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SoSyM Ten-year most influential paper award
The paper “A model-driven traceability framework for software product lines”, by Nicolas Anquetil, Uirá Kulesza, Ralf Mitschke, Ana Moreira, Jean-Claude Royer, Andreas Rummler and André Sousa, was distinguished with the 2020 SoSyM Ten-year most influential Regular Paper Award.
This award is given every year to the authors of a regular paper published in the Journal on Software & System Modeling which had the most influence within the past decade.
In this article, the authors propose the AMPLE Traceability Framework (ATF), produced in the context of the European AMPLE project, to support the creation and evolution of software product lines (SPL). Traceability in software development refers to the ability of keeping track of a given requirement or software module, hence allowing us to trace product requirements back to stakeholders needs and forward to correlated design artifacts and decisions, code, and tests. It is therefore fundamental to software maintenance and evolution. Software product line engineering, on the other hand, supports the derivation of cost-effective software product families from a set of reusable components and services, using a common production method. Therefore, SPL engineering is about large-scale planned reuse.
ATF offers mechanisms to manage the traceability of heterogeneous models and artifacts for SPL domain and application engineering, not supported by the approaches and tools available back in 2009, offering good support to define an open and extensible reference model for traceability. This framework is process-agnostic, flexible, scalable and extensible. The first major contribution embodies four orthogonal traceability dimensions, namely refinement, similarity, variability, and versioning. The second contribution is the specification of a metamodel for a repository of traceability links and the implementation of the framework. ATF enables fundamental traceability management operations, such as queries, trace import and export, modification, and visualization.
The paper was presented by Ana Moreira, researcher from NOVA LINCS Software Systems Group, at the 23rd International Conference on Model Driven Engineering Languages and Systems (MODELS 2020).