Ian A. Mason

  SRI International

  8 shared

• Valery Trifonov

  7 shared

• Jonathan Eifrig

  Johns Hopkins University

  6 shared