Track: Old software, New approaches
Human and Artificial Intelligences for Software Evolution
ABOUT
Old software systems typically raise numerous quality issues. In a context where the norm is having too little funding, too much to do, and obsolete technologies, legacy software is a seemingly endless source of challenges: evolving the structure of the systems to embrace new development directions, maintaining an acceptable level of quality in an ever changing code base, keeping pace with the evolution of practices and technologies, finding and motivating developers to work with obsolete technologies, ...
We seek novel contributions on how to help developers evolve software systems. If the subject of software evolution research is as old as computing itself, it needs to tap into novel research areas, for example novel solutions based on artificial intelligence and data mining are emerging; novel artifacts are used including social medias (eg: stackoverflow).
TOPICS
Topics of interest include, but are not limited to:
Artificial intelligence applied to software evolution
Human aspects of software maintenance and comprehension
Software maintenance methods, techniques and tools
Change and defect management
Code smells detection and visualization
Software refactoring and restructuring
Reverse engineering and re-engineering
Empirical studies on software maintenance and comprehension
Software quality assessment
Technical debt in software maintenance
TRACK COMMITTEE
Chair: Nicolas Anquetil, INRIA & University of Lille-1, France
Program Committee:
Abdelhak-Djamel Seriai, University of Montpellier, France
Alexandros Chatzigeorgiou, University of Macedonia, Greece
Andrea Janes, Free University of Bolzano, Italy
Andres Diaz Pace, ISISTAN Research Institute, UNICEN University, Argentina
Apostolos Ampatzoglou, University of Macedonia, Greece
Bartosz Walter, Poznań University of Technology, Poland
Christelle Urtado, Ecole Mines-Telecom, France
Christopher Fuhrman, Ecole de Technologie Supérieure, Canada
Claudia Raibulet, University of Milano Bicocca, Italy
Elena María Navarro Martínez, University of Castilla-La Mancha, Spain
Fabio Palomba, University of Salerno, Italy
Gordana Rakic, University of Novi Sad, Serbia
Lavazza Luigi, Università degli Studi dell'Insubria, Italy
Miguel Goulao, Universidade Nova de Lisboa, portugal
Rafael Capilla Sevilla, King Juan Carlos University, Spain
Sandro Morasca, Università degli Studi dell'Insubria, Italy
Steve Counsell, Brunel University, UK
Yania Crespo, University of Valladolid, Spain
Nicolas Anquetil completed his PhD in 1996 at University of Montréal. Since then, he worked successively at University of Ottawa (Canada), Federal University of Rio de Janeiro (Brazil), Catholic University of Brasilia (Brazil), and École des Mines de Nantes (France). He is now Associate Professor (MCF/HDR) at University of Lille and member of the RMod research team (affiliated with the LIFL --Laboratoire d'Informatique Fondamentale de Lille-- a joint laboratory between University of Lille, CNRS, and Inria).
His research interests cover about anything that has to do with software maintenance and evolution. Currently, in the INRIA/RMod team, he is working on reverse engineering which aims at providing technical solutions to help people understand better and modify legacy software. For example, he works on software re-structuring, or how to help re-organizing a legacy software into coherent modules. Because "We cannot control what we cannot measure", he is also interested in software quality topics, to measure the maintenance activity and legacy software.