Blogs (1) >>
ASE 2019
Sun 10 - Fri 15 November 2019 San Diego, California, United States
Wed 13 Nov 2019 17:00 - 17:10 at Hillcrest - Performance Chair(s): Tim Menzies

As data volume and complexity grow at an unprecedented rate, the performance of data analytics programs is becoming a major concern for developers. We observed that developers sometimes use alternative data analytics APIs to improve program runtime performance while preserving functional equivalence. However, little is known on the characteristics and performance attributes of alternative data analytics APIs. In this paper, we propose a novel approach to extract alternative implementations that invoke different data analytics APIs to solve the same tasks. A key appeal of our approach is that it exploits the comparative structures in Stack Overflow discussions to discover programming alternatives. We show that our approach is promising, as 86% of the extracted code pairs were validated as true alternative implementations. In over 20% of these pairs, the faster implementation was reported to achieve a 10x or more speedup over its slower alternative. We hope that our study offers a new perspective of API recommendation and motivates future research on optimizing data analytics programs.

Conference Day
Wed 13 Nov

Displayed time zone: Tijuana, Baja California change

16:00 - 17:50
PerformanceResearch Papers / Demonstrations at Hillcrest
Chair(s): Tim MenziesNorth Carolina State University
16:00
20m
Talk
Accurate Modeling of Performance Histories for Evolving Software Systems
Research Papers
Stefan MühlbauerBauhaus-University Weimar, Sven ApelSaarland University, Norbert SiegmundBauhaus-University Weimar
Pre-print
16:20
20m
Talk
An Industrial Experience Report on Performance-Aware Refactoring on a Database-centric Web Application
Research Papers
Boyuan ChenYork University, Zhen Ming (Jack) JiangYork University, Paul MatosCopywell Inc., Michael LacariaCopywell Inc.
Authorizer link Pre-print
16:40
20m
Talk
An Experience Report of Generating Load Tests Using Log-recovered Workloads at Varying Granularities of User Behaviour
Research Papers
Jinfu ChenJiangsu University, Weiyi ShangConcordia University, Canada, Ahmed E. HassanQueen's University, Yong WangAlibaba Group, Jiangbin LinAlibaba Group
Pre-print
17:00
10m
Talk
How Do API Selections Affect the Runtime Performance of Data Analytics Tasks?
Research Papers
Yida TaoShenzhen University, Shan TangShenzhen University, Yepang LiuSouthern University of Science and Technology, Zhiwu XuShenzhen University, Shengchao QinUniversity of Teesside
17:10
10m
Talk
Demystifying Application Performance Management Libraries for Android
Research Papers
Yutian TangThe Hong Kong Polytechnic University, Xian ZhanThe Hong Kong Polytechnic University, Hao ZhouThe Hong Kong Polytechnic University, Xiapu LuoThe Hong Kong Polytechnic University, Zhou XuWuhan University, Yajin ZhouZhejiang University, Qiben YanMichigan State University
17:20
10m
Demonstration
PeASS: A Tool for Identifying Performance Changes at Code Level
Demonstrations
David Georg ReicheltUniversität Leipzig, Stefan KühneUniversität Leipzig, Wilhelm HasselbringKiel University
Pre-print Media Attached File Attached
17:30
20m
Talk
ReduKtor: How We Stopped Worrying About Bugs in Kotlin Compiler
Research Papers
Daniil StepanovSaint Petersburg Polytechnic University, Marat AkhinSaint Petersburg Polytechnic University / JetBrains Research, Mikhail BelyaevSaint Petersburg Polytechnic University
Pre-print