Leila Samimi-Dehkordi; Abbas Horri
Abstract
In the last few years, we have witnessed a significant growth of "low-code development platforms" (LCDPs) in attracting the attention of both the market and the academia. LCDPs are visual development platforms that typically run on the cloud, reducing the need for manual coding. They are also used by ...
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In the last few years, we have witnessed a significant growth of "low-code development platforms" (LCDPs) in attracting the attention of both the market and the academia. LCDPs are visual development platforms that typically run on the cloud, reducing the need for manual coding. They are also used by non-professional developers with limited knowledge in programming to construct applications. In this paper, the characteristics of well-known LCDPs are first studied to evaluate the advantages of this approach. Given that the low-code platforms have many goals and features in common with the model-driven engineering (MDE) approaches, it is necessary to examine the position of these platforms in comparison with the MDE approaches and identify the strengths and weaknesses of both. One of the reasons for the popularity of the LCDP platforms is the use of cloud computing, which most model-driven engineering approaches have failed to achieve. Therefore, in this article, we review the solutions for using cloud computing in MDE to apply these approaches to develop low-code platforms and apply the approach on a modeling language for smart contracts.
Introduction
Software engineering is an engineering system that aims to educate, research, and apply methods to develop applications for increasing software productivity and quality and reducing the cost and production time (Kung, 2013). One of the software engineering methods that has received attention in recent years is using Low-Code Development Platforms (LCDP) (Alamin et.al, 2023). LCDPs use a graphical user interface to develop software instead of traditional programming. These types of platforms are suitable tools for organizational companies to reduce development costs and time to market (Tisi et al., 2020). Increasing the level of abstraction in order to reduce the cost of development is exactly the same goal that "Model-Driven Software Engineering" (MDSE) pursues. MDSE is an approach in software engineering where models are used not only as documentation but also for automatic code generation (Brambilla et al., 2017). The MDSE methodology has matured and its best practices can be used for the new field of LCDP (Verbruggen and Snoeck, 2023). At the same time, LCDP has been of great interest in the last few years, and migrating from Model-Driven Engineering to cloud spaces to create LCDPs can be applicable and appropriate (Ruscio et al., 2022).
Research Question(s)
What features can be considered for common LCDPs?
What is the position of LCDPs compared to MDSE?
What are the prerequisites for migrating modeling languages from MDSE to LCDP?
Literature Review
2.1. Theoretical foundations of research
Model-Driven Engineering and a Low-Code Development Platform have both been introduced with the goal of rapid product delivery with minimal programming (Ruscio et al., 2022). However, MDSE is more mature than LCDP (Verbruggen and Snoeck, 2023). Mendix, one of the pioneers in the LCDP field, has presented a LCDP manifesto including 9 principles, which are model-driven development, collaboration, agility, cloud computing, openness, multi-user development, experimentation, governance, and community (Kenneweg et al., 2021). To investigate the features of the LCDP platforms, six stages for developing an application has introduced, which are domain modeling, user interface definition, business logic specification, integration with external services, deployment, and maintenance (Sahay et al., 2020).
2.2. Related Work
2.2.1. Researches related to LCDP and MDSE
Cabot stated that the LCDP approach is the same as MDSE and it has been changed only with the aim of attracting the audience and better understanding the name of the approach (Cabot, 2020). Khorram et al. stated that LCDPs are based on MDSE, in which system design with visual modeling and automatic production of the final executable system has been introduced as a common feature of both approaches (Khorram et al., 2020). In the Locomote framework research, it is stated that developers can take advantage of MDSE principles, but as scalability is one of the serious problems in MDSE, this challenge is more evident in LCDP (Tisi et al., 2020). Alamin et al. stated that LCDP is inspired by MDSE, and development is done using abstract representations instead of focusing on algorithmic calculations (Alamin et al., 2021). Ruscio et al., have classified five research areas, in which the differences between MDSE and LCDP, including end users and application scope, are stated (Ruscio et al., 2022).
2.2.2. Well-known LCDPs
In Appsheet, a variety of tools and services, including data-driven applications, can be easily developed on top of the Google cloud database (Käss et al., 2023). In SwiftUI, it is possible to create a user interface for any Apple device by means of a declarative syntax, drag-and-drop support, and real-time preview (Nekras, 2022). Honeycode is a spreadsheet component and a set of templates for creating simple web-based applications (ElBatanony and Succi, 2021). PowerApps is a no-code platform for business users that starts with the data model and business processes and goes on to automatically generate responsive portable applications. (Gürcan and Taentzer, 2021). OutSystems is a low-code development platform that enables the development of desktop and mobile applications (Martins et al., 2020). Mendix is a low-code development platform where all features can be accessed via drag-and-drop functionality (Gürcan and Taentzer, 2021). KissFlow is a cloud-based workflow automation software platform that helps users build and modify automated enterprise applications (Hili and Oliveira, 2022). Appian is one of the oldest LCDPs that enables the creation of mobile and web applications through personalization tools, built-in team collaboration tools, task management, and social networking (Vincent et al., 2019).
