The additional in-person event, called ICSA-Lite, will take place on August 22-24, 2022 at the Imin Conference Center, Honolulu (Hawaii USA) on the beautiful campus of the University of Hawaii at Manoa.
The event will be, to large extent, a working conference to discuss the hottest and most challenging research directions in the software architecture field.
We will also have some keynotes. Besides exciting content, attending will also give you a chance to connect to senior members of the community!
We aim to produce several research roadmaps centered around important topics. We have already identified the following as tentative topics:
- Architecture for ML-intensive systems
- Relationships between architecture and Agile/DevOps
- Architecture & CI/CD, and DevOps
- Agile architecting, continuous architecting, and other approaches to architecting
- Architecture concerns/approaches in security/privacy
- Architecture for IoT/Edge systems
- Architecture for Industry 4.0/Digital Twins
- Architectural considerations in hybrid traditional/quantum systems
- Mining and sharing data to create an empirical basis for architecture research
- Approaches to architecture education
- Architecture models in the 2020s: (where) do they deliver value, how to align models and data?
For the resulting research roadmaps, we plan to write them during and after the conference, with shared authorship among the attendees. We are currently investigating publishing options.
There will also be the opportunity for authors of papers accepted to ICSA 2022 to present their work in person.
Registration is now open: Register for ICSA-Lite 2022 here!
You can now book your room here in the conference hotel at the special ICSA rate: Hilton Garden Inn Waikiki Beach
|9:00 - 10:30 (UTC)
|Opening & Keynote 1
|Keynote 2 & two invited talks (*)
|SANER talks (***)
|10:30 - 11:00 (UTC)
|11:00 - 12:30 (UTC)
|Organizing the Working Sessions
|12:30 - 13:30 (UTC)
|13:30 - 15:00 (UTC)
|WS4 & short presentations (5min each) & group reflection
|15:00 - 15:30 (UTC)
|15:30 - 17:00 (UTC)
|WS2 & short presentations (5 min each)
|ICSA talks (**)
|Wrap-up and organizing the post-conf work
Ian Gorton is the director of computer science master’s programs and a professor of the practice at the Khoury College of Computer Sciences at Northeastern University’s Seattle campus. He is passionate about analyzing and designing complex, high-performance scalable distributed systems and embodying design and architecture principles in methods and tools that can be exploited by architects in other projects. Before joining Northeastern in 2015, he was a senior member of the technical staff at the Carnegie Mellon University Software Engineering Institute. He had several projects on the principles of designing massively scalable software architectures for big data applications and building knowledge bases both manually and using machine learning to support engineering tasks. Before this, Gorton was a laboratory fellow in computational sciences and math at Pacific Northwest National Laboratory (PNNL). He managed the Data-Intensive Scientific Computing research group and was the chief architect for PNNL’s Data Intensive Computing Initiative. He was also PI for multiple projects in environmental modeling, carbon capture and sequestration, and bioinformatics. This experience has led to a particular interest in the design of large-scale, highly customizable cyber-infrastructures for scientific research. Gorton is a senior member of the IEEE Computer Society and a Fellow of the Australian Computer Society. Until July 2006, he led the software architecture R&D at National ICT Australia in Sydney, Australia, and previously worked at CSIRO, IBM, Microsoft, and in academia in Australia. A complete list of his publications and citations can be found on Google Scholar and in dblp. He is the author of Essential Software Architecture (2011) and The Foundations of Scalable Systems (2022).
Dr. Yuanfang Cai is a Professor at Drexel University, and currently working at Google as a visiting researcher during her sabbatical. Her primary research interests are software design, software architecture, software evolution, technical debt detection, and software economics. She has created a number of influential concepts, methods, and tools, including Design Rule Space, Decoupling Level, Modularity Violation, Hotspot patterns, etc. Her team has created and validated the automated detection and quantification of design debt, supported by their DV8 tool suite, on hundreds of open source projects and dozens of industrial projects from various companies. She has authored about 100 publications and four patents. Dr. Cai is currently serving on program committees and organizing committees for multiple top conferences, and serves as an Associate Editor and editorial board member for top journals in the area of software engineering. The tools and technologies from Dr Cai’s research have been licensed and adopted by multiple multinational corporations.
(*) Invited Talks
Mehdi Mirakhorli Tool Sharing, Composition, and Reproducible Research through Software Architecture INstrument (SAIN)
John Stough Acquire Like you Fight
(**) ICSA talks
Cesare Pautasso Web API structures and data models analysis
Sebastian Gottschalk Model-driven Continuous Experimentation on Component-based Software Architectures
Marco Konersmann Evaluation Methods and Replicability of Software Architecture Research Objects
Bara Buhnova Predictive Simulation within the Process of Building Trust
(***) SANER talks
- Giulia Sellitto, Emanuele Iannone, Zadia Codabux, Valentina Lenarduzzi, Andrea De Lucia, Fabio Palomba, Filomena Ferrucci Toward Understanding the Impact of Refactoring on Program Comprehension
- Roberto Tonelli Some trends in Blockchain Oriented Software Engineering
- Wolfgang Mauerer and Stefanie Scherzinger A 1-2-3 Reproducibility for Quantum Software Experiments
- Aitor Arrieta, Maialen Otaegi, Liping Han, Goiuria Sagardui, Shaukat Ali, and Maite Arratibe Automating Test Oracle Generation in DevOps for Industrial Elevators
- Tao Yue and Shaukat Ali Quantum Software Analysis, Evolution and Reengineering
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