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ICSE 2020
Wed 24 June - Thu 16 July 2020
Thu 9 Jul 2020 07:00 - 07:12 at Silla - I15-Ecosystems 1 Chair(s): Raula Gaikovina Kula

Software projects are increasingly forming social-technical ecosystems within which individual projects rely on the infrastructures or functional components provided by other projects, leading to complex inter-dependencies. Through inter-project dependencies, a bug in an upstream project may have profound impact on a large number of downstream projects, resulting in cross-project bugs. The emerging type of bugs has brought new challenges in bug fixing due to their unclear influence on downstream projects. In this paper, we present an approach to estimating the impact of a cross-project bug within its ecosystem by identifying the affected downstream modules (classes/methods). Note that a downstream project that uses a buggy upstream function may not be affected as the usage does not satisfy the failure inducing preconditions. For a reported bug with the known root cause function and failure inducing preconditions, we first collect the candidate downstream modules that call the upstream function through an ecosystem-wide dependence analysis. Then, the paths to the call sites of the buggy upstream function are encoded as symbolic constraints. Solving the constraints, together with the failure inducing preconditions, identifies the affected downstream modules. Our evaluation of 31 existing upstream bugs on the scientific Python ecosystem containing 121 versions of 22 popular projects (with a total of 16 millions LOC) shows that the approach is highly effective: from the 25490 candidate downstream modules that invoke the buggy upstream functions, it identifies 1132 modules where the upstream bugs can be triggered, pruning 95.6% of the candidates. The technique has no false negatives and an average false positive rate of 7.9%. Only 49 downstream modules (out of the 1132 we found) were reported before to be affected.

Thu 9 Jul

Displayed time zone: (UTC) Coordinated Universal Time change

07:00 - 08:00
Impact Analysis of Cross-Project Bugs on Software EcosystemsTechnical
Technical Papers
Wanwangying Ma Nanjing University, Lin Chen Nanjing University, Xiangyu Zhang Purdue University, Yang Feng Nanjing University, Zhaogui Xu Nanjing University, China, Zhifei Chen Huawei, Yuming Zhou Nanjing University, Baowen Xu Nanjing University
SIEVE: Helping Developers Sift Wheat from Chaff via Cross-Platform AnalysisJ1
Journal First
Agus Sulistya Telkom Institute of Technology Surabaya, Gede Artha Azriadi Prana Singapore Management University, Abhishek Sharma Singapore Management University, Singapore, David Lo Singapore Management University, Christoph Treude The University of Adelaide
Sharing at Scale: An Open-Source-Software-based License Compliance EcosystemSEIP
Software Engineering in Practice
Frances Paulisch Siemens Healthineers, Arun Azhakesan Siemens Healthineers
Extended abstract “Software Deployment on Heterogeneous Platforms: A Systematic Mapping Study”J1
Journal First
Hugo Andrade Chalmers University of Technology, Jan Schroeder Chalmers | University of Gothenburg, Ivica Crnkovic Chalmers | University of Gothenburg
A Large Scale Study of Long-Time Contributor Prediction for GitHub ProjectsJ1
Journal First
Lingfeng Bao Zhejiang University, Xin Xia Monash University, David Lo Singapore Management University, Gail Murphy University of British Columbia