Investigation of Tools, Techniques and Languages for Model Driven Software Product Lines (SPL): A Systematic Literature Review

Software development is a complex and difficult task that requires the investment of sufficient resources and carries major risk of failure. Model Driven Engineering (MDE) focuses on creating software models and automating code generation from the models. Model Driven Software Development (MDSD) offers significantly more effective approaches. These approaches improve the way of building software. Model driven approaches partially increase developer productivity, decrease the cost of software construction, improve software reusability, and make software more maintainable. This paper investigates the methods where Model Driven Software Development is integrated with Software Product Line (SPL). This SLR has been conducted to identify 71 research works published since 2014. We have collected 18 tools, 14 techniques and 17 languages used for MDSD for SPL. We analyze which technique is suitable for SPL. We compare the techniques on the basis of features provided by these tools to understand the better-quality results.

MODEL-BASED DEVELOPMENT OF REAL-TIME SOFTWARE SYSTEM FOR ELECTRONIC UNIT PUMP SYSTEM

A real-time operating system （RTOS）, also named OS, is designed based on the hardware platform of MC68376, and is implemented in the electronic control system for unit pump in diesel engine. A parallel and time-based task division method is introduced and the multi-task software architecture is built in the software system for electronic unit pump （EUP） system. The V-model software development process is used to control algorithm of each task. The simulation results of the hardware-in-the-loop simulation system （HILSS） and the engine experimental results show that the OS is an efficient real-time kernel, and can meet the real-time demands of EUP system; The built multi-task software system is real-time, determinate and reliable. V-model development is a good development process of control algorithms for EUP system, the control precision of control system can be ensured, and the development cycle and cost are also decreased.

UML-based combat effectiveness simulation system modeling within MDE

To reduce complexity, the combat effectiveness simulation system(CESS) is often decomposed into static structure,physical behavior, and cognitive behavior, and model abstraction is layered onto domain invariant knowledge(DIK) and application variant knowledge(AVK) levels. This study concentrates on the specification of CESS’s physical behaviors at the DIK level of abstraction, and proposes a model driven framework for efficiently developing simulation models within model-driven engineering(MDE). Technically, this framework integrates the four-layer metamodeling architecture and a set of model transformation techniques with the objective of reducing model heterogeneity and enhancing model continuity. As a proof of concept, a torpedo example is illustrated to explain how physical models are developed following the proposed framework. Finally, a combat scenario is constructed to demonstrate the availability, and a further verification is shown by a reasonable agreement between simulation results and field observations.

Development of River Rating Curves for Simple to Complex Hydraulic Structure Based on Calibrated HEC-RAS Hydraulic Model, in Kwale, Coastal Kenya

Accurate and reliable river flow information is critical to planning and management for sustainable water resources utilization. Most of engineering activities related to hydrologic designs, flood, drought, reservoirs and their operations are heavily dependent on the river flow information derived from river rating curve. The rating curve for a given river section is normally developed from a set of direct stage-discharge measurements for different periods. This involves considerable labour, risk and resources, and presupposes a complex and extensive measuring survey. Extrapolating the rating curve beyond the measured range, as common in many cases, is fraught with errors and uncertainties, due to the complex hydraulic behaviour of the surface water profile in transition from section, channel, downstream and flood plain controls which are often poorly understood with direct measurements. Hydraulic modeling has recently emerged as one of the more promising methods to efficiently develop accurate rating curves for a river section with simple or complex hydraulic structures and conditions. This paper explores the use of a Hydraulic Engineering Center-River Analysis System (HEC-RAS) model to review and develop river rating curves for three hydrometric stations on two rivers in Kwale, coastal Kenya. The HEC-RAS models were set up based on topographical (cross section and longitudinal) survey data for the reaches and engineering drawings for the hydraulic structures commonly used as section controls for flow measurement. The model was calibrated under unsteady state conditions against measured stage-discharge data which were captured using a Velocity Current Meter (Valeport) and an Acoustic Doppler Current Profiler (ADCP) for both low and high flow. The rating curves were extracted from model results and the uncertainty associated with each rating curve analyzed. The results obtained by the HEC-RAS model were satisfactory and deemed acceptable for predicting discharge across the stage range at each river section.

