Published on 08 Sep 2021

ESEC/FSE 2021 Best Artifact Award

Screenshot of virtual award ceremony at the ESEC/FSE 2021.

Best Artifact Award announced at the ESEC/FSE 2021 award ceremony. From top right: Wu Xiuheng (NTU), former SCSE researcher Zhu Chengguang (UT Austin) and Asst Prof Li Yi (NTU).

The paper “DIFFBASE: A Differential Factbase for Effective Software Evolution Management”, by SCSE postgraduate Wu Xiuheng (NTU), former SCSE research staff Zhu Chenguang (UT Austin), and SCSE Asst Prof Li Yi (NTU) has won a Best Artifact Award at the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2021). The conference was held virtually from 23 to 27 August 2021. This was one of the two Best Artifact Awards selected from the 33 invited software artifacts at ESEC/FSE this year. The award recognizes the effort of creating and sharing outstanding research artifacts, and is a part of the open-science initiative in the software engineering research community.

ESEC/FSE is a premium software engineering conference and an internationally renowned forum for researchers, practitioners, and educators to present and discuss the most recent innovations, trends, experiences, and challenges in the field of software engineering.

The awarded work proposes DIFFBASE, a simple yet powerful representation of pertinent information in evolving software systems. Numerous tools and techniques have been developed to extract and analyze information from software development artifacts. Yet, there is a lack of effective method to process, store, and exchange information among different analyses. DIFFBASE considers program changes as first-class objects, which establish links between intra-version facts of single program snapshots and provide insights on how certain artifacts evolve over time via inter-version facts. The first author Mr Wu Xiuheng is a 3rd year PhD student supervised by Asst Prof Li Yi. His follow-up work on a related topic has recently been accepted at the 36th IEEE/ACM International Conference on Automated Software Engineering (ASE 2021).

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