The 27th International Conference on Engineering of Complex Computer Systems (ICECCS 2023) is a well-established event that has been held around the world for over 25 years. Over the past years, we have seen a rapidly rising emphasis on the design, implementation and management of complex computer systems which are present in every aspect of human activities, such as manufacturing, communications, defence, transportation, aerospace, hazardous environments, energy, and healthcare. These complex systems are frequently distributed over heterogeneous networks and process a large amount of data. Complexity arises from many factors, including the dynamic environment and the scenarios these systems operate in, demanding and sometimes conflicting requirements in functionality, efficiency, scalability, security, dependability and adaptability, as well as the wide range of development methodologies, programming languages and implementation details. Performance, real-time behaviour, fault tolerance, security, adaptability, development time and cost, and long life concerns are some of the key issues arising in the development of such systems.
The goal of this conference is to bring together industrial, academic, and government experts from a variety of application domains and software disciplines, to discuss how the disciplines' problems and solution techniques interact within the whole system. Researchers, practitioners, tool developers and users, and technology transfer experts are all welcome. The scope of the conference includes long-term research issues, near-term requirements and challenges, established complex systems, emerging promising tools, and retrospective and prospective reflections of research and development into complex systems.
ICECCS is an A-ranked international conference by the Computing Research and Education Association of Australasia (CORE) 2018 ranking.
Abstract Submissions Due:
08 December 2022 16 January 2023
Full Paper Submissions Due:
15 December 2022 16 January 2023
Acceptance/Rejection Notification: 15 March 2023
Camera-ready Due: 15 April 2023
Conference date: 14-16 June 2023
Authors are invited to submit papers describing original, unpublished research results, case studies and tools. Papers are solicited in all areas related to complex computer-based systems, including the causes of complexity and means of avoiding, controlling, or coping with complexity. Topic areas include, but are not limited to:
Different kinds of contributions are sought, including novel research, lessons learned, experience reports, and discussions of practical problems faced by industry and user domains. The ultimate goal is to build a rich and comprehensive conference program that can fit the interests and needs of different classes of attendees: professionals, researchers, managers, and students. A program goal is to organize several sessions that include both academic and industrial papers on a given topic and culminate panels to discuss relationships between industrial and academic research.
Full papers are divided into two categories: Technical Papers and Experience Reports. The papers submitted to both categories will be reviewed by the program committee members, and papers accepted in either category will be published in the conference proceedings. The proceedings of ICECCS 2023 will be published by Conference Publishing Services (CPS). Technical papers should describe original research, and experience reports should present practical projects carried out in the industry, and reflect on the lessons learnt from them.
Short paper submissions describe early-stage, ongoing or PhD research. All short papers will be reviewed by the program committee members, and accepted short papers will be published in the conference proceedings.
Submissions to the conference must not have been published or be concurrently considered for publication elsewhere. All submissions will be judged on the basis of originality, contribution to the field, technical and presentation quality, and relevance to the conference.
Submitted manuscripts should be in English and formatted in the style of the double-column Conference Publishing Services (CPS) format. Full papers should not exceed 10 pages, and short papers should not exceed 6 pages, including figures, references, and appendices. All submissions should be in PDF format. Submissions not adhering to the specified format and length may be rejected immediately, without review.
Please prepare your manuscripts in accordance to the (Conference Publishing Services (CPS) guidelines). We invite all prospective authors to submit their manuscripts via the ICECCS'23 portal, hosted on EasyChair.
Access submission portal
|Author Registration (before 25th April)||600 €|
|Early Normal Registration (no later than 15 May)||600 €|
|Late Normal Registration (after 15 May)||650 €|
|Extra ticket for gala dinner||60 €|
|Extra ticket for visit||30 €|
Go to the registration page and follow the instructions to fill in all sections of the registration form.
University: Institut National Polytechnique de Toulouse (INPT)
Code NAF (APE) : 8542Z "Enseignement Supérieur"
VAT number : FR42193113818
Bank Account Information
Account name : « INPT – Agent comptable »
Bank address: Trésorerie Générale - Place Occitane - 31029 Toulouse Cedex FRANCE
Phone : +33 (0)5 61 26 55 35
Bank code: 10071 - Code Guichet: 31000
Account number: 10071 / 31000 / 00001001328
Key : 85
IBAN : FR76 / 1007 /1310 / 0000 / 0010 0132 885
BIC : TRPUFRP1
Title. "Testing automation using RoboStar"
Abstract. The RoboStar framework supports a model-based approach in the development of control software for robotics applications. It provides domain-specific tool-independent notations for modelling and simulation, and techniques for automatic generation of artefacts. In this talk, we focus on the RoboStar techniques for automatic test generation. We can generate tests using reactive design models described in a diagrammatic notation called RoboChart. These tests can be used for animation or converted for execution against simulations, either automatically generated or custom-developed. We target a well-established tool, RT-Tester, and simulations that use ROS (Robot Operating System). Conversion reflects a notion of correctness that compares reactive models to cyclic models that embed the paradigm of simulations, and provides traceability. We present the approach, and its foundations and applications.