Urban Development Boundary Simulation Based on“Double Evaluation”and FLUS Model

The delimitation of urban development boundaries plays an important role in optimizing the nation land space.“Double evaluation”is one of the important means to study and predict the scale of new construction land in the future and to determine the spatial distribution of urban construction land.This study combines the“double evaluation”with the FLUS(Future Land-Use Simulation)model to study the delimitation of the urban development boundary of Yichang.The results show that:(1)the“double evaluation”method comprehensively considers the carrying capacity of the resource environmental bear and the suitability of urban development;(2)the FLUS model can better couple the“double evaluation”method for Land Use/Land Cover(LULC)suitability evaluation,Land Use/land Cover Change(LUCC)simulation and urban development boundary delineation,and the overall accuracy of the simulation reaches 96%;(3)according to the requirements of relevant national policies,this study divides the urban development boundary of the study area into concentrated construction areas,elastic development areas and special purpose areas.This function-based division can meet the requirements of urban flexible development,ecological protection and urban safety.This research combines the FLUS model,which is widely used in the simulation of LUCC,with the double evaluation method used in China’s new round of land and space planning to obtain the result of the urban development boundary.This result is consistent with the existing plan of the study area.

Towards a Model-Driven IEC 61131-Based Development Process in Industrial Automation

The IEC 61131-3 standard defines a model and a set of programming languages for the development of industrial automation software. It is widely accepted by industry and most of the commercial tool vendors advertise compliance with it. On the other side, Model Driven Development (MDD) has been proved as a quite successful paradigm in general-purpose computing. This was the motivation for exploiting the benefits of MDD in the industrial automation domain. With the emerging IEC 61131 specification that defines an object-oriented (OO) extension to the function block model, there will be a push to the industry to better exploit the benefits of MDD in automation systems development. This work discusses possible alternatives to integrate the current but also the emerging specification of IEC 61131 in the model driven development process of automation systems. IEC 61499, UML and SysML are considered as possible alternatives to allow the developer to work in higher layers of abstraction than the one supported by IEC 61131 and to more effectively move from requirement specifications into the implementation model of the system.

Model architecture-oriented combat system effectiveness simulation based on MDE

Combat system effectiveness simulation (CSES) is a special type of complex system simulation. Three non-functional requirements (NFRs), i.e. model composability, domain specific modeling, and model evolvability, are gaining higher priority from CSES users when evaluating different modeling methodologies for CSES. Traditional CSES modeling methodologies are either domain-neutral (lack of domain characteristics consideration and limited support for model composability) or domain-oriented (lack of openness and evolvability) and fall short of the three NFRs. Inspired by the concept of architecture in systems engineering and software engineering fields, we extend it into a concept of model architecture for complex simulation systems, and propose a model architecture-oriented modeling methodology in which the model architecture plays a central role in achieving the three NFRs. Various model-driven engineering (MDE) approaches and technologies, including simulation modeling platform (SMP), unified modeling language (UML), domain specific modeling (DSM), eclipse modeling framework (EMF), graphical modeling framework (GMF), and so forth, are applied where possible in representing the CSES model architecture and its components' behaviors from physical and cognitive domain aspects. A prototype CSES system, called weapon effectiveness simulation system (WESS), and a non-trivial air-combat simulation example are presented to demonstrate the methodology.

Object-oriented Battlefield Environment Simulation Process Object Model Based on Task-driven

Battlefield environment simulation process is an important part of battlefield environment information support, which needs to be built around the task process. At present, the interoperability between battlefield environment simulation system and command and control system is still imperfect, and the traditional simulation data model cannot meet war fighters’ high-efficient and accurate understanding and analysis on battlefield environment’s information. Therefore, a kind of task-orientated battlefield environment simulation process model needs to be construed to effectively analyze the key information demands of the command and control system. The structured characteristics of tasks and simulation process are analyzed, and the simulation process concept model is constructed with the method of object-orientated. The data model and formal syntax of GeoBML are analyzed, and the logical model of simulation process is constructed with formal language. The object data structure of simulation process is defined and the object model of simulation process which maps tasks is constructed. In the end, the battlefield environment simulation platform modules are designed and applied based on this model, verifying that the model can effectively express the real-time dynamic correlation between battlefield environment simulation data and operational tasks.

