Evolution

Every organization naturally evolves over time. This evolution is often driven by the business environment, that forces the organization to change its business processes, and, transitively, the information system that supports them. Practically, the integration of new concepts and new business rules generally translates into the introduction of new data structures and new program components, into the updating of existing components, or into the configuration of reusable features. The identification of requirements changes, their translation into system changes, and the application and deployment of the latter are collectively called information system evolution. PReCISE contributes to this field of research, by developing languages, methods, techniques and tools aiming to provide automated support to such evolution processes as information system understanding, migration, customization and evolution.

Themes

  • Information system understanding. Information system evolution requires understanding the extant system. Beyond the preliminary steps, namely requirements collection, analysis, design and coding, most, if not all, after-birth information system engineering processes require an in-depth understanding of each system component in order to maintain it, to evolve it, or to migrate it to a new platform.
  • Database evolution. Such database evolution scenarios as platform migration or schema change should, ideally, only impact the database component of the system. Unfortunately, the database most often has a deep influence over other components, like the application programs and the user interfaces, which must be adapted accordingly.
  • Software product lines. Information systems often evolve towards differentiated markets. This naturally leads to software product lines (SPL). SPL Engineering systematizes the management and evolution of similar products. When starting from legacy developments, a first step is to model the existing features and variabilities using reverse engineering, with the aim to allow their systematic management, and their rapid customization to individual customer's needs.

Scientific results

PReCISE has developed methodologies, techniques and tools (1) to recover implicit knowledge about a legacy information system, particularly about its database and its variability, (2) to support the co-evolution of information system artefacts in the context of platform migration and database schema change and (3) to build highly (re)configurable systems that can adapt to changing business requirements, customer needs, and execution contexts.

Industrial results

Industrial level methodologies and tools have been developed and practically used in several large-scale database migration projects for private companies and public administrations. Some of the research results are validated, exploited, maintained and extended by the ReveR spin-off.

Product line management tools include reasoners, model checkers, etc. A spin-off project called CONF&TI has just started to industrialize the SPL and variability-management technologies developed by PReCISE.

Resources

  • Selected Publications
    • Andreas Classen, Quentin Boucher, and Patrick Heymans. A text-based approach to feature modelling: Syntax and semantics of TVL. In Science of Computer Programming, Special Issue on Software Evolution, Adaptability and Variability, 76(12):1130-1143, 2011. Ranked A in CORE. Impact factor: 1.282.
    • Andreas Classen, Patrick Heymans, Pierre-Yves Schobbens, and Axel Legay. Symbolic model checking of software product lines. In Proceedings of the 33rd International Conference on Software Engineering (ICSE 2011), pp. 321–330. ACM, 2011. Ranked A* in CORE. Acceptance rate: 14%.
    • Andreas Classen, Patrick Heymans, Pierre-Yves Schobbens, Axel Legay, and Jean-François Raskin. Model checking lots of systems: Efficient verification of temporal properties in software product lines. In Proceedings of the 32nd International Conference on Software Engineering (ICSE 2010), Cape Town, South Africa, Proceedings, pages 335–344, ACM, 2010. Ranked A* in CORE. Acceptance rate: 13.7%.
    • Anthony Cleve, Tom Mens, and Jean-Luc Hainaut. Data-Intensive System Evolution. IEEE Computer, 43(8):110–112, August 2010. Rank A in CORE. Impact factor: 1.812.
    • Anthony Cleve, Anne-France Brogneaux, and Jean-Luc Hainaut. A Conceptual Approach to Database Applications Evolution. In Proceedings of the 27th International Conference on Conceptual Modeling (ER 2010), volume 6412 of Lecture Notes in Computer Science, pp. 132–145. Springer, 2010. Rank A in CORE. Acceptance rate: 20%.
    • Jean-Luc Hainaut, Anthony Cleve, Jean Henrard, and Jean-Marc Hick. Migration of Legacy Information Systems. In Tom Mens and Serge Demeyer, editors, Software Evolution, pp. 105–138. Springer, 2008.
    • Patrick Heymans, Pierre-Yves Schobbens, Jean-Christophe Trigaux, Yves Bontemps, Raimundas Matulevicius, Andreas Classen. Evaluating Formal Properties of Feature Diagram Languages, in IET Software Journal , volume 2, issue 3, pp. 281-302.
    • Andreas Metzger, Patrick Heymans, Klaus Pohl, Pierre-Yves Schobbens, Germain Saval. Disambiguating the Documentation of Variability in Software Product Lines: A Separation of Concerns, Formalization and Automated Analysis. In Proceedings of the 15th IEEE International Conference on Requirements Engineering (RE’07), pp. 243-253. Ranked A in CORE. Ranked A in CORE.  Acceptance rate: 12%.
    • Pierre-Yves Schobbens, Patrick Heymans, Jean-Christophe Trigaux. Feature Diagrams: A Survey and a Formal Semantics. In Proceedings of the 14th IEEE International Conference on Requirements Engineering (RE’06), pp. 139-148, 2006. Ranked A in CORE. Acceptance rate: 14%.
    • Pierre-Yves Schobbens, Patrick Heymans, Jean-Christophe Trigaux, and Yves Bontemps. Generic semantics of feature diagrams. Computer Networks, 51(2):456–479, 2007. Ranked A in CORE. Impact factor: 1.176.
    • Ravi Ramdoyal, Anthony Cleve, and Jean-Luc Hainaut. Reverse Engineering User Interfaces for Interactive Database Conceptual Analysis. In Proceedings of the 22nd International Conference on Advanced Information Systems Engineering (CAiSE 2010), volume 6051 of Lecture Notes in Computer Science, pp. 332–347. Springer, 2010. Rank A in CORE. Acceptance rate: 15%.
    • Philippe Thiran, Jean-Luc Hainaut, Geert-Jan Houben, Djamal Benslimane. Wrapper-based Evolution of Legacy Information Systems, in ACM Transactions on Software Engineering and Methodology (TOSEM), volume 15, issue 4, pp. 329-359, 2006. Rank A* in CORE. Impact factor: 1.694.

Products and services

  • Methodologies for database migration and evolution
  • DB-MAIN, a programmable data centered CASE platform
  • Software Product Line Methodology

Contributing projects

  • DB-MAIN (Database Engineering)
  • e-Health (Data interoperability through an e-Health platform)
  • RISTART (Evolution of large information systems)
  • Fundamental Issues in Modelling, Verification and Evolution of Software (MoVES)
  • Verification of recursive, evolutive, real-time software (VEREV)
  • Software Product Lines Verification (VLPL) 
  • Research network on software adaptability (Re2adapt) 
  • Modelling and model checking variability-intensive system (FTS)  

Former projects

  • BioMaze (Biochemical database evolution)
  • InterDB (Architecture, Methods and Tools for Database Federation)