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ICSE 2020
Wed 24 June - Thu 16 July 2020
Tue 7 Jul 2020 08:05 - 08:17 at Baekje - I4-Clones and Changes Chair(s): Chanchal K. Roy

Modern machine learning programs are often written in Python, with the main computations specified through calls to some highly optimized libraries (e.g., TensorFlow, PyTorch). How to maximize the computing efficiency of such programs is essential for many application domains, which has drawn lots of recent attention. This work points out a common limitation in existing efforts: they focus their views only on the static computation graphs specified by library APIs, but leave the influence from the hosting Python code largely unconsidered. The limitation often causes them to miss the big picture and hence many important optimization opportunities. This work proposes a new approach named HARP to address the problem. HARP enables holistic analysis that spans across computation graphs and their hosting Python code. HARP achieves it through a set of novel techniques: analytics-conscious speculative analysis to circumvent Python complexities, a unified representation augmented computation graphs to capture all dimensions of knowledge related with the holistic analysis, and conditioned feedback mechanism to allow risk-controlled aggressive analysis. Refactoring based on HARP gives 1.3–3X and 2.07X average speedups on a set of TensorFlow and PyTorch programs.

Tue 7 Jul
Times are displayed in time zone: (UTC) Coordinated Universal Time change

08:05 - 09:05
I4-Clones and ChangesTechnical Papers / Journal First / New Ideas and Emerging Results / Demonstrations at Baekje
Chair(s): Chanchal K. RoyUniversity of Saskatchewan
HARP: Holistic Analysis for Refactoring Python-Based Analytics ProgramsTechnical
Technical Papers
Weijie ZhouNorth Carolina State University, Yue ZhaoNCSU, Guoqiang ZhangNorth Carolina State University, Xipeng ShenNorth Carolina State University
CC2Vec: Distributed Representations of Code ChangesTechnical
Technical Papers
Thong HoangSingapore Management University, Singapore, Hong Jin KangSchool of Information Systems, Singapore Management University, Julia LawallInria, David LoSingapore Management University
Code Duplication on Stack OverflowNIER
New Ideas and Emerging Results
Sebastian BaltesQAware GmbH and The University of Adelaide, Christoph TreudeThe University of Adelaide
Pre-print Media Attached
Siamese: Scalable and Incremental Code Clone Search via Multiple Code RepresentationsJ1
Journal First
Chaiyong RagkhitwetsagulMahidol University, Thailand, Jens KrinkeUniversity College London
Link to publication DOI Pre-print Media Attached
Empirical comparison of text-based mobile apps similarity measurement techniquesJ1
Journal First
Afnan Al-SubaihinKing Saud University, Federica SarroUniversity College London, UK, Sue BlackDurham University, Licia CapraUniversity College London
Link to publication DOI Media Attached File Attached
SimilarAPI: Mining Analogical APIs for Library MigrationDemo
Chunyang ChenMonash University