Muhammad Ali Gulzar
Ph.D Candidate in Computer Science

I am a Ph.D. candidate at the University of California, Los Angeles Computer Science Department where I am advised by Miryung Kim.
The vision of my research is to build systems that improve developer productivity through automated debugging and testing of 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. Recently, I have been collaborating with the ML group at UCLA to investigate automated testing for deep neural networks.
I have collaborated with a variety of researchers from different sub-fields of computer science, including Tyson Condie, Todd Millstein, Madan Musuvathi, and Harry Xu.
gulzar cs.ucla.edu | Google Scholar | Github | LinkedInAwards
Publications
2020
-
[ESEC/FSE 2020] Is Neuron Coverage a Meaningful Measure for Testing Deep Neural Networks? 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
-
[ICSE 2020] HeteroRefactor: Refactoring for Heterogeneous Computing with FPGA (* are equal co-first authors ordered alphabetically by their last names) In 2020 IEEE/ACM 42nd International Conference on Software Engineering 2020 13 Pages. Full Paper. 20.9% Acceptance Rate
-
[ICSE Demo 2020] BigTest: Symbolic Execution Based Systematic Test Generation Tool for Apache Spark In Proceedings of the 2020 42nd International Conference on Software Engineering 2020 4 Pages. Demonstration Paper. 33.3% Acceptance Rate
2019
-
[ESEC/FSE 2019] White-box Testing of Big Data Analytics with Complex User-defined Functions 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
-
[SoCC 2019] PerfDebug: Performance Debugging of Computation Skew in Dataflow Systems In Proceedings of the 2019 Symposium on Cloud Computing 2019 12 Pages. Full Paper. 24.8% Acceptance Rate
-
[ICSE SEIP 2019] Perception and Practices of Differential Testing In Proceedings of the 41st International Conference on Software Engineering: Software Engineering in Practice 2019 10 Pages. Full Paper. 22.2% Acceptance Rate
2018
-
[ICDCS 2018] LogLens: A Real-Time Log Analysis System In 2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS) 2018 11 Pages. Full Paper. 20.6% Acceptance Rate
-
[VLDB Journal 2018] Adding Data Provenance Support to Apache Spark The VLDB Journal 2018 21 Pages. VLDB Journal Paper.
-
[ESEC/FSE Demo 2018] BigSift: Automated Debugging of Big Data Analytics in Data-intensive Scalable Computing 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
-
[ICSE ACM Student Research Competition 2018] Interactive and Automated Debugging for Big Data Analytics ( ACM Student Research Competition Gold Medal Winner) In Proceedings of the 40th International Conference on Software Engineering: Companion Proceeedings 2018 3 Pages. Short Paper.
2017
-
[SoCC 2017] Automated Debugging in Data-intensive Scalable Computing In Proceedings of the 2017 Symposium on Cloud Computing 2017 15 Pages. Full Paper. 23.6% Acceptance Rate
-
[SIGMOD Demo 2017] Debugging Big Data Analytics in Spark with BigDebug In Proceedings of the 2017 ACM International Conference on Management of Data 2017 4 Pages. Demonstration Paper. 34% Acceptance Rate
2016
-
[ICSE 2016] BigDebug: Debugging Primitives for Interactive Big Data Processing in Spark In 2016 IEEE/ACM 38th International Conference on Software Engineering 2016 12 Pages. Full Paper. 19.1% Acceptance Rate
-
[SoCC 2016] Optimizing Interactive Development of Data-Intensive Applications In Proceedings of the Seventh ACM Symposium on Cloud Computing 2016 13 Pages. Full Paper. 25.1% Acceptance Rate
-
[VLDB 2016] Titian: Data Provenance Support in Spark ( The "Best of VLDB" Paper) Proc. VLDB Endow. 2016 12 Pages. Full Paper. 21.2% Acceptance Rate
-
[HotCloud 2016] Interactive Debugging for Big Data Analytics In 8th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 16) 2016 7 Pages. Workshop Paper. 30.8% Acceptance Rate
-
[ESEC/FSE Demo 2016] BigDebug: Interactive Debugger for Big Data Analytics in Apache Spark 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
-
[PACIS 2015] A Classification Based Framework to Predict Viral Threads In The Pacific Asia Conference on Information Systems (PACIS) 2015 13 Pages. Full Paper.
News
Jul 23, 2019 | Our work on performance debugging of dataflow applications is accepted to SoCC 2019. Congrats Jason! |
Apr 9, 2019 | Our work on symbolic-execution based testing of big data analytics is accepted to ESEC/FSE 2019. |
Dec 9, 2018 | Our paper on practices of Differential Testing at Google got accpeted to ICSE SEIP 2019. I contributed towards this work as an intern at Google in 2018. |
Sep 30, 2018 | My work on a real time log analysis framework at NEC Labs America got accepted to ICDCS 2018. |
Sep 30, 2018 | We are awarded $50K NSF I-Corps grant for technology transfer of our interactive and automated debugging work. I am the EL (Entrepreneurial Lead) of this grant. |
Jun 20, 2018 | I started working at Google Inc. Mountain View as Software Engineer Tools and Infrastructure Intern. |
May 31, 2018 | Miryung and I demonstrated our tool BigSift at Spark Summit 2018. |
May 26, 2018 | I received a gold medal at ACM Student Research Competition at ICSE 2018 |
Jun 5, 2017 | Our work on automated debugging in DISC is accepted to SoCC 2017. |
Mar 31, 2017 | I am honored to be awarded the 2017 Google Ph.D Fellowship in Software Engineering. Thanks Google! |
Dec 31, 2016 | Our work on automated and interactive debugging in Spark is accepted at SIGMOD 2017 demonstration track |
Jun 30, 2016 | Our work, BigDebug, for interactive debugging of big data applications is accepted at FSE 2016 demonstration track |
Jun 20, 2016 | I started working as a Summer Research Assistant at NEC Labs America, Princeton in summer 2016 |
Apr 30, 2016 | Our workshop paper on automated fault localization and debugging in big data applications is accepted to HotCloud 2016 |
Nov 30, 2015 | Our paper on debugging primitives for interactive big data processing is accepted to ICSE 2016 |
Jun 5, 2015 | Our paper on Apache Spark’s Data Provenance is accepted to VLDB 2016 |
Dec 31, 2014 | My undergraduate work atLUMS for predicting viral threads is accepted to PACIS 2015 |
Dec 31, 2014 | Our position paper on Debugging primitives of Big Data frameworks is accepted to HPTS 2015 |