Muhammad Ali Gulzar

Assistant Professor in Computer Science

I am an assistant professor in the Computer Science Department at Virginia Tech. I received my Ph.D. in Computer Science at the University of California, Los Angeles in 2020. I was also the recipient of Google Ph.D. Fellowship 2017-20.

The vision of my research is to build systems that improve developer productivity through automated debugging and testing for big data analytics. Broadly, I am interested in designing novel tool support for data-centric software development. My approach combines insights from software engineering, distributed systems, and databases. My past work has focused on interactive and automated debugging for Apache Spark, symbolic execution based test generation for dataflow programs, and performance debugging in Apache Spark.

gulzar cs.vt.edu | Google Scholar | Github | LinkedIn

News

Our work on isolating fault-inducing operations in dataflow applications is accepted to SoCC 2021!
Our work on untangling tracking and functional resources in web apps is accepted to IMC 2021. Congrats Hadi!
We received an NSF medium grant on Fuzz Testing of Data and Compute Intensive Systems (PIs: Gulzar and Kim).
I joined the computer science department at Virginia Tech as an assistant professor.
Our work on influence-based data provenance is accepted to SoCC 2020. Congrats Jason!
Our work on fuzz testing for data analytics is accepted to ASE 2020. Congrats Qian!
I received my Ph.D. in Computer Science from UCLA. Ph.D. Dissertation.
I am honored to receive the 2019-20 Outstanding Computer Science Graduating Ph.D. Student from the computer science department at UCLA.
I am honored to receive the 2019-20 Northrop Grumman Outstanding Computer Science Graduate Student Research Award from the computer science department at UCLA.
Our work on evaluating neuron coverage as a testing criterion for DNNs is accepted to FSE 2020. Congrats Fabrice!
Older news

Publications

2021

  1. [SOCC 2021] OptDebug: Fault-Inducing Operation Isolation for Dataflow Applications
    Muhammad Ali Gulzar, and Miryung Kim
    In The 12th ACM Symposium on Cloud Computing 2021
    13 Pages. 30% Acceptance Rate
  2. [IMC 2021] TrackerSift: Untangling Mixed Tracking and Functional Web Resources
    Abdul Hadi Amjad, Muhammad Saleem, Muhammad Ali Gulzar*, Zubair Shafiq*, and Fareed Zaffar*
    In Proceedings of the 2021 ACM Internet Measurement Conference 2021
    8 Pages. 27.9% Acceptance Rate
  3. [HiPS 2021] Towards a Serverless Bioinformatics Cyberinfrastructure Pipeline
    Shunyu David Yao, Muhammad Ali Gulzar, Liqing Zhang, and Ali R. Butt
    In Proceedings of the 1st Workshop on High Performance Serverless Computing 2021
    8 Pages. Workshop Paper.

2020

  1. [SOCC 2020] Influence-Based Provenance for Dataflow Applications with Taint Propagation
    Jason Teoh, Muhammad Ali Gulzar, and Miryung Kim
    In The 11th ACM Symposium on Cloud Computing 2020
    12 Pages. Full Paper. 24.4% Acceptance Rate
  2. [ASE 2020] BigFuzz: Efficient Fuzz Testing for Data Analytics using Framework Abstraction
    Qian Zhang, Jiyuan Wang, Muhammad Ali Gulzar, Rohan Padhye, and Miryung Kim
    In The 35th IEEE/ACM International Conference on Automated Software Engineering 2020
    12 Pages. Full Paper. 22.5% Acceptance Rate
  3. [ESEC/FSE 2020] Is Neuron Coverage a Meaningful Measure for Testing Deep Neural Networks?
    Fabrice Harel-Canada, Lingxiao Wang, Muhammad Ali Gulzar, Quanquan Gu, and Miryung Kim
    In The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering 2020
    12 Pages. Full Paper. 28.0% Acceptance Rate
  4. [ICSE 2020] HeteroRefactor: Refactoring for Heterogeneous Computing with FPGA
    Jason Lau*, Aishwarya Sivaraman*, Qian Zhang*, Muhammad Ali Gulzar, Jason Cong, and Miryung Kim
    In 2020 IEEE/ACM 42nd International Conference on Software Engineering 2020
    13 Pages. Full Paper. 20.9% Acceptance Rate
  5. [ICSE Demo 2020] BigTest: Symbolic Execution Based Systematic Test Generation Tool for Apache Spark
    Muhammad Ali Gulzar, Madan Musuvathi, and Miryung Kim
    In Proceedings of the ACM/IEEE 42nd International Conference on Software Engineering: Companion Proceedings 2020
    4 Pages. Demonstration Paper. 33.3% Acceptance Rate

2019

  1. [ESEC/FSE 2019] White-box Testing of Big Data Analytics with Complex User-defined Functions
    Muhammad Ali Gulzar, Shaghayegh Mardani, Madanlal Musuvathi, and Miryung Kim
    In Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering 2019
    12 Pages. Full Paper. 24.4% Acceptance Rate
  2. [SoCC 2019] PerfDebug: Performance Debugging of Computation Skew in Dataflow Systems
    Jason Teoh, Muhammad Ali Gulzar, Harry Xu, and Miryung Kim
    In Proceedings of the 2019 Symposium on Cloud Computing 2019
    12 Pages. Full Paper. 24.8% Acceptance Rate
  3. [ICSE SEIP 2019] Perception and Practices of Differential Testing
    Muhammad Ali Gulzar, Yongkang Zhu, and Xiaofeng Han
    In Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice 2019
    10 Pages. Full Paper. 22.2% Acceptance Rate

