Model-driven applications may maintain large networks of structured data models and transformations among them. The development of such applications is complicated by the need to reflect on the whole network any runtime update performed on models or transformation logic. If not carefully designed, the execution of such updates may be computationally expensive. In this paper we propose a reactive paradigm for programming model transformations, and we implement a reactive model-transformation engine. We argue that this paradigm facilitates the development of autonomous model-driven systems that react to update and request events from the host application by identifying and performing only the needed computation. We implement such approach by providing a reactive engine for the ATL transformation language. We evaluate the usage scenarios that this paradigm supports and we experimentally measure its ability to reduce computation time in transformation-based applications.
The Java EE framework, a popular technology of choice for the development of web applications, provides developers with the means to define access-control policies to protect application resources from unauthorized disclosures and manipulations. Unfortunately, the definition and manipulation of such security policies remains a complex and error prone task, requiring expert-level knowledge on the syntax and semantics of the Java EE access-control mechanisms. Thus, misconfigurations that may lead to unintentional security and/or availability problems can be easily introduced. In response to this problem, we present a (model-based) reverse engineering approach that automatically evaluates a set of security properties on reverse engineered Java EE security configurations, helping to detect the presence of anomalies. We evaluate the efficacy and pertinence of our approach by applying our prototype tool on a sample of real Java EE applications extracted from GitHub.
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