Models@Runtime: The Development and Re-Configuration Management of Python Applications Using Formal Methods
Source abstract
Abstract
Models@runtime (models at runtime) are based on computation reflection. Runtime models can be regarded as a reflexive layer causally connected with the underlying system. Hence, every change in the runtime model involves a change in the reflected system, and vice versa. To the best of our knowledge, there are no runtime models for Python applications. Therefore, we propose a formal approach based on Petri Nets (PNs) to model, develop, and reconfigure Python applications at runtime. This framework is supported by a tool whose architecture consists of two modules connecting both the model and its execution. The proposed framework considers execution exceptions and allows users to monitor Python expressions at runtime. Additionally, the application behavior can be reconfigured by applying Graph Rewriting Rules (GRRs). A case study using Service-Level Agreement (SLA) violations is presented to illustrate our approach.
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Research context
OpenAlex topics: Model-Driven Software Engineering Techniques · Advanced Software Engineering Methodologies · Service-Oriented Architecture and Web Services
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
MISC Laboratory, Department of Computer Science and Its Applications, University Constantine 2 Abdelhamid Mehri, Constantine 25016, Algeria
Instituto de Investigación en Informática, Universidad de Castilla-La Mancha, 02071 Albacete, Spain
Faculty of Medicine, University Constantine 3 Salah Boubnider, Constantine 25016, Algeria
Funding
Ministerio de Ciencia, Innovación y Universidades, Spain · European Union · Regional Government of Castile-La Mancha · University of Castilla-La Mancha · Algerian Ministry of Higher Education and Scientific Research
References (35)
Show source-provided references
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