2018

  1. [ICDCS 2018] LogLens: A Real-Time Log Analysis System
    Biplob Debnath, Mohiuddin Solaimani, Muhammad Ali Gulzar, Nipon Arora, Cristian Lumezanu, Jianwu Xu, Bo Zong, Hui Zhang, Guofei Jiang, and Latifur Khan
    In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS) 2018
    11 Pages. Full Paper. 20.6% Acceptance Rate
  2. [VLDB Journal 2018] Adding Data Provenance Support to Apache Spark
    Matteo Interlandi, Ari Ekmekji, Kshitij Shah, Muhammad Ali Gulzar, Sai Deep Tetali, Miryung Kim, Todd Millstein, and Tyson Condie
    The VLDB Journal 2018
    21 Pages. VLDB Journal Paper.
  3. [ESEC/FSE Demo 2018] BigSift: Automated Debugging of Big Data Analytics in Data-intensive Scalable Computing
    Muhammad Ali Gulzar, Siman Wang, and Miryung Kim
    In Proceedings of the 2018 26th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering 2018
    4 Pages. Demonstration Paper. 38.8% Acceptance Rate
  4. [ICSE ACM Student Research Competition 2018] Interactive and Automated Debugging for Big Data Analytics ( ACM Student Research Competition Gold Medal Winner)
    Muhammad Ali Gulzar,
    In Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings 2018
    3 Pages. Short Paper.

2017

  1. [SoCC 2017] Automated Debugging in Data-intensive Scalable Computing
    Muhammad Ali Gulzar, Matteo Interlandi, Xueyuan Han, Mingda Li, Tyson Condie, and Miryung Kim
    In Proceedings of the 2017 Symposium on Cloud Computing 2017
    15 Pages. Full Paper. 23.6% Acceptance Rate
  2. [SIGMOD Demo 2017] Debugging Big Data Analytics in Spark with BigDebug
    Muhammad Ali Gulzar, Matteo Interlandi, Tyson Condie, and Miryung Kim
    In Proceedings of the 2017 ACM International Conference on Management of Data 2017
    4 Pages. Demonstration Paper. 34% Acceptance Rate

2016

  1. [ICSE 2016] BigDebug: Debugging Primitives for Interactive Big Data Processing in Spark
    Muhammad Ali Gulzar, Matteo Interlandi, Seunghyun Yoo, Sai Tetali, Tyson Condie, Todd Millstein, and Miryung Kim
    In 2016 IEEE/ACM 38th International Conference on Software Engineering 2016
    12 Pages. Full Paper. 19.1% Acceptance Rate
  2. [SoCC 2016] Optimizing Interactive Development of Data-Intensive Applications
    Matteo Interlandi, Sai Deep Tetali, Muhammad Ali Gulzar, Joseph Noor, Tyson Condie, Miryung Kim, and Todd Millstein
    In Proceedings of the Seventh ACM Symposium on Cloud Computing 2016
    13 Pages. Full Paper. 25.1% Acceptance Rate
  3. [VLDB 2016] Titian: Data Provenance Support in Spark ( The "Best of VLDB" Paper)
    Matteo Interlandi, Kshitij Shah, Sai Deep Tetali, Muhammad Ali Gulzar, Seunghyun Yoo, Miryung Kim, Todd Millstein, and Tyson Condie
    Proc. VLDB Endow. 2016
    12 Pages. Full Paper. 21.2% Acceptance Rate
  4. [HotCloud 2016] Interactive Debugging for Big Data Analytics
    Muhammad Ali Gulzar, Xueyuan Han, Matteo Interlandi, Shaghayegh Mardani, Sai Deep Tetali, Todd Millstein, and Miryung Kim
    In 8th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 16) 2016
    7 Pages. Workshop Paper. 30.8% Acceptance Rate
  5. [ESEC/FSE Demo 2016] BigDebug: Interactive Debugger for Big Data Analytics in Apache Spark
    Muhammad Ali Gulzar, Matteo Interlandi, Tyson Condie, and Miryung Kim
    In Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering 2016
    5 Pages. Demonstration Paper. 40.1% Acceptance Rate

2015

  1. [PACIS 2015] A Classification Based Framework to Predict Viral Threads
    Hashim Sharif, Saad Ismail, Shehroze Farooqi, Mohammad Taha Khan, Muhammad Ali Gulzar, Hasnain Lakhani, Fareed Zaffar, and Ahmed Abbasi
    In The Pacific Asia Conference on Information Systems (PACIS) 2015
    13 Pages. Full Paper.
* Student authors contributed equally.
* Senior authors are alphabatically arranged.

Funding

SHF: Medium: Reinventing Fuzz Testing for Data and Compute Intensive Systems
Duration: 2021-2025
Amount: $900,000
PIs: Miryung Kim (UCLA, Lead), Muhammad Ali Gulzar (Virgina Tech)
Virginia Tech’s Share: $323,982.00

2017 Google Ph.D. Fellowship
Duration: 2017-2020
Amount: $160,000
Institution: UCLA

NSF I-Corps Grant for Technology Transfer
Duration: Fall 2018
Amount: $50,000
PI: Miryung Kim, El: Muhammad Ali Gulzar, IM: Alan Ho