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Model-driven development (MDD) in the Artificial Intelligence of Things (AIoT) domain faces significant challenges in ensuring the consistency and preservation of model properties during transformations, often leading to system inconsistencies. This research introduces the Property Preservation Framework (PPF), a novel approach fortified with a Markov chain methodology, specifically designed to address these challenges. The PPF integrates formal procedures and constraint-checking methods to systematically validate and preserve model properties, thereby enhancing the reliability of AIoT systems. Through empirical evaluations, the framework has demonstrated its ability to efficiently determine and verify model characteristics at various transformation stages, significantly reducing the incidence of property violations. The results indicate that the PPF not only ensures overall consistency and reliability but also optimizes resource allocation, thereby enhancing data efficiency during the property validation and preservation processes. These advancements make a substantial contribution to the domain of MDD, providing developers with the methodology to execute model transformations that accurately reflect system requirements and behaviors in AIoT ecosystems. The findings underscore the potential of the PPF to revolutionize AIoT development by ensuring high-quality, dependable, and efficient modeling outcomes.

BPMN process models have been widely used in software designs. The BPMN process models are characterized by a static graph-oriented modeling language and a lack of analytical capabilities as well as dynamic behavior verification capabilities, which not only leads to inconsistencies in the semantics of the BPMN process models, but also leads to a lack of model error detection capabilities for the BPMN process models, which also hinders the correctness verification and error correction efforts of the models. In this study, we propose an executable modeling approach for CPN-based data flow well-structured BPMN (dw-BPMN) process models, and consider both control-flow and data-flow perspectives. First, we present a formal definition of the dw-BPMN process model, which is formally mapped into a CPN executable model in three steps: splitting, mapping and combining. Then, we discuss four types of data flow errors that can occur in the model: missing, lost, redundant, and inconsistent data error. To detect these four data flow errors, we propose a detection method based on the execution results of the CPN model. Subsequently, we propose correction strategies for these four data flow errors. Finally, a dw-BPMN process model of a robot’s temperature detection system for COVID-19 prevention and control in a kindergarten was used as an example to verify the validity of the method.

Parallel scheduling of multiple real-time applications onto heterogeneous processors is needed in the emerging embedded systems such as self-driving cars, smart cameras, and smartphones. Assuming that an embedded application is specified as a synchronous dataflow (SDF) graph or its extension, we propose a novel parallel scheduling methodology based on an evolutionary algorithm where the mapping of tasks onto processors is evolved to optimize a given objective function in an iterative fashion. In each iteration, we use an existing worst-case response time (WCRT) analysis tool to check if all applications satisfy their real-time requirements by translating each SDF graph into a directed acyclic graph (DAG) that is assumed in the WCRT analysis tool. Since the WCRT analysis must be performed in each iteration of evolution, we propose a clustering technique to reduce drastically the analysis time that depends on the number of nodes and their dependency. We formally prove that the proposed clustering technique does not change the estimated WCRT of each application. The effectiveness of the proposed scheduling methodology with the clustering technique is verified with extensive experiments using real-life benchmarks, randomly generated graphs, and the comparison with the existing technique.

The ever-increasing number of mobile platforms constitutes a challenge for application developers, who must develop efficient mobile applications for multiple platforms. Recently, a specific interest is being taken in the Model Based User Interface Development (MBUID) by Software Engineering Community. In such paradigm, an application’s user interface is obtained by defining models and transformations of those models. This paper aim at adopting MBUID paradigm to address the problem of mobile application development. As such, we propose a new approach and its support system for the automatic generation of mobile user interfaces. The approach and the system are based on a set of standards and relevant technologies such as EMF, GMF, ATL, and Xpand. A case study is presented, in the paper, with the aim of verifying the usefulness of this approach.

In the early phases of the software development process, specifications are mostly written in a natural language rather than formal models, which is not supported by the Model Driven Architecture (MDA). For this reason, the Semantic of Business Vocabulary and Rules (SBVR) is proposed by the Object Management Group to represent the textual specifications in a language comprehensible by both of humans and machines, to facilitate its integration in the MDA lifecycle. However, businesspeople are usually not familiar with SBVR standard. In this paper we present an approach to automatically transform textual business rules to an SBVR model, to facilitate its integration in nowadays information technology infrastructures. Our approach is distinguished from existing works in that it uses an in-depth Natural Language Processing to extract a more comprehensible SBVR model that includes the semantic formulation of each business rule statement, coupled with a Terminological Dictionary of extracted concepts, to which we have added further specifications such as definitions and synonyms. The evaluation of our approach shows that for three sets of business rules statements taken from different domains, we could generate the correct meaning with an average of F1-score exceeding 87%.

