Assessing and improving quality of QVTo model transformations

We investigate quality improvement in QVT operational mappings (QVTo) model transformations, one of the languages defined in the OMG standard on model-to-model transformations. Two research questions are addressed. First, how can we assess quality of QVTo model transformations? Second, how can we develop higher-quality QVTo transformations? To address the first question, we utilize a bottom–up approach, starting with a broad exploratory study including QVTo expert interviews, a review of existing material, and introspection. We then formalize QVTo transformation quality into a QVTo quality model. The quality model is validated through a survey of a broader group of QVTo developers. We find that although many quality properties recognized as important for QVTo do have counterparts in general purpose languages, a number of them are specific to QVTo or model transformation languages. To address the second research question, we leverage the quality model to identify developer support tooling for QVTo. We then implemented and evaluated one of the tools, namely a code test coverage tool. In designing the tool, code coverage criteria for QVTo model transformations are also identified. The primary contributions of this paper are a QVTo quality model relevant to QVTo practitioners and an open-source code coverage tool already usable by QVTo transformation developers. Secondary contributions are a bottom–up approach to building a quality model, a validation approach leveraging developer perceptions to evaluate quality properties, code test coverage criteria for QVTo, and numerous directions for future research and tooling related to QVTo quality

A bottom-up quality model for QVTo

We investigate the notion of quality in QVT Operational Mappings (QVTo), one of the languages defined in the OMG standard on model-to-model transformations. We utilize a bottom-up approach, starting with a broad exploratory study including QVTo expert interviews, a review of existing material, and introspection. We then formalize QVTo transformation quality into a QVTo quality model, consisting of high-level quality goals, quality properties, and evaluation procedures. We validate the quality model by conducting a survey in which a broader group of QVTo developers rate each property on its importance to QVTo code quality. We find that although many quality properties recognized as important for QVTo do have counterparts in traditional languages, a number are specific to QVTo or model transformation languages. Additionally, a selection of QVTo best practices discovered are presented. The primary contribution of this paper is a QVTo quality model relevant to QVTo practitioners, while secondary contributions are a bottom-up approach to building a quality model and a validation approach leveraging developer perceptions to evaluate individual quality properties

Assessing and improving quality of QVTo model transformations

We investigate quality improvement in QVT operational mappings (QVTo) model transformations, one of the languages defined in the OMG standard on model-to-model transformations. Two research questions are addressed. First, how can we assess quality of QVTo model transformations? Second, how can we develop higher-quality QVTo transformations? To address the first question, we utilize a bottom–up approach, starting with a broad exploratory study including QVTo expert interviews, a review of existing material, and introspection. We then formalize QVTo transformation quality into a QVTo quality model. The quality model is validated through a survey of a broader group of QVTo developers. We find that although many quality properties recognized as important for QVTo do have counterparts in general purpose languages, a number of them are specific to QVTo or model transformation languages. To address the second research question, we leverage the quality model to identify developer support tooling for QVTo. We then implemented and evaluated one of the tools, namely a code test coverage tool. In designing the tool, code coverage criteria for QVTo model transformations are also identified. The primary contributions of this paper are a QVTo quality model relevant to QVTo practitioners and an open-source code coverage tool already usable by QVTo transformation developers. Secondary contributions are a bottom–up approach to building a quality model, a validation approach leveraging developer perceptions to evaluate quality properties, code test coverage criteria for QVTo, and numerous directions for future research and tooling related to QVTo quality

Formalizing correspondence rules for automotive architecture views

Architecture views have long been used in software industry to systematically model complex systems by representing them from the perspective of related stakeholder concerns. However, consensus has not been reached for the architecture views between automotive architecture description languages and automotive architecture frameworks. Therefore, this paper presents the automotive architecture views based on an elaborate study of existing automotive architecture description techniques. Furthermore, we propose a method to formalize correspondence rules between architecture views to enforce consistency between architecture views. The approach was implemented in a Java plugin for IBM Rational Rhapsody and evaluated in a case study based on the Adaptive Cruise Control system. The outcome of the evaluation is considered to be a useful approach for formalizing correspondences between different views and a useful tool for automotive architects

Formalizing correspondence rules for automotive architectural views

Architecture views have long been used in software industry to systematically model complex systems by representing them from the perspective of related stakeholder concerns. However, consensus has not been reached for the architecture views between automotive architecture description languages and automotive architecture frameworks. Therefore, this paper presents the automotive architecture views based on an elaborate study of existing automotive architecture description techniques. Furthermore, we propose a method to formalize correspondence rules between architecture views to enforce consistency between architecture views. The approach was implemented in a Java plugin for IBM Rational Rhapsody and evaluated in a case study based on the Adaptive Cruise Control system. The outcome of the evaluation is considered to be a useful approach for formalizing correspondences between different views and a useful tool for automotive architects