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Every year, ACM holds Student Research Competitions, which offer undergraduate and graduate students an opportunity to present their original research before a panel of judges and attendees at well-known ACM-sponsored and co-sponsored conferences. This year, Muhammad Gulzar, a UCLA CS Ph.D. student, was awarded the top prize in the graduate category of the ACM Student Research Competition at the International Conference on Software Engineering (ICSE), held in Gothenburg, Sweden.

It was a great experience [being a part of the competition],” Gulzar said. “I feel really happy that our research got recognized and acknowledged by such a broad community of Software Engineering.”

The award, sponsored by Microsoft Research, allows students to present their research in the ACM Student Research Competition Grand Finals. Gulzar’s winning submission was titled “Interactive and Automated Debugging for Big Data Analytics”, which focuses on assisting data scientists in debugging and testing big data analytic programs.

“Debugging is a challenging problem for such developers because of the sheer size of input data being ingested by the program,” Gulzar explained. “A failure or fault may appear due to one out of the billions of data points. The techniques and tools that we built minimize user effort by finding the root cause of these problems interactively and automatically, consequently saving developers time and computing resources.”

Gulzar’s overall research interests span software engineering, distributed systems, and data science. He aims to merge ideas from software engineering and database systems to enable debugging of big data analytics, without compromising the throughput or performance of big data systems. Gulzar’s most recent research on interactive and automated debugging for big data analytics reflects this – “This new piece of work fits really well in the high level goal of my work, which is to help big data analytic developers find and remove faults in their programs through better testing and debugging techniques,” Gulzar said.

In the long run, Gulzar hopes to keep working on improving testing of big data analytics by bringing insights from conventional software testing techniques.

“The area of big data debugging is still new,” Gulzar explained. “I believe that this line of research has a direct impact on the industry where software engineers and data scientists are spending days trying to debug their big data analytics programs – we have been repeatedly told to provide access to these tools by both industry and academia, which indicates the need of such tooling in this domain. [My recent work] with another graduate student is to find these bottlenecks in big data execution, and take appropriate actions to improve the running time of the overall big data analytic jobs…In the long run, this line of work has the potential to drastically improve developer productivity and reduce the use of computing resources.”

Read more about Gulzar’s research project and his upcoming participation in the final rounds of the competition against gold medalists across all domains of computer science here.