Bio. Ana Cavalcanti is a professor at the University of York and a Royal Academy of Engineering Chair in Emerging Technologies. She leads RoboStar, a centre of excellence on software engineering for robotics.
The RoboStar approach to model-based software engineering compliments the current practice of design and verification of mobile and autonomous robots, covering simulation, testing and proof. This approach is practical, supported by tools, and yet mathematically rigorous so that it can provide reliable evidence of trustworthiness.
Title. "Probabilistic Reasoning for Sports Analytics"
Abstract. Sports analytics encompasses the utilization of data science, artificial intelligence (AI), psychology, and advanced Internet of Things (IoT) devices to enhance sports performance, strategy, and decision-making. This process involves the collection, processing, and interpretation of cloud-based data from a variety of sources, such as video recordings, performance metrics, and scouting reports. The resulting insights aid in evaluating player and team performance, preventing injuries, and supporting coaches and team managers in making well-informed decisions to optimize resources and achieve superior outcomes. One widely recognized formal method, Probabilistic Model Checking (PMC), has been conventionally employed in reliability analysis for intricate safety critical systems. For instance, the reliability of an aircraft can be determined by evaluating the reliability of its individual components, including the engine, wings, and sensors. Our groundbreaking approach applies PMC to a novel domain: Sports Strategy Analytics. As an example, the reliability (winning percentage) of a sports player can be ascertained from the reliability (success rate) of their specific sub-skill sets (e.g., serve, forehand, backhand, etc., in tennis). In this presentation, we will discuss our recent research work, which involves the application of PMC, machine learning, and computer vision to the realm of sports strategy analytics. At the end of the presentation, we will also discuss the vision of a new international sports analytics conference series https://formal-analysis.com/isace/2023/).
Bio. Dr. Jin-Song Dong is a professor at the National University of Singapore. His research spans a range of fields, including formal methods, safety and security systems, probabilistic reasoning, sports analytics, and trusted machine learning. He co-founded the commercialized PAT verification system, which has garnered thousands of registered users from over 150 countries and received the 20-Year ICFEM Most Influential System Award. Jin Song also co-founded the commercialized trusted machine learning system Silas (www.depintel.com). He has received numerous best paper awards, including the ACM SIGSOFT Distinguished Paper Award at ICSE 2020. He served on the editorial board of ACM Transactions on Software Engineering and Methodology, Formal Aspects of Computing, and Innovations in Systems and Software Engineering, A NASA Journal. He has successfully supervised 28 PhD students, many of whom have become tenured faculty members at leading universities worldwide. He is also a Fellow of the Institute of Engineers Australia. In his leisure time, Jin Song developed Markov Decision Process (MDP) models for tennis strategy analysis using PAT, assisting professional players with pre-match analysis (outperforming the world's best). He is a Junior Grand Slam coach and takes pleasure in coaching tennis to his three children, all of whom have reached the #1 national junior ranking in Singapore/Australia. Two of his children have earned NCAA Division 1 full scholarship, while his second son, Chen Dong, played #1 singles for Australia in the Junior Davis Cup and participated in both the Australian Open and US Open Junior Grand Slams.
Title. "Disproving XAI Myths with Formal Methods -- Initial Results"
Abstract. The advances in machine learning (ML) in recent years have been both impressive and far-reaching. However, the deployment of ML models is still impaired by lack of trust on how the best-performing ML models make predictions. The issue of lack of trust is even more acute in the uses of ML models in high-risk or safety-critical domains. eXplainable artificial intelligence (XAI) is at the core of ongoing efforts for delivering trustworthy AI. Unfortunately, XAI is riddled with critical misconceptions, that foster distrust instead of building trust. This talk details some of the most visible misconceptions in XAI, and shows how formal methods have been used, both to disprove those misconceptions, but also to devise practically effective alternatives.
Bio. Joao Marques-Silva is a CNRS Research Director (Directeur de Recherche), being affiliated with IRIT in Toulouse, France. He is also one of the Research Chairs of the Artificial and Natural Intelligence Toulouse Institute (ANITI). Before joining CNRS, IRIT and ANITI, Joao Marques-Silva held senior academic appointments at the University of Lisbon in Portugal, the University College Dublin in Ireland, and the University of Southampton in the United Kingdom. Dr. Marques-Silva is a Fellow of the IEEE, and he was a recipient of the 2009 CAV Award for fundamental contributions to the development of high-performance Boolean satisfiability solvers.
Scientific and Social Programme of ICECCS 2023
ICECCS 2023 Proceedings
The conference will be held in INP-ENSEEIHT. It is located in the centre of Toulouse. It is easily accessible by metro from François Verdier station or Jean-Jaurès station.
ENSEEIHT Engineer school
2 Rue Charles Camichel
Toulouse can easily be reached by plane: The airport Toulouse-Blagnac (TLS) is the 5th largest airport in France with over 6.5 million passengers per year. There are flights from 87 destinations serving 73 cities abroad.
