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Today, I accepted the EAPLS best paper award on behalf of my coauthors at the virtual ETAPS 2020 afternoon. Thank you, ETAPS, and congrats again to Yiming, Mehdi, and Baishakhi!
We are honored to receive the EAPLS best paper award at the 2020 International Conference on Fundamental Approaches to Software Engineering (FASE ’20) for our paper entitled, “An Empirical Study on the Use and Misuse of Java 8 Streams” with Yiming Tang, Mehdi Beherdezeh, and Baishakhi Ray. (more…)
I am excited to announce that I have received $1,500 from the Amazon Web Services (AWS) Cloud Credits for Research Program. (more…)
I am pleased to announce that I have received an ACM SIGSOFT CAPS professional travel award to attend the IEEE/ACM International Conference on Automated Software Engineering (ASE) 2019.
I am pleased to announce that I have been selected to receive the CUNY Academy Stewart Travel Award for Assistant Professors for the 2018-2019 academic year.
We are honored to receive a best paper award at the 2018 IEEE International Working Conference on Source Code Analysis and Transformation (SCAM ’18) for our paper entitled, “A Tool for Optimizing Java 8 Stream Software via Automated Refactoring” with Yiming Tang, Mehdi Beherdezeh, and Syed Ahmed. (more…)
I am pleased to announce that the Japan Society for the Promotion of Science (JSPS) US Alumni Association (AA) has generously awarded a grant to host a seminar on programming languages and software engineering in New York City! Plans are currently in the works for a seminary to be held in early 2019. Stay tuned!
I am pleased to announce that I have recently received a PSC-CUNY Enhanced Research Award for a project entitled, “Analyses and Automated Refactorings for Imperative Programs that Use Functional Features.” The award amount is $12,000 and will help support students and travel. The award program is an internal funding mechanism to help promote research at CUNY. A brief abstract of the proposal is listed below:
Imperative programming uses statements to alter a program’s state, whereas functional programming avoids mutating existing data. With the recent popularity rise of functional programming, imperative languages are increasingly incorporating new functional features, enabling developers not previously familiar with functional programming to enjoy many of its benefits. Despite the advantages, however, issues arise from the interplay between the two paradigms, particular regarding involving MapReduce-style operations. This project will address these problems by formulating a theoretical foundation for the analysis and refactoring of hybrid functional/imperative programs and subsequently used to identify code that may safely be refactored for performance gains. Based on typestate analysis, it will determine when it is advantageous and safe to run hybrid code in parallel via a novel ordering inference approach that the PI will introduce. This work will advance the state-of-the-art in program analysis and automated refactoring for this mixed paradigm.