Our new paper entitled, “Safe Automated Refactoring for Intelligent Parallelization of Java 8 Streams” has been accepted to the International Conference on Software Engineering (ICSE) 2019 technical track! Out of 529 submissions, 109 papers were accepted (an acceptance rate of 20.6%). The conference will be held in Montréal later next year. An abstract is listed below.
Congratulations to the authors, particularly Yiming Tang, for having a publication appear in a top-tier conference only in the second year of her Ph.D. studies! A preliminary version of the work was published as an ICSE 2018 poster:
Streaming APIs are becoming more pervasive in mainstream Object-Oriented programming languages. For example, the Stream API introduced in Java 8 allows for functional-like, MapReduce-style operations in processing both finite and infinite data structures. However, using this API efficiently involves subtle considerations like determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. In this paper, we present an automated refactoring approach that assists developers in writing efficient stream code in a semantics-preserving fashion. The approach, based on a novel data ordering and typestate analysis, consists of preconditions for automatically determining when it is safe and possibly advantageous to convert sequential streams to parallel and unorder or de-parallelize already parallel streams. The approach was implemented as a plug-in to the Eclipse IDE, uses the WALA and SAFE analysis frameworks, and was evaluated on 11 Java projects consisting of $\sim$642 thousand lines of code. We found that 36.31% of candidate streams were refactorable, and an average speedup of 3.49 on performance tests was observed. The results indicate that the approach is useful in optimizing stream code to their full potential.