Software Engineers’ Response to Public Crisis: Lessons Learnt from Spontaneously Building an Informative COVID-19 Dashboard
Wed 11 May 2022 11:00 - 11:05 at ICSE room 4-odd hours - Autonomic Systems and Self-Adaptation Chair(s): Henry Muccini
The Coronavirus disease 2019 (COVID-19) outbreak quickly spread around the world, resulting in over 240 million infections and 4 million deaths by Oct 2021. While the virus is spreading from person to person silently, fear has also been spreading around the globe. The COVID-19 information from the Australian Government is convincing but not timely or detailed, and there is much information on social networks with both facts and rumors. As software engineers, we have spontaneously and rapidly constructed a COVID-19 information dashboard aggregating reliable information semi-automatically checked from different sources for providing one-stop information sharing site about the latest status in Australia. Inspired by the John Hopkins University COVID-19 Map, our dashboard contains the case statistics, case distribution, government policy, latest news, with interactive visualization. In this paper, we present a participant’s in-person observations in which the authors acted as founders of https://covid-19-au.com/ serving more than 830K users with 14M page views since March 2020. According to our first-hand experience, we summarize 9 lessons for developers, researchers and instructors. These lessons may inspire the development, research and teaching in software engineer aspects for coping with similar public crises in the future.
Tue 10 MayDisplayed time zone: Eastern Time (US & Canada) change
Wed 11 MayDisplayed time zone: Eastern Time (US & Canada) change
11:00 - 12:00 | Autonomic Systems and Self-AdaptationSEIS - Software Engineering in Society / Technical Track at ICSE room 4-odd hours Chair(s): Henry Muccini University of L'Aquila, Italy | ||
11:00 5mTalk | Software Engineers’ Response to Public Crisis: Lessons Learnt from Spontaneously Building an Informative COVID-19 Dashboard SEIS - Software Engineering in Society Han Wang Monash University, Chao Wu Monash University, Chunyang Chen Monash University, Burak Turhan University of Oulu, Shiping Chen Data61 at CSIRO, Australia / UNSW, Australia, Jon Whittle CSIRO's Data61 and Monash University Pre-print Media Attached | ||
11:05 5mTalk | DRESS-ML: A Domain-specific Language for Modelling Exceptional Scenarios and Self-adaptive Behaviours for Drone-based Applications SEIS - Software Engineering in Society Lucas Vieira State University of Ceará, José Davi da Silva Pereira State University of Ceara, Brazil, Natália Aragão State University of Ceara, Brazil, Matheus Chagas State University of Ceará, Paulo Maia State University of Ceará Pre-print Media Attached | ||
11:10 5mTalk | Lowering Barriers to Application Development With Cloud-Native Domain-Specific Functions SEIS - Software Engineering in Society José Miguel Pérez-Álvarez NAVER LABS Europe, Adrian Mos NAVER LABS Europe, Benjamin V. Hanrahan Pennsylvania State University, Iyadunni J. Adenuga Pennsylvania State University Pre-print Media Attached | ||
11:15 5mTalk | Automated Assertion Generation via Information Retrieval and Its Integration with Deep Learning Technical Track Hao Yu Peking University, Yiling Lou Purdue University, Ke Sun , Dezhi Ran Peking University, Tao Xie Peking University, Dan Hao Peking University, Ying Li School of Software and Microelectronics, Peking University, Beijing, China, Ge Li Peking University, Qianxiang Wang Huawei Technologies Co. Ltd DOI Pre-print Media Attached | ||