The development and management of software-intensive systems requires high-level expertise and a fine network of interactions between complementary disciplines, in particular software engineering, computer science and information management.

NADI promotes scientific research in and between these disciplines, and aims to reduce the gap between them. The Institute brings together a wide range of internationally recognized skills covering the entire software development cycle - from requirements engineering and modeling to testing and evolution. It considers a variety of software system artifacts, including human-machine interfaces, requirements specifications, software architectures, variability models, structural and behavioral models, source code, databases, access control models or natural language forum discussions.

NADI researchers have recently been investigating various topics related to software and systems engineering and management: AI and recommendation techniques for software engineering; software product lines for configuration management; mutation testing, static program analysis for code duplication and plagiarism detection; repository mining and program analysis for quality assessment; database evolution and reconfiguration in hybrid polystores; blockchain for inter-organizational processes; adaptive, multimodal and tangible interface development, augmented reality; and programming and software development education.

Beyond their scientific contributions and industrial collaborations in their respective fields, NADI members also regularly contribute to building a more inclusive (digital) society. The Silverkit and SSL projects aim to design software capable of automatically adapting to elderly users. The SILENT project aims to build an interactive online dictionary of French sign language and Franco-Belgian sign language, to be used by linguists, interpreters, translators, teachers and language learners. The SQLFast project aims to develop tools, methods and case studies, exploiting database theories and technologies to aid problem solving. These tools are primarily aimed at non-professional IT users, who are confronted with complex problems of data collection, storage, processing and presentation. As part of the VeriLearn project, NADI researchers are investigating important societal issues related to the use of machine learning in various fields. For example, in collaboration with KULeuven, they recently proposed a framework to improve the fairness of deep learning algorithms with regard to certain sensitive attributes (gender, skin color, ...) while preserving their performance. The above contributions illustrate the interdisciplinary nature of the work carried out as part of NADI.

