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 Zurich, Switzerland
  • 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.

PREVIOUS TRACK EDITIONS

QUATIC 2019, QUATIC 2012, QUATIC 2010