AADL is widely used to depict the architecture and behavior of real-time safety-critical systems such as avionics and aerospace. The development of these systems has strict requirements for building fault-free systems. Formal verification is frequently applied to verify the critical properties of the systems, such as safety and liveness; however, the formal verification is not supported by AADL. Model transformation is commonly applied to provide formal semantics; hence, the AADL model can be verified by a language that supports formal verification in addition to the ability to cover all AADL model behavior. Event-B, with its proof obligation, is increasingly used to model and verify safety-critical systems. This paper presents the transformation of the AADL model into Event-B, which captures most AADL components and behavioral actions to be effective in the verification of current real-time systems models. Then, we define theorems and invariants of safety and liveness properties to be proven by using the RODIN platform. To demonstrate the efficacy of our method, we model the AADL of movement authority (MA) control of the Chinese Train Control System, transform the AADL model to Event-B and verify its crucial properties.

Model transformations and model-driven engineering (MDE) have been applied widely in service-oriented architecture based information systems. To support the development of such a service-oriented information system, it is necessary to guarantee the quality of model transformations. With the increasing complexity and scale of model transformations, debugging of model transformations becomes more and more time-consuming and difficult, there is an increasing need to rely on efficient and accurate fault localization approaches to help with debugging. Among the existing fault localization approaches, the spectrum-based fault localization (SBFL), as a dynamic analysis method, mainly used the coverage information and execution results of the rules of model transformation to estimate the probability of each rule may be faulty. However, there are many false-positive and false-negative results in the rule coverage information, the accuracy of the SBFL is not ideal, so we consider mining the impact of covered range in different test models to further improve the effectiveness of fault localization. In this paper, we propose an optimized strategy of fault localization based on the impact of the test model, according to the covered range of test models, weight values are assigned to different test models, and the statistical coverage information of rules are weighted and adjusted accordingly. We compare the proposed approach with the SBFL, the experimental results show that under the same techniques for computing the suspiciousness, our approach can help locate around 26% more faulty rules in the ranking Top-1 of the suspicious list than the SBFL, the effectiveness of fault localization techniques can be improved by 50.42% in the best case and 8.9% in the average case.

The BPMN design models are widely used in the software development process. Owing to the lack of BPMN standard semantics, formal verification is used to validate whether the BPMN design model is free of undesirable properties. The primary challenges of BPMN design model verification are the enormous size and complexity of BPMN design models; these challenges may lead to time-consuming processes for model abstraction and overcoming the state space explosion problem. This paper proposes a hierarchical verification technique for the state space analysis based on a colored Petri net (CPN). A BPMN partitioning technique and rules for the transformation of a BPMN into a CPN model are provided. The partitioning approach supports the unstructured BPMN design model, and the obtained CPN model also supports hierarchical verification. To validate and analyze the BPMN design model, the transformation technique and state space generator are implemented as a BPMN verification framework. This method is a viable option for the software process designers and is suitable for the large-scale BPMN design model verification.

This paper investigates the parameter estimation problem for multivariate output-error systems perturbed by autoregressive noises. To reduce the influence of the colored noises on parameter estimates, we turn the original model into the new model with white noises by using the model transformation. In consideration of the high dimensions of multivariate systems and different types of parameters, we decompose the transformed system model into several sub-models in accordance with the number of the outputs. However, the decomposition results in many redundant estimates. Here, we propose two algorithms to cut down the redundant estimates. By taking the average of the parameter estimation vectors, we develop a model transformation partially-coupled (MT-PC) recursive least squares algorithm. Moreover, an MT-PC recursive least squares algorithm is presented by means of the coupling identification concept. Compared with the multivariate recursive generalized least squares algorithm, the two algorithms have higher computational efficiencies and smaller estimation errors. Finally, an illustrative example is provided to demonstrate the effectiveness of the proposed algorithms.

