Internetware 2024, the 15th Asia-Pacific Symposium on Internetware, provides a forum for researchers and practitioners to discuss the trending software technologies in the Internet era. Internetware 2024 will be held July 24-26 in Macau, China.

Internetware 2024 Keynote

Keynote 1: Prof. Andreas Zeller: Advances in Language-Based Testing

Abstract: Generating test inputs (Fuzzing) for software gets much easier if one knows the input language of the software under test. In this talk, I present novel game-changing methods for (1) inferring complex input languages statically via symbolic analysis, enabling fuzzers to cover the full input space with 100% precision and recall; (2) specifying input languages, using novel combinations of grammars and constraints that cover syntax and semantics; (3) applying these techniques on highly complex input domains such as XML, allowing to exhaustively test business systems; and (4) automatically learning models from programs that fully replicate their input/output behavior, leveraging generated tests. Includes live demos!

Bio: Andreas Zeller is faculty at the CISPA Helmholtz Center for Information Security and professor for Software Engineering at Saarland University. His research on automated debugging, mining software archives, specification mining, and security testing has won several awards for its impact in academia and industry. Zeller is an ACM Fellow, holds an ACM SIGSOFT Outstanding Research Award, and has won two ERC Advanced Grants, Europe’s highest funding for individual researchers.

Keynote 2: Prof. Tao Xie: Development of System Software Stack for RISC-V+AI Computility

Abstract: In recent years, the RISC-V open ISA has gained much progress rapidly and has become a focus of international technology competition. It has also become an effective way to consolidate industrial development consensus through open source and build a global industrial computility ecosystem. Although Nvidia’s GPUs and CUDA software ecosystem currently dominate the global AI computing market, the industry urgently hopes to establish a new software ecosystem to break through CUDA ecosystem barriers. A gradually formed consensus is to use RISC-V AI chips as a common ground, unite related companies and universities/research institutes to jointly develop ISA AI extension standards in an open source and open manner, and cooperate in the development of an open-source AI system software stack on top of these standards. This presentation discusses this direction, its significant opportunities, and the strategies for addressing the faced challenges.

Bio: Tao Xie, Peking University Chair Professor, Chair of the Department of Software Science and Engineering in the School of Computer Science at Peking University, a Deputy Director of the Key Lab of High Confidence Software Technologies, Ministry of Education. He was a Full Professor at the Department of Computer Science, the University of Illinois at Urbana-Champaign (UIUC), USA. He is a Foreign Member of Academia Europaea, and a Fellow of ACM, IEEE, AAAS, and China Computer Federation (CCF). He serves as Director of CCF Technical Committee of System Software (TCSS), Chair of RISC-V+AI Computility Ecosystem (RACE) Committee, and Chair of RISC-V International AI/ML SIG.

Keynote 3: Dr. Hongxia Yang: Edge GenAI: Pioneering the Next Phase of AI Evolution

Abstract: Edge AI is transforming artificial intelligence by enhancing cost efficiency, energy conservation, privacy, and personalized experiences. Our research focuses on edge-based Generative AI (GenAI), targeting specialized reasoning and planning applications to potentially surpass benchmarks set by industry leaders like OpenAI.
This presentation will spotlight three pivotal technologies essential for the success of edge Generative AI (GenAI): the Unified GenAI Distillation Paradigm, Low Resource Inference and Learning, and Multimodal Reasoning and Planning. We will introduce the Single-step Distillation (SiD), an innovative approach that transforms complex pretrained models into efficient generators. This method notably reduces computational demands by 60% through a score-matching loss minimization technique, representing a significant advancement in GenAI distillation paradigms. Addressing challenges in low-resource environments, we will unveil our novel LEGO architecture—comprising modular ‘LEGO blocks’ designed to build multiscale Transformers. This architecture significantly reduces GPU load and cuts sampling times by 60%. Additionally, we will discuss our strategies for Multimodal Large Language Models (MLLM), focusing on aligning model representations across diverse data modalities. Our leading method, InfiMM, utilizes smaller-scale models within the Flamingo architecture and incorporates autoregressive (AR) techniques in the Vision Language-connector to enhance performance across various modalities.
Join us to explore how these advancements are set to redefine edge GenAI, making it more accessible and effective for practical applications.