Discrete Event Simulation-Based Evaluation of a Single-Lane Synchronized Dual-Traffic Light Intersections

This research involved an exploratory evaluation of the dynamics of vehicular traffic on a road network across two traffic light-controlled junctions. The study uses the case study of a one-kilometer road system modelled on Anylogic version 8.8.4. Anylogic is a multi-paradigm simulation tool that supports three main simulation methodologies: discrete event simulation, agent-based modeling, and system dynamics modeling. The system is used to evaluate the implication of stochastic time-based vehicle variables on the general efficiency of road use. Road use efficiency as reflected in this model is based on the percentage of entry vehicles to exit the model within a one-hour simulation period. The study deduced that for the model under review, an increase in entry point time delay has a domineering influence on the efficiency of road use far beyond any other consideration. This study therefore presents a novel approach that leverages Discrete Events Simulation to facilitate efficient road management with a focus on optimum road use efficiency. The study also determined that the inclusion of appropriate random parameters to reflect road use activities at critical event points in a simulation can help in the effective representation of authentic traffic models. The Anylogic simulation software leverages the Classic DEVS and Parallel DEVS formalisms to achieve these objectives.

A New Approach to Software Development Fusion Process Model

There are several software process models that have been proposed and are based on task involved in developing and maintaining software product. The large number of software projects not meeting their expectation in terms of functionality, cost, delivery schedule and effective project management appears to be lacking. In this paper, we present a new software fusion process model, which depicts the essential phases of a software project from initiate stage until the product is retired. Fusion is component based software process model, where each component implements a problem solving model. This approach reduces the risk associated with cost and time, as these risks will be limited to a component only and ensure the overall quality of software system by considering the changing requirements of customer, risk assessment, identification, evaluation and composition of relative concerns at each phase of development process.

A Control Theoretical Model of Web Service Value Development

This paper describes a control theoretical model of collaborative value development. This model is designed to assist managers in choosing parameters that are critical to the development process in service design and support their Business Model. This methodology uses control system modelling of web-based service value generation implemented in SIMULINK/MATLAB. An application based on public domain Wikipedia data is used to validate and develop the model. A control theoretic model applied to the creation of Wikipedia articles shows very good agreement with Wikipedia published data for the time dependent growth in articles produced, and editors used, well within the variability of parametric data listed publically justifying the principle equations used in the model. This development and fine tuning of the model has been limited by the publically available data. To obtain a more accurate model in this area would need the co-operation of web service organisations to reveal confidential data. This modelling procedure can produce a decision support process for service design and could, with modification be applied much more widely to other choices in service design/implementation, even allowing for user contribution to be evaluated. This work shows how subjective judgements on value and other intangibles need to be continually re-evaluated. Such methodology has not been applied elsewhere to value generation applications. It could be used to rank contributions from co-creators for reward sharing.

Modelling to Generate Alternatives Using Simulation-Driven Optimization: An Application to Waste Management Facility Expansion Planning

Public sector decision-making typically involves complex problems that are riddled with competing performance objecttives and possess design requirements which are difficult to capture at the time that supporting decision models are constructed. Environmental policy formulation can prove additionally complicated because the various system components often contain considerable stochastic uncertainty and frequently numerous stakeholders exist that hold completely incompatible perspectives. Consequently, there are invariably unmodelled performance design issues, not apparent at the time of the problem formulation, which can greatly impact the acceptability of any proposed solutions. While a mathematically optimal solution might provide the best solution to a modelled problem, normally this will not be the best solution to the underlying real problem. Therefore, in public environmental policy formulation, it is generally preferable to be able to create several quantifiably good alternatives that provide very different approaches and perspectives to the problem. This study shows how a computationally efficient simulation-driven optimization approach that com- bines evolutionary optimization with simulation can be used to generate multiple policy alternatives that satisfy required system criteria and are maximally different in decision space. The efficacy of this modelling-to-generate-alternatives method is specifically demonstrated on a municipal solid waste management facility expansion case.