The “Flybus” shuttle bus service connects the airport to the city centre, even during weekends. The bus stops at the "Compans-Caffarelli" bus station. Alternatively, a tram (line T2) connects the airport to the city centre (stops are "Palais de Justice" and "Arènes"). The tram line runs every 15 min from 5:30 to 23:30, 7/7.
The main railway station in Toulouse is the Toulouse-Matabiau station. It is located in the city centre and is connected to the subway. You can reach most French cities with direct trains and even go to Barcelona.
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The city transport network ("Tisséo") includes 2 metro lines, 2 tram lines and 84 bus services. For those arriving by plane, a shuttle and a tram link the airport to the city centre and the train station.
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Dominique Mery, Université de Lorraine, France
Yamine Ait Ameur, IRIT/INPT-ENSEEIHT, France
Étienne André, Université Sorbonne Paris Nord, France
Cyrille Valentin Artho, KTH Royal Institute of Technology, Sweden
Christian Attiogbé, L2N - Université de Nantes, France
Guangdong Bai, University of Queensland, Australia
Hadrien Bride, Griffith University, Australia
Lei Bu, Nanjing University, China
Yuting Chen, Shanghai Jiao Tong University, China
Sylvain Conchon, Universite Paris-Sud, France
Florin Craciun, Babes-Bolyai University, Romania
Juergen Dingel, Queen's University, Canada
Guillaume Dupont, IRIT-ENSEEIHT,France
Flavio Ferrarotti, Software Competence Centre Hagenberg, Austria
John Fitzgerald, Newcastle University, United Kingdom
Marc Frappier, Université de Sherbrooke, Canada
Ning Ge, Beihang University, China
Sebastien Gerard, CEA, LIST, France
Sudipto Ghosh, Colorado State University, USA
Brahim Hamid, IRIT- University of toulouse, France
Thai Son Hoang, University of Southampton, United Kingdom
Hiroshi Hosobe, Hosei University, Japan
Zhe Hou, Griffith University, Australia
Fuyuki Ishikawa, National Institute of Informatics, Japan
Ferhat Khendek, Concordia University, Canada
Kenji Kono, Keio University, Japan
Kung-Kiu Lau, The University of Manchester, United Kingdom
Scott Uk-Jin Lee, Hanyang University, Korea
Michael Leuschel, University of Düsseldorf, Germany
Shang-Wei Lin, Nanyang Technological University, Singapore
Yun Lin, Shanghai Jiao Tong University, China
Yang Liu, Nanyang Technological University, Singapore
Shaoying Liu, Hiroshima University, Japan
Gerald Luettgen, University of Bamberg, Germany
Lei Ma, University of Alberta, Canada
Frederic Mallet, Universite Nice Sophia-Antipolis, France
Tiziana Margaria, Lero, Ireland
Dominique Mery, Université de Lorraine, France
Weikai Miao, East China Normal University, China
Stefan Mitsch, Carnegie Mellon University, USA
Rosemary Monahan, Maynooth University, Ireland
Sadaf Mustafiz, Ryerson University, Canada
Fumiko Nagoya, College of Commerce, Nihon University, Japan
Shin Nakajima, National Institute of Informatics, Japan
Manuel Núñez, Universidad Complutense de Madrid, Spain
Laure Petrucci, Université Paris 13, France
Salah Sadou, IRISA, University of South Brittany, France
Gwen Salaün, University of Grenoble Alpes, France
Wuwei Shen, Western Michigan Univarsity, USA
Neeraj Kumar Singh, IRIT-ENSEEIHT, Toulouse, France
Meng Sun, Peking University, China
Jing Sun, University of Auckland, New Zealand
Jun Sun, Singapore Management University, Singapore
Maurice ter Beek, ISTI-CNR, Pisa, Italy
Ferdian Thung, Singapore Management University, Singapore
Tatsuhiro Tsuchiya, Osaka University, Japan
Tullio Vardanega, University of Padua, Italy
Hai H. Wang, University of Aston, United Kingdom
Shi Lin Wang, Shanghai Jiao Tong University, China
Hironori Washizaki, Waseda University, Japan
Burkhart Wolff, Univ. Paris-Saclay, France
Zhilin Wu, Chinese Academy of Sciences, China
Yinxing Xue, University of Science and Technology of China, China
Fatiha Zaidi, Univ. Paris-Sud, France
Chenyi Zhang, Jinan University
Jianjun Zhao, Kyushu University, Japan
Junjun Zheng, Osaka University, Japan
Tewfik Ziadi, Sorbonne Université-CNRS 7606, LIP6, France
Jin Song Dong, National University of Singapore, Singapore
Mike Hinchey, University of Limerick, Ireland
Xiaohong Li, Tianjin University, China
Shaoying Liu, Hiroshima University, Japan
Mauro Pezze, University in Lugano, Switzerland
Roy Sterritt, Ulster University, United Kingdom
Jing Sun (Chair), University of Auckland, New Zealand
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