• V. Amaral De Sousa, C. Burnay. Towards an integrated methodology for the development of blockchain-based solutions supporting cross-organizational processes. In Proc. of RCIS 2019: 1-6.
• V. Amaral De Sousa, C. Burnay, M. Snoeck. B-MERODE: A Model-Driven Engineering and Artifact-Centric Approach to Generate Blockchain-Based Information Systems. In Proc. of CAiSE 2020: 117-133.
• M. Belarbi, V. Englebert. Bespoke: a Methodology to design Software Factories. A preliminary approach. In Proc. of RCIS 2019: 1-6.
• A. Classen, P. Heymans, P.-Y. Schobbens, A. Legay, and J.-F. Raskin, J. F. (2010). Model checking lots of systems: efficient verification of temporal properties in software product lines. In Proc. of the 32nd ACM/IEEE International Conference on Software Engineering-Volume 1 (pp. 335-344). Most Influential Paper Award 2020.
• M. Cronel, B. Dumas, P. Palanque, and A. Canny. MIODMIT: a generic architecture for dynamic multimodal interactive systems. 2018, pp. 109--129.
• P. Delobelle P. Temple, G. Perrouin, B. Frénay, P. Heymans, B. Berendt. Ethical Adversaries: Towards Mitigating Unfairness with Adversarial Machine Learning. 1st Workshop on Bias and Fairness in Machine Learning @ECML-PKDD 2020.
• P. Derakhshanfar, X. Devroey, G. Perrouin, A. Zaidman, A. van Deursen. Search-based crash reproduction using behavioural model seeding. Software Testing, Verification and Reliability. 2020 May ;30(3):e1733.
• X. Devroey, G. Perrouin, M. Papadakis, A. Legay, P.-Y. Schobbens and P. Heymans. Featured model-based mutation analysis. In Proc. of the 38th International Conference on Software Engineering (ICSE 2016), pp. 655-666.
• C. Duarte, S. Desart, D. Costa, and B. Dumas. Designing multimodal mobile interaction for a text messaging application for visually impaired users, Frontiers in ICT, vol. 4, p. 26, 2017.
• B. Duhoux, K. Mens and B. Dumas. Feature visualiser: An inspection tool for context-oriented programmers. In Proceedings of the 10th International Workshop on Context-Oriented Programming: Advanced Modularity for Run-time Composition (pp. 15-22), 2018.
• B. Dumas, J. Pirau, and D. Lalanne. Modelling fusion of modalities in multimodal interactive systems with MMMM, 2017, pp. 288--296.
• J. Fink, M. Gobert, and A. Cleve. Adapting Queries to Database Schema Changes in Hybrid Polystores. In Proc. of the 20th IEEE International Working Conference on Source Code Analysis and Manipulation (SCAM 2020). NIER Track. IEEE Computer Society Press, 2020. Best paper award 2020.
• J.-M. Jacquet, and M. Barkallah, Scan: A Simple Coordination Workbench. Proceedings of the 21st Conference on Coordination Models and Languages, Lecture Notes in Computer Science, vol. 11533, pp. 75-91, 2019.
• I. Jureta. What Happens to Intentional Concepts in Requirements if Intentional States Cannot Be Known? In Proc. of ER 2017: 209-222.
• A. Koshima, V. Englebert, M. Amrani, A. Debieche, A. Wakjira. A Model-Driven Engineering Approach for the Well-Being of Ageing People. In ER Workshops 2016: 21-29.
• C. Libert and W. Vanhoof. Analysis of students' preconceptions of concurrency. In EASEAI 2019. In Proceedings of the 1st ACM SIGSOFT International Workshop in Education through Advanced Software Engineering and Artificial Intelligence, ACM Press, pp. 9-12.
• L. Meurant, M. Gobert, A. Cleve: Modelling a Parallel Corpus of French and French Belgian Sign Language. In Proc. of LREC 2016.
• L. Meurice, C. Nagy, and A. Cleve. Static Analysis of Dynamic Database Usage in Java Systems. In Proc. of the 28th International Conference on Advanced Information Systems Engineering (CAiSE 2016), LNCS 9694, pp 491--506. Springer, 2016.
• L. Meurice, C. Nagy, and A. Cleve. Detecting and Preventing Program Inconsistencies under Database Schema Evolution. In Proc. of the 2016 IEEE International Conference on Software Quality, Reliability and Security (QRS 2016), pp 262--273. IEEE Computer Society, 2016. }{Best paper award 2016.
• F. Mesnard, E. Payet, W. Vanhoof. Towards a framework for algorithm recognition in binary code. In Principles and Practice of Declarative Programming 2016, Edinburgh, United Kingdom. ACM Press, pp. 202-213.
• P.-Y. Schobbens, P. Heymans, and J.-C. Trigaux. Feature diagrams: A survey and a formal semantics. 14th IEEE International Requirements Engineering Conference (RE'06). IEEE, 2006. Most Influential Paper Award 2016
• P. Temple, G. Perrouin, M. Acher, B. Biggio, J.-M. Jézéquel, F. Roli, Empirical Assessment of Generating Adversarial Configurations for Software Product Lines, Empirical Software Engineering Journal, To appear, Springer.
• G. Yernaux, W. Vanhoof and L. Schumacher. Moulinog: A Generator of Random Student Assignments Written in Prolog. In Principles and Practice of Declarative Programming 2020, ACM Press.
• G. Yernaux and W. Vanhoof. Anti-unification in Constraint Logic Programming. In Theory and Practice of Logic Programming, 19(5-6):773-789, 2019.

• DISSE - Data-Intensive Software System Evolution, 2013-2017.
• IDEES - The Internet of Tomorrow, 2017-2020.
• INSTINCT - Improving Database Interactions in NoSQL Applications, 2020-2024
• SECO-ASSIST - Automated Assistance for Developing Software in Ecosystems of the Future, 2018-2022.
• SILENT - Towards an online contextual dictionary of LSFB-French, 2018-2021.
• SILVERKIT - Self-adaptive software for elderly users, since 2018.
• SSL -- Smart Socialized Living, 2020-2022.
• TYPHON - Polyglot and Hybrid Persistence Architectures for Big Data Analytics, 2017-2020
• VERILEARN - Verifying Learning Artificial Intelligence Systems, 2018-2022