A Reference Model for the Analysis and Comparison of MDE Approaches for Web-Application Development

The emerging Model-Driven Engineering (MDE) paradigm advocates the use of models as first-class citizens in the software development process, while artifacts such as documentation and source-code can be quickly produced from those models by using automated transformations. Even though many MDE-oriented approaches, languages and tools have been developed in the recent past, there is no standard that concretely defines a specific sequence of steps to obtain a functional software system from a model. Thus, the existing approaches present numerous differences among themselves, because each one handles the problems inherent to software development in its own way. This paper presents and discusses a reference model for the comparative study of current MDE approaches in the scope of web-application development. This reference model focuses on relevant aspects such as modeling language scope (domain, business-logic, user-interface), usage of patterns, separation of concerns, model transformations, tool support, and deployment details like web-platform independence and traditional programming required. The ultimate goal of this paper is to determine the aspects that will be of greater importance in future web-oriented MDE languages.

A Data-Driven Simulation Model for China Haze Monitor and Governance

Recently, the China haze becomes more and more serious, but it is very difficult to model and control it. Here, a data-driven model is introduced for the simulation and monitoring of China haze. First, a multi-dimensional evaluation system is built to evaluate the government performance of China haze. Second, a data-driven model is employed to reveal the operation mechanism of China’s haze and is described as a multi input and multi output system. Third, a prototype system is set up to verify the proposed scheme, and the result provides us with a graphical tool to monitor different haze control strategies.

Analyses of the Temporal Development and Yield Losses due to Sheath Blight of Rice (Rhizoctonia solani AG1.1a)

Sheath blight of rice, caused by Rhizoctonia solani AG 1. 1a, has become the most important disease and caused serious yield losses in some major rice-growing regions in China in recent years. In the present study, field plot experiment was conducted to examine the relationships between disease intensity and inoculum density （ID）, the seasonal disease epidemic dynamics, and yield reductions due to disease damages. Results from the experiment demonstrated that the areas under progress curves of disease severity and those of percent rice tillers diseased were positively and closely related to the relative initial ID of the pathogen. The inoculum density-disease （IDD） relationships were simulated and the impractical linear models were obtained. Both logistic and Gompertz functions could be used to simulate the disease progress dynamics in time, but the progress curves of the disease severity were modeled better by the Gompertz than by logistic function. However, the Richards function was found to be the best in simulating the disease progress curves when a most appropriate value was chosen for the shape parameter m by using the computer software Epitimulator. Sheath blight infection decreased rice yield very significantly and a yield reduction of 40% was recorded in rice crop with the highest inoculum density. Rice yield was linearly and negatively correlated with the disease severity and the percent tillers affected. The simulated models for all these relationships were computed through executing Epitimulator software and were presented in this paper.

A Process-Based Model for Simulating Phasic Developmentand Phenology in Rice

A simulation model for phasic and phenological development of rice was developed using the scale of physiological development time, based on the ecophysiological development processes. The interaction of daily thermal effectiveness, photoperiod effectiveness and intrinsic earliness(before heading), and basic filling duration factor(after heading)determined the daily physiological effectiveness, which accumulated to get physiological development time. The Beta and quadratic functions were used to describe daily thermal and photoperiod effectiveness, respectively. Five specific genetic parameters were added to adjust the genotypic differences in rice development so that all different varieties could reach the same physiological development time at a given development stage. The stages of seedling emergence, panicle initiation, heading, and maturity were validated using sowing dates under different ecological environments, with the RMSE of 1. 47, 5. 10, 4.58 and 3.37 days, respectively. The results showed that the model was not only explanatory and systematic but also accurate and applicable.