Formal verification is a process to ensure that the business process model and notation (BPMN) design model is free of deadlock, livelock, and other undesirable properties that can cause a system crash. Formal verification is a complicated procedure involving model abstraction and model checking tools used for property checking. There are several existing transformation techniques that yield an abstract model, but the data perspective is not considered. These techniques are also inappropriate for the large-scale BPMN design model. An automated transformation can reduce the flaws, time consumption, and complexity of the large-scale BPMN design model. This paper proposes a transformation technique and provides a framework for transforming the BPMN design models into colored Petri nets (CPNs). Our techniques cover both the control-flow and data-flow perspectives. The partitioning technique of the BPMN design model is applied to reduce the complexity and leads to a CPN model that can support the hierarchical and compositional verification techniques that are suitable for the large-scale BPMN design models. The proposed transformation has been implemented as a transformation framework and is able to consistently transform the BPMN design models into CPN models.

In the modern era of mobile computing, context-aware computing is an emerging paradigm due to its widespread applications. Context-aware applications are gaining increasing popularity in our daily lives since these applications can determine and react according to the situational context and help users to enhance usability experience. However, testing these applications is not straightforward since it poses several challenges, such as generating test data, designing context-coupled test cases, and so on. However, the testing process can be automated to a greater extent by employing model-based testing technique for context-aware applications. To achieve this goal, it is necessary to automate model transformation, test data generation, and test case execution processes. In this paper, we propose an approach for behavior modeling of context-aware application by extending the UML activity diagram. We also propose an automated model transformation approach to transform the development model, i.e., extended UML activity diagram into the testing model in the form of function nets. The objective of this paper is to automate the context-coupled test case generation and execution. We propose a functional testing framework for automated execution of keyword-based test cases. Our functional testing framework can reduce the testing time and cost, thus enabling the test engineers to execute more testing cycles to attain a higher degree of test coverage.

This paper explores and describes the state of the art for what concerns the model-driven approaches proposed in the literature to support reverse engineering. We conducted a systematic literature review on this topic with the aim to answer three research questions. We focus on various solutions developed for model-driven reverse engineering, outlining in particular the models they use and the transformations applied to the models. We also consider the tools used for model definition, extraction, and transformation and the level of automation reached by the available tools. The model-driven reverse engineering approaches are also analyzed based on various features such as genericity, extensibility, automation of the reverse engineering process, and coverage of the full or partial source artifacts. We describe in detail and compare fifteen approaches applying model-driven reverse engineering. Based on this analysis, we identify and indicate some hints on choosing a model-driven reverse engineering approach from the available ones, and we outline open issues concerning the model-driven reverse engineering approaches.

AADL along with its Behavior Annex is an architecture and behavior description language for safety-critical domains, e.g. avionics, aerospace, and defence. In order to formally analyze behavior properties of AADL models, it is necessary to transform the AADL language into formal languages supported by formal verification tools. Moreover, comprehensive formal verification of AADL models highly requires that the transformation supports larger subset of the AADL language, as well as verification tools are able to capture various behavior of AADL, such as concurrency and timing. As an extended communicating sequential process (CSP), stateful timed CSP with its model checker-PAT provide an strongly expressive language and verification tool for real-time systems, distributed systems, and concurrent systems. This paper introduces a model transformation approach from a comparatively complete subset of AADL to stateful timed CSP, in particular supporting major components of AADL Behavior Annex. We propose a comprehensive set of transformation rules for AADL to stateful timed CSP. Then, we perform formal verification in PAT to analyze concurrent behavior properties of AADL models, such as safety, liveness, and trace refinement with various fairness assumptions, in which we consider time capacities, deadlines, periods of AADL threads and durations of AADL processes. As a study case, we develop an AADL model of F-16 “Auto Pilot Controller”and transform the model into Stateful Timed CSP. We specify a set of critical properties of the model and perform formal verification in PAT.

