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D-Index & Metrics

Computer Science

D-Index
40
Citations
6003
World Ranking
9374
National Ranking
3975

Overview

Julian Dolby is affiliated with IBM in the United States and has an extensive publication record primarily in the field of Computer Science, with a focus on Artificial Intelligence and Information Systems. The research covers several subfields including Software, Signal Processing, and Management Science and Operations Research.

The scientist's research topics include Software Engineering Research, Computational Physics and Python Applications, Machine Learning and Data Classification, Topic Modeling, Software Testing and Debugging Techniques, Natural Language Processing Techniques, and Data Quality and Management.

Julian Dolby has contributed multiple papers to various respected venues. Some notable recent papers include:

  • CodeNet: A Large-Scale AI for Code Dataset for Learning a Diversity of Coding Tasks, 2021, published by Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Static Analysis of Shape in TensorFlow Programs, 2020, published by Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • A scalable AutoML approach based on graph neural networks, 2022, published in Proceedings of the VLDB Endowment
  • Program analysis using WALA (tutorial), 2022, published in Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
  • Can Machines Read Coding Manuals Yet? - A Benchmark for Building Better Language Models for Code Understanding, 2022, published in Proceedings of the AAAI Conference on Artificial Intelligence

Frequently collaborating with other researchers, Julian Dolby's notable coauthors include Kavitha Srinivas, Ibrahim Abdelaziz, Horst Samulowitz, Mossad Helali, and Essam Mansour. The collaboration count ranges from three to eleven papers with these coauthors.

The primary publication venues for Julian Dolby's works encompass:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • Proceedings of the VLDB Endowment
  • Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
  • Proceedings of the AAAI Conference on Artificial Intelligence

The publication record reflects a strong interdisciplinary approach with a concentration on advancing toolsets and datasets for software engineering and AI-related challenges. Julian Dolby's work contributes to both foundational aspects and practical applications within these domains.

Best Publications

  • The Jikes research virtual machine project: building an open-source research community

    B. Alpern;S. Augart;S. M. Blackburn;M. Butrico

  • Associating synchronization constraints with data in an object-oriented language

    Mandana Vaziri;Frank Tip;Julian Dolby

  • Building an efficient RDF store over a relational database

    Mihaela A. Bornea;Julian Dolby;Anastasios Kementsietsidis;Kavitha Srinivas

  • A framework for automated testing of javascript web applications

    Shay Artzi;Julian Dolby;Simon Holm Jensen;Anders Moller

  • Finding Bugs in Web Applications Using Dynamic Test Generation and Explicit-State Model Checking

    S Artzi;A Kiezun;J Dolby;F Tip

  • Finding bugs in dynamic web applications

    Shay Artzi;Adam Kiezun;Julian Dolby;Frank Tip

  • Directed test generation for effective fault localization

    Shay Artzi;Julian Dolby;Frank Tip;Marco Pistoia

  • Saving the world wide web from vulnerable JavaScript

    Salvatore Guarnieri;Marco Pistoia;Omer Tripp;Julian Dolby

  • Correlation tracking for points-to analysis of javascript

    Manu Sridharan;Julian Dolby;Satish Chandra;Max Schäfer

  • CLAP: recording local executions to reproduce concurrency failures

    Jeff Huang;Charles Zhang;Julian Dolby

  • Efficient construction of approximate call graphs for JavaScript IDE services

    Asger Feldthaus;Max Schafer;Manu Sridharan;Julian Dolby

  • Alias analysis for object-oriented programs

    Manu Sridharan;Satish Chandra;Julian Dolby;Stephen J. Fink

  • Scalable and precise taint analysis for Android

    Wei Huang;Yao Dong;Ana Milanova;Julian Dolby

  • Race detection for web applications

    Boris Petrov;Martin Vechev;Manu Sridharan;Julian Dolby

  • An automatic object inlining optimization and its evaluation

    Julian Dolby;Andrew Chien

  • Dynamic detection of atomic-set-serializability violations

    Christian Hammer;Julian Dolby;Mandana Vaziri;Frank Tip

  • Matching patient records to clinical trials using ontologies

    Chintan Patel;James Cimino;Julian Dolby;Achille Fokoue

  • Practical fault localization for dynamic web applications

    Shay Artzi;Julian Dolby;Frank Tip;Marco Pistoia

  • Scalable semantic retrieval through summarization and refinement

    Julian Dolby;Achille Fokoue;Aditya Kalyanpur;Aaron Kershenbaum

  • MemSAT: checking axiomatic specifications of memory models

    Emina Torlak;Mandana Vaziri;Julian Dolby

Frequent Co-Authors

Frank Tip
Frank Tip Northeastern University
Marco Pistoia
Marco Pistoia JPMorgan Chase & Co (United States)
Manu Sridharan
Manu Sridharan University of California, Riverside
Anastasios Kementsietsidis
Anastasios Kementsietsidis Google (United States)
Aditya Kalyanpur
Aditya Kalyanpur Elemental Cognition
Stephen J. Fink
Stephen J. Fink Facebook (United States)
Vijay Karamcheti
Vijay Karamcheti New York University
Vivek Sarkar
Vivek Sarkar Georgia Institute of Technology
Barbara G. Ryder
Barbara G. Ryder Virginia Tech
Jan Vitek
Jan Vitek Northeastern University

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