World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
56
Citations
10411
World Ranking
4139
National Ranking
1954

Overview

Jane Cleland-Huang is affiliated with the University of Notre Dame in the United States and has contributed extensively to the field of computer science, with a focus on software engineering and related subfields. Their work spans multiple domains including software reliability, artificial intelligence, aerospace engineering, and human-automation interaction.

Their research encompasses the following main topics:

  • Software Engineering Research
  • Software Reliability and Analysis Research
  • Software Engineering Techniques and Practices
  • Advanced Software Engineering Methodologies
  • Human-Automation Interaction and Safety
  • Software Testing and Debugging Techniques
  • Anomaly Detection Techniques and Applications

Jane Cleland-Huang has published numerous papers, with notable recent publications including:

  • "Human-machine Teaming with Small Unmanned Aerial Systems in a MAPE-K Environment," 2023, ACM Transactions on Autonomous and Adaptive Systems
  • "Configuring mission-specific behavior in a product line of collaborating Small Unmanned Aerial Systems," 2022, Journal of Systems and Software
  • "Information retrieval versus deep learning approaches for generating traceability links in bilingual projects," 2021, Empirical Software Engineering
  • "Detecting Anomalies in Small Unmanned Aerial Systems via Graphical Normalizing Flows," 2023, IEEE Intelligent Systems
  • "Visualizing Change in Agile Safety-Critical Systems," 2020, IEEE Software

Their frequent coauthors include:

  • A.K. Agrawal
  • Michael Vierhauser
  • Nitesh V. Chawla
  • Md Nafee Al Islam
  • Jinfeng Lin

Jane Cleland-Huang has contributed to a range of publication venues, most prominently in:

  • arXiv (Cornell University)
  • Journal of Systems and Software
  • ACM Transactions on Autonomous and Adaptive Systems
  • SSRN Electronic Journal
  • IEEE Intelligent Systems

Their research falls within the broader field of computer science and covers notable subfields such as:

  • Information Systems
  • Artificial Intelligence
  • Software
  • Aerospace Engineering
  • Social Psychology

Best Publications

  • Event-based traceability for managing evolutionary change

    J. Cleland-Huang;C.K. Chang;M. Christensen

  • Software traceability: trends and future directions

    Jane Cleland-Huang;Orlena C. Z. Gotel;Jane Huffman Hayes;Patrick Mäder

  • Semantically enhanced software traceability using deep learning techniques

    Jin Guo;Jinghui Cheng;Jane Cleland-Huang

  • Automated classification of non-functional requirements

    Jane Cleland-Huang;Raffaella Settimi;Xuchang Zou;Peter Solc

  • Software and Systems Traceability

    Jane Cleland-Huang;Orlena Gotel;Andrea Zisman

  • Goal-centric traceability for managing non-functional requirements

    Jane Cleland-Huang;Raffaella Settimi;Oussama BenKhadra;Eugenia Berezhanskaya

  • The Detection and Classification of Non-Functional Requirements with Application to Early Aspects

    J. Cleland-Huang;R. Settimi;Xuchang Zou;P. Solc

  • Best Practices for Automated Traceability

    J. Cleland-Huang;R. Settimi;E. Romanova;B. Berenbach

  • Utilizing supporting evidence to improve dynamic requirements traceability

    J. Cleland-Huang;R. Settimi;Chuan Duan;Xuchang Zou

  • A machine learning approach for tracing regulatory codes to product specific requirements

    Jane Cleland-Huang;Adam Czauderna;Marek Gibiec;John Emenecker

  • Message from the program chairs of icse 2020

    Jane Cleland-Huang;Darko Marinov

  • On-demand feature recommendations derived from mining public product descriptions

    Horatiu Dumitru;Marek Gibiec;Negar Hariri;Jane Cleland-Huang

  • Feature model extraction from large collections of informal product descriptions

    Jean-Marc Davril;Edouard Delfosse;Negar Hariri;Mathieu Acher

  • The incremental funding method: data-driven software development

    M. Denne;J. Cleland-Huang

  • Supporting software evolution through dynamically retrieving traces to UML artifacts

    R. Settimi;J. Cleland-Huang;O. Ben Khadra;J. Mody

  • Traceability Fundamentals

    Unknown

  • Strategic Traceability for Safety-Critical Projects

    Patrick Mader;Paul L. Jones;Yi Zhang;Jane Cleland-Huang

  • Improving automated requirements trace retrieval: a study of term-based enhancement methods

    Xuchang Zou;Raffaella Settimi;Jane Cleland-Huang

  • Supporting Domain Analysis through Mining and Recommending Features from Online Product Listings

    Negar Hariri;Carlos Castro-Herrera;Mehdi Mirakhorli;Jane Cleland-Huang

  • A heterogeneous solution for improving the return on investment of requirements traceability

    J. Cleland-Huang;G. Zemont;W. Lukasik

  • The quest for Ubiquity: A roadmap for software and systems traceability research

    O. Gotel;J. Cleland-Huang;J. Huffman Hayes;A. Zisman

  • Towards automated requirements prioritization and triage

    Chuan Duan;Paula Laurent;Jane Cleland-Huang;Charles Kwiatkowski

  • Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering

    Thomas Zimmermann;Jane Cleland-Huang;Zhendong Su

Frequent Co-Authors

Patrick Mäder
Patrick Mäder Ilmenau University of Technology
Jane Huffman Hayes
Jane Huffman Hayes University of Kentucky
Bamshad Mobasher
Bamshad Mobasher DePaul University
Ankit Agrawal
Ankit Agrawal Northwestern University
Denys Poshyvanyk
Denys Poshyvanyk William & Mary
Paul Grünbacher
Paul Grünbacher Johannes Kepler University of Linz
Giuliano Antoniol
Giuliano Antoniol Polytechnique Montréal
Jonathan I. Maletic
Jonathan I. Maletic Kent State University
Roel Wieringa
Roel Wieringa University of Twente
Xavier Franch
Xavier Franch Universitat Politècnica de Catalunya

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