This paper investigates the sliding-mode control (SMC) problem of Takagi–Sugeno (T–S) fuzzy multiagent systems (MASs). A cooperative fuzzy-based dynamical sliding-mode (SM) controller is designed and the overall closed-loop T–S fuzzy MAS is constructed. A new model transformation method for T–S fuzzy MASs is presented to transform the fuzzy weighting matrix into a set of fuzzy weighting scalars. By applying the method of linear matrix inequality, a general stability analysis approach for T–S fuzzy MASs is proposed. Moreover, the energy-cost constraint problem is studied by using the linear quadratic regulator method. Finally, numerical examples are provided to illustrate the effectiveness of the proposed theoretical approaches and the improved performance compared to existing results. [ABSTRACT FROM AUTHOR]

Fault analysis and resolution of faults should be part of any end-to-end system development process. This paper is concerned with developing a formal transformation method that maps control flows modeled in unified modeling language activities to semantically equivalent fault trees. The transformation method developed features the use of propositional calculus and probability theory. Fault propagation chains are introduced to facilitate the method. An overarching metamodel comprised of transformations between models is developed and is applied to an understood traffic management system of systems problem to demonstrate the approach. In this way, the relational structure of the system behavior model is reflected in the structure of the fault tree. The paper concludes with a discussion of limitations of the transformation method and proposes approaches to extend it to object flows, state machines, and functional allocations. [ABSTRACT FROM AUTHOR]

Offshore cranes often work in harsh sea conditions. As a result, they may suffer from various external disturbances, especially the persistent and unpredictable ship motion caused by sea waves, which will introduce severe disturbances to the crane dynamics, including the unactuated part. Due to this reason, the control problem for offshore boom cranes presents great challenges, for which only boundedness or stability, instead of the generally desired asymptotic stability, of the closed-loop system can be usually guaranteed by currently available methods. For this problem, a novel nonlinear control strategy for an offshore crane is proposed in this brief, which ensures that the closed-loop system’s equilibrium point is asymptotically stable even in the presence of the persistent ship roll disturbances. The proposed control law is further extended to be an output feedback controller to deal with the situations when the velocities are unavailable, still guaranteeing asymptotic stability. Finally, some experimental results are provided to validate the efficiency of the proposed controllers. [ABSTRACT FROM PUBLISHER]

A software system's requirements are often specified by textual use cases due to the latter's concrete and narrative style of expressions. However, they have limitation in the synthesis of the system behavior since they have a poor basis for the formal interpretation. Existing synthesis techniques are either largely manual or focus on the use case interactions. We present a framework from a model-based point of view to automatically synthesize system behavior from textual use cases to a Petri net model. The generated net model can well describe component module interactions and thus can be used to check the requirement properties. The function of Send-Railway-Emergency-Call of European Integrated Railway Radio Enhanced Network is used to show the proposed method. Moreover, the experimental results on a set of examples demonstrate the effectiveness of the proposed method. [ABSTRACT FROM PUBLISHER]

The currents and voltages in the multiphase transmission line are described by differential equations that sometimes can be difficult to solve due the mutual coupling and skin effect that have to be considered for accurate results. An alternative consists in using a matrix to decompose the multiphase transmission line in n single phase systems uncoupled. For evaluating modal voltages and currents, each system will be represented by two models well-known for studies in electromagnetic transients in transmission line. The first model uses the lumped parameters to represent the transmission line and it is developed directly in the time domain. The second model uses the distributed parameters and transforms the differential equations in the time domain to algebraic equations in the frequency domain using Laplace Transform. Once solved them, it can be applied the inverse transformation and the solutions are obtained in the time domain. It can be observed the presence of spurious oscillations in the lumped model simulations. This work will analyze the spurious oscillations in the voltages in the open receiving end using, considering a fixed length transmission line, represented by different quantities of circuits during energization process. [ABSTRACT FROM PUBLISHER]

As the complexity of model transformations grows, there is an increasing need to count on methods, mechanisms, and tools for checking their correctness, i.e., the alignment between specifications and implementations. In this paper we present a light-weight and static approach for locating the faulty rules in model transformations, based on matching functions that automatically establish these alignments using the metamodel footprints, i.e., the metamodel elements used. The approach is implemented for the combination of Tracts and ATL, both residing in the Eclipse Modeling Framework, and is supported by the corresponding toolkit. An evaluation discussing the accuracy and the limitations of the approach is also provided. Furthermore, we identify the kinds of transformations which are most suitable for validation with the proposed approach and use mutation techniques to evaluate its effectiveness. [ABSTRACT FROM PUBLISHER]