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Frank Tip

Frank Tip

· Professor

Northeastern University · Software Engineering

Active 1992–2025

h-index44
Citations8.2k
Papers16820 last 5y
Funding$960k

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Amal Ahmed is a professor and the Associate Dean of Graduate Programs at Khoury College of Computer Sciences. Her research focuses on programming languages, with particular attention to semantics, type systems, secure compilation, gradual typing, and software contracts. She is committed to advancing the understanding and development of programming language theory and its applications, contributing to the college's leadership in computer science education and research.

Research topics

  • Computer Science
  • Machine Learning
  • Artificial Intelligence
  • Programming language
  • Software engineering
  • Computer network
  • Distributed computing

Selected publications

  • An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation

    IEEE Transactions on Software Engineering · 2023 · 267 citations

    Senior authorCorresponding

    Unit tests play a key role in ensuring the correctness of software. However, manually creating unit tests is a laborious task, motivating the need for automation. Large Language Models (LLMs) have recently been applied to various aspects of software development, including their suggested use for automated generation of unit tests, but while requiring additional training or few-shot learning on examples of existing tests. This paper presents a large-scale empirical evaluation on the effectiveness…

    PublisherDOI

  • Platform-Independent Dynamic Taint Analysis for JavaScript

    IEEE Transactions on Software Engineering · 2018-10-26 · 55 citations

    article

    Previous approaches to dynamic taint analysis for JavaScript are implemented directly in a browser or JavaScript engine, limiting their applicability to a single platform and requiring ongoing maintenance as platforms evolve, or they require nontrivial program transformations. We present an approach that relies on instrumentation to encode taint propagation as instructions for an abstract machine. Our approach has two key advantages: it is platform-independent and can be used with any existing J…

    PublisherDOI

  • An Empirical Evaluation of Using Large Language Models for Automated Unit Test Generation

    arXiv (Cornell University) · 2023 · 53 citations

    Senior authorCorresponding

    Unit tests play a key role in ensuring the correctness of software. However, manually creating unit tests is a laborious task, motivating the need for automation. Large Language Models (LLMs) have recently been applied to this problem, utilizing additional training or few-shot learning on examples of existing tests. This paper presents a large-scale empirical evaluation on the effectiveness of LLMs for automated unit test generation without additional training or manual effort, providing the LLM…

    PublisherOA PDFDOI

  • Automatic migration from synchronous to asynchronous JavaScript APIs

    Proceedings of the ACM on Programming Languages · 2021 · 20 citations

    Senior authorCorresponding

    The JavaScript ecosystem provides equivalent synchronous and asynchronous Application Programming Interfaces (APIs) for many commonly used I/O operations. Synchronous APIs involve straightforward sequential control flow that makes them easy to use and understand, but their "blocking" behavior may result in poor responsiveness or performance. Asynchronous APIs impose a higher syntactic burden that relies on callbacks, promises, and higher-order functions. On the other hand, their nonblocking beha…

    PublisherOA PDFDOI

  • Stubbifier: debloating dynamic server-side JavaScript applications

    Empirical Software Engineering · 2022-09-20 · 12 citations

    articleSenior author
    PublisherDOI

Recent grants

Frequent coauthors

  • Julian Dolby

    34 shared

  • John K. Field

    University of Liverpool

    22 shared

  • Max Schäfer

    19 shared

  • Gavin Bierman

    18 shared

  • Jens Palsberg

    18 shared

  • Oege de Moor

    18 shared

  • Terrance Chua

    National Heart Centre Singapore

    16 shared

  • Seigo Yasutome

    Osaka Institute of Technology

    16 shared

Labs

  • Programming Research LaboratoryPI

Awards & honors

  • Amazon Scholar (2024)

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