Abstract—When modeling requirements, software analysts have to choose the relevant modeling constructs among all those available. If they do not choose the right set, their model may lack some important information or their model may contain many superfluous details. In previous work, we proposed to capture the purpose of a model with a set of model operations such as queries or model transformations. Then, modelers can analyze the footprints of these operations, that is, the set of model elements touched during their execution. In this paper, we report on two controlled experiments performed with students to evaluate whether footprinting can help them in creating better models. While our studies did not demonstrate statistically significan...
The variety of design artefacts (models) produced in a model-driven design process results in an int...
Model building in machine learning is an iterative process. The performance analysis and debugging s...
In the area of student knowledge assessment, knowledge tracing is a model that has been used for ove...
International audienceWhen modeling requirements, software analysts have to choose the relevant mode...
International audienceWhen performed on a model, a set of operations (e.g., queries or model transfo...
The variety of design artifacts (models) produced in a model-driven design process results in an int...
Context: Requirements Traceability (RT) is concerned with monitoring and documenting the lifecycle o...
Model-driven engineering (MDE) is a software engineering discipline that is gaining popularity, both...
International audienceModel-Driven Engineering is a development paradigm that uses models instead of...
[Context and Motivation] Requirements Traceability (RT) aims to follow and describe the lifecycle of...
This paper presents quality goals for models and provides a state-of-the-art analysis regarding mode...
International audienceContext: Software systems are often too complex to be expressed by a single mo...
The potential of ecological models for supporting environmental decision making is increasingly ackn...
The variety of design artefacts (models) produced in a model-driven design process results in an int...
Model building in machine learning is an iterative process. The performance analysis and debugging s...
In the area of student knowledge assessment, knowledge tracing is a model that has been used for ove...
International audienceWhen modeling requirements, software analysts have to choose the relevant mode...
International audienceWhen performed on a model, a set of operations (e.g., queries or model transfo...
The variety of design artifacts (models) produced in a model-driven design process results in an int...
Context: Requirements Traceability (RT) is concerned with monitoring and documenting the lifecycle o...
Model-driven engineering (MDE) is a software engineering discipline that is gaining popularity, both...
International audienceModel-Driven Engineering is a development paradigm that uses models instead of...
[Context and Motivation] Requirements Traceability (RT) aims to follow and describe the lifecycle of...
This paper presents quality goals for models and provides a state-of-the-art analysis regarding mode...
International audienceContext: Software systems are often too complex to be expressed by a single mo...
The potential of ecological models for supporting environmental decision making is increasingly ackn...
The variety of design artefacts (models) produced in a model-driven design process results in an int...
Model building in machine learning is an iterative process. The performance analysis and debugging s...
In the area of student knowledge assessment, knowledge tracing is a model that has been used for ove...