Developing a process-based and remote sensing driven crop yield model for maize(PRYM–Maize) and its validation over the Northeast China Plain

Spatial dynamics of crop yield provide useful information for improving the production. High sensitivity of crop growth models to uncertainties in input factors and parameters and relatively coarse parameterizations in conventional remote sensing(RS) approaches limited their applications over broad regions. In this study, a process-based and remote sensing driven crop yield model for maize(PRYM–Maize) was developed to estimate regional maize yield, and it was implemented using eight data-model coupling strategies(DMCSs) over the Northeast China Plain(NECP). Simulations under eight DMCSs were validated against the prefecture-level statistics(2010–2012) reported by National Bureau of Statistics of China, and inter-compared. The 3-year averaged result could give more robust estimate than the yearly simulation for maize yield over space. A 3-year averaged validation showed that prefecture-level estimates by PRYM–Maize under DMCS8, which coupled with the development stage(DVS)-based grain-filling algorithm and RS phenology information and leaf area index(LAI), had higher correlation(R, 0.61) and smaller root mean standard error(RMSE, 1.33 t ha^(–1)) with the statistics than did PRYM–Maize under other DMCSs. The result also demonstrated that DVS-based grain-filling algorithm worked better for maize yield than did the harvest index(HI)-based method, and both RS phenology information and LAI worked for improving regional maize yield estimate. These results demonstrate that the developed PRYM–Maize under DMCS8 gives reasonable estimates for maize yield and provides scientific basis facilitating the understanding the spatial variations of maize yield over the NECP.

Hybrid Enterprise Modelling: Integrating Modelling Mechanisms for Socio-Technical Systems Analysis and Design

Nowadays, Model Driven Development (MDD) is a powerful technique for modelling complex systems and also for aligning business and information technology (IT), giving designers the ability to execute business models as they are intended to be run and behaved in the business environment. The Object Management Group (OMG) adopted many business standards into the Model Driven Architecture (MDA) environment e.g. Semantics of Business Vocabulary and Business Rules (SBVR), the Business Motivation Model (BMM), Business Process Modelling and Notation (BPMN) and Organisational Structure Model (OSM). These can work together to model different aspects of the enterprise at the business level. However, these models lack reasoning and dynamic simulation: there is no significant way to simulate discrete and continuous time system behaviour or to build arguments for reasoning about the design options within the OMG specifications. In this paper we propose an approach to overcoming this problem, by integrating a set of modelling tools into one single platform, taking advantage of meta-modelling techniques to integrate new tools with the OMG specifications in a model driven environment. The prospective framework should be able to tackle advanced analysis and design problems by intertwining design, reasoning and simulation to achieve a higher level of design maturity through implementing the desired scenario.

Incorporating AOSD to Enhance Model Driven Architecture

Various software development approaches in the present scenario are best suited for a specific application. The software development strategies include both merits and demerits when talked in terms of generalization. The Model Driven Architecture (MDA) describes software development based on models on various levels of abstraction. The model driven software development process consists of sequence of model transformations between various models. This paper presents incorporation of the merits of Aspect Oriented Software Development (AOSD) like modularization, reusability and reduced complexity into Model Driven Architecture (MDA) software development strategy. The proposed Model Driven Software Development approach which combines the merits of MDA and AOSD meets the ever changing and challenging demand of the enterprise software development.

Machine learning inspired workflow to revise field development plan under uncertainty

We present an efficient and risk-informed closed-loop field development (CLFD) workflow for recurrently revising the field development plan (FDP) using the accrued information. To make the process practical, we integrated multiple concepts of machine learning, an intelligent selection process to discard the worst FDP options and a growing set of representative reservoir models. These concepts were combined and used with a cluster-based learning and evolution optimizer to efficiently explore the search space of decision variables. Unlike previous studies, we also added the execution time of the CLFD workflow and worked with more realistic timelines to confirm the utility of a CLFD workflow. To appreciate the importance of data assimilation and new well-logs in a CLFD workflow, we carried out researches at rigorous conditions without a reduction in uncertainty attributes. The proposed CLFD workflow was implemented on a benchmark analogous to a giant field with extensively time-consuming simulation models. The results underscore that an ensemble with as few as 100 scenarios was sufficient to gauge the geological uncertainty, despite working with a giant field with highly heterogeneous characteristics. It is demonstrated that the CLFD workflow can improve the efficiency by over 85% compared to the previously validated workflow. Finally, we present some acute insights and problems related to data assimilation for the practical application of a CLFD workflow.