Al Science Foundation of China (Project No. 20973008, No. 51902344). Institutional Overview Board
Al Science Foundation of China (Project No. 20973008, No. 51902344). Institutional Evaluation Board Statement: Not applicable. Informed Consent Statement: Not applicable. Data Availability Statement: The data presented in this study are accessible from the corresponding author upon affordable request. Acknowledgments: We appreciate Yang Liu, Institute of Chemistry, Chinese Academy of Sciences, for his help with all the data evaluation. Conflicts of Interest: The authors declare no conflict of interest.
applied sciencesArticleModels@Runtime: The Development and Re-Configuration Management of Python Applications Utilizing Formal MethodsMohammed Mounir Bouhamed 1 , Gregorio D z 2, , Allaoua Chaoui 1 and Radouane Nouaraand Oussama Kamel 1,2MISC Laboratory, Department of Laptop Science and Its Applications, University Constantine 2 Abdelhamid Mehri, Constantine 25016, Algeria; [email protected] (M.M.B.); [email protected] (A.C.); [email protected] or [email protected] (O.K.); [email protected] (R.N.) Instituto de Investigaci en Inform ica, Universidad de Castilla-La Mancha, 02071 Albacete, Spain Faculty of Medicine, University Constantine three Salah Boubnider, Constantine 25016, Algeria Correspondence: [email protected]; Tel.: +34-650-29-95-Citation: Bouhamed, M.M.; D z, G.; Chaoui, A.; Kamel, O.; Nouara, R. Models@Runtime: The Development and Re-Configuration Management of Python Applications Making use of Formal Methods. Appl. Sci. 2021, 11, 9743. https://doi.org/10.3390/ app11209743 Academic Editor: Alessandro Di Nuovo Received: 13 September 2021 Gossypin NF-��B Accepted: 9 October 2021 Published: 19 OctoberAbstract: Models@(S)-Venlafaxine In stock Runtime (models at runtime) are depending on computation reflection. Runtime models could be regarded as a reflexive layer causally connected with the underlying method. Therefore, each alter in the runtime model includes a alter inside the reflected technique, and vice versa. To the most effective of our understanding, there are actually no runtime models for Python applications. Therefore, we propose a formal method according to 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 permits users to monitor Python expressions at runtime. On top of that, the application behavior may be reconfigured by applying Graph Rewriting Guidelines (GRRs). A case study applying Service-Level Agreement (SLA) violations is presented to illustrate our strategy. Keywords: models@runtime; python application; petri nets; formal methods; graph rewriting rules; application re-configuration; application management1. Introduction This operate is motivated by two interrelated necessities of application development: computational reflection and change control. Computational reflection, as described by Maes [1], is “the activity performed by a computational program when undertaking computations about its own computation”. In other words, computational reflection is often a program’s ability to modify itself though operating. Moreover, computer software improvement is depending on addressing two troubles already stated in the 1970s by the very first two of Lehman’s laws: “continuous change” and “increasing complexity” [2]. These complications arise from the need for the software program to become adapted towards the new user specifications, major to software changes that enhance the c.