Bio: Dr. Hongxia Yang, with over 15 years of experience as an AI scientist, specializes in large-scale machine learning, data mining, and deep learning. Throughout her career, she has developed 10 significant algorithmic systems, improving the operations of various enterprises. Her research includes pre-trained models, big data analytics, and the practical deployment of large language model (LLM) systems in real settings. Dr. Yang has published more than 100 top-tier papers, amassed over 8,500 citations with an H-index of 41, and holds over 50 patents. She has received several awards, including the 2019 SAIL Award at the World Artificial Intelligence Conference and the 2020 National Science and Technology Progress Award, China’s top tech accolade. Named one of Forbes China’s Top 50 Women in Tech in 2022 and AI 2000 Most Influential Scholar Award in 2023-2024, Dr. Yang has held prominent roles at ByteDance US, Alibaba Group, Yahoo! Inc, and IBM T.J. Watson Research Center. She earned her PhD from Duke University and her B.S. from Nankai University.

Accepted Papers

Call for Papers

Internet is open, dynamic, and meets a constantly changing environment. These characteristics impose new requirements on software over internet. The goals or values of software paradigm is to better utilize hardware capabilities or runtime features, as well as to provide a more expressive and natural computing model from the perspective of application domain. In that sense, software paradigm can be considered as a reflection of the runtime environment and application domain. When the dominant network environment changed from Intranet to internet, software paradigm shifts from object-oriented to component-based and service-oriented. Therefore, software paradigm is very related to environment changes such as hardware and human itself. The new software paradigm is needed for Internet computer, and it is called as Internetware. Internetware is constructed by a set of autonomic software entities distributed over the Internet, and a set of connectors enabling the collaborating among these entities in various manners.

Current years, intelligent information fusion becomes important approach applied in an extensive computing field. Researchers also tend to utilize AI technologies to develop a series of automated tools for improving the efficiency and performance of ubiquitous computing in Internetware. Increased computational power, advanced machine learning techniques, and access to very large-scale data have led to a significant transition into the emergence of Large Language Models (LLMs). LLMs are blurring the line between human and machine-produced language, thus can be successfully applied in ubiquitous computing in Internetware. In the future human-cyber-physical ternary ubiquitous computing, there are a lot of new patterns and scenarios. LLMs can provide the good solutions for analyzing the data resources, hardware, and applications so that increasing the performance of ubiquitous computing in Internetware.

This symposium aims to provide an interactive forum where researchers and professionals from multiple disciplines and domains meet and exchange ideas to explore and address the challenges brought by Internetware.

Internetware 2024 will be held July 24-26 in Macau SAR, China. We solicit submissions describing original and unpublished results of theoretical, empirical, conceptual, and experimental software engineering research related to Internetware. Topics of interests include but are not limited to:

• Novel software paradigm for Internetware
• Modeling and implementation of Internetware
• Research and Applications in Ubiquitous Operating Systems
• Human Aspects in Ubiquitous Operating Systems
• Human-Cyber-Physical ternary ubiquitous computing applied in Internetware
• Artificial intelligence of things (AIoT)
• Operating system and Internetware
• Intelligent information fusion
• Requirements engineering for Internetware
• Software analysis, verification, and testing
• Mining software repositories
• Software dependability, trustworthiness and confidence
• Software architecture and design
• Crowd-based methods, techniques and tools for Internetware
• Social-technical models and techniques
• Software ecosystem practices and experiences
• Software models and techniques for Internet-based systems such as Cloud Computing, Service Computing, Social computing, Mobile Internet, Internet of Things, and Cyber-Physical Systems
• Software engineering for/with Big data
• Software engineering for/with Artificial Intelligence

How to Submit

All submissions must not exceed 10 pages for all text, figures, tables, and references. All submissions must be in English and in PDF format. Submissions that do not comply with the above instructions will be desk rejected without review. Please use the ACM Primary Article Template (double column), as can be obtained from the ACM Proceedings Template pages.

Submissions to internetware 2024 conference that meet the above requirements can be made via the internetware 2024 submission site (https://internetware2024.hotcrp.com) by the submission deadline. We encourage the authors to upload their paper info early (and can submit the PDF later) to properly enter conflicts for double-anonymous reviewing.

Review and Evaluation Criteria

The Internetware 2024 conference will employ a double-anonymous review process. Thus, no submission may reveal its authors’ identities. The authors must make every effort to honor the double-anonymous review process. In particular:

• Authors’ names must be omitted from the submission.
• All references to the author’s prior work should be in the third person.
• While authors have the right to upload preprints on ArXiV or similar sites, they should avoid specifying that the manuscript was submitted to Internetware 2024.
• During review, authors should not publicly use the submission title.

Internetware 2024 will follow the ACM SIGSOFT rules on Conflicts of Interest and Confidentiality of Submissions, and all authors, reviewers, organizers are expected to uphold the ACM Code of Conduct.