Methodology
The present research method is practical in terms of purpose and descriptive survey in terms of nature. The purpose of this research is to investigate various approaches in the field of LCDPs and compare them with MDSE approaches. Based on this, three research questions were designed. The first question is to examine the characteristics of LCDPs. To answer the first question, two types of studies have been conducted to collect information about these platforms: (1) a review of articles from 2014 to 2023 and (2) a review of LCDP tools.
The second question is to examine the position of LCDPs compared to the MDSE approaches. The review of articles has been from 2014 onwards and the articles that have addressed both issues have been taken into consideration.
The main challenge for LCDPs is the commercial nature of these platforms, which makes a limited community of users able to use them. MDSE tools are often academic and free. Consequently, the third question examined the requirements for moving from MDSE to LCDP. To answer this question, by introducing a case, the requirements of migration have been studied.
Conclusion
In this paper, the emerging approach of LCDP has been introduced. First, the important features of LCDPs have been reviewed and seven different tools were compared based on the reviewed features. Also, due to the common goal with the MDSE field, a comparison between these two fields has been presented and the position of LCDPs has been determined. Based on the MDSE benefits, the migration of modeling languages from the model-driven approach to the low-code development platform has been studied, and an example of migration has been investigated. One of the important limitations of this research is the lack of sufficient resources in the modern LCDP field. Most of the common platforms are commercial and there are few free platforms currently. Consequently, we suggested using the experiences of the model-driven field in the development of these types of platforms. For future work, it is necessary to study the characteristics and complexity of applications built using LCDPs, with the aim of evaluating the performance status of these platforms and reasoning about criteria such as their scalability and efficiency.
Acknowledgments
This article is derived from the results of the research project implemented under the contract number 5497/141 from the funds of Shahrekord University Research and Technology Vice-Chancellor.
Keywords: Model-Driven Engineering, Low-Code Development Platform, Cloud Computing.
Maryam Sadat Mazaheri; Changiz Valmohammadi; Alireza Pourebrahimi; Mahnaz Rabeei
Abstract
IntroductionNowadays, cloud computing has attracted the attention of many organizations. So many of them tend to make their business more agile by using flexible cloud services. Currently, the number of cloud service providers is increasing. In this regard, choosing the most suitable cloud service provider ...
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IntroductionNowadays, cloud computing has attracted the attention of many organizations. So many of them tend to make their business more agile by using flexible cloud services. Currently, the number of cloud service providers is increasing. In this regard, choosing the most suitable cloud service provider based on the criteria according to the conditions of the service consumer will be considered one of the most important challenges. Relying on previous studies and using a meta-synthesis approach, this research comprehensively searches past researches and provides a comprehensive framework of factors affecting the choice of cloud service providers including 4 main categories and 10 sub-areas. Then, using the opinions of experts who were selected purposefully and using the snowball method, and using the Lawshe validation method, the framework is finalized.Research Question(s)This research aims to complete the results of previous studies and answer the following questions with a systematic review of the subject literature:-What are the components of the comprehensive framework for choosing cloud service providers?-What are the effective criteria to choose a cloud service provider?-What is the selected framework of effective factors? Literature ReviewMany researchers have looked at the problem of choosing the best CSP from different aspects and have tried to provide a solution in this field. In this regard, we can refer to "Tang and Liu" (2015) who proposed a model called "FAGI" which defines the choice of a trusted CSP through four dimensions: security functions, auditability, management capability, and Interactivity helps. "Kong et al." (2013) presented an optimization algorithm based on graph theory to facilitate CSP selection. Some researchers have also provided a framework for CSP selection, such as "Gash" (2015) who provides a framework called "SelCSP" with the combination of trustworthiness and competence to estimate the risk of interaction. "Brendvall and Vidyarthi" (2014) suggest that in order to choose the best cloud service provider, a customer must first identify the indicators related to the level of service quality related to him and then evaluate different providers. Some researchers have focused on using different techniques for selection. For example: "Supraya et al." (2016) use the MCDM method to rank based on infrastructure parameters (agility, financial, efficiency, security, and ease of use). They investigate the mechanisms of cloud service recommender systems and divide them into four main categories and their techniques in four features of scalability, accessibility, accuracy, and trustIn this research, it has been tried to use the models and variables of the subject literature in developing a comprehensive framework. The codes, concepts, and categories related to the choice of cloud service providers are extracted from previous studies, and a comprehensive framework of the factors influencing the choice of cloud service providers is presented using the meta-composite method. MethodologyIn this research, based on the "Sandusky and Barroso" meta-composite qualitative research method, which is more general, a systematic review of the research literature was conducted, and the codes in the research literature were extracted. Then the codes, categories, and finally the proposed model are formed. The seven-step method of "Sandusky and Barroso" consists of: formulation of the research question, systematic review of the subject literature, search and selection of suitable articles, extraction of article information, analysis and synthesis of qualitative findings, quality control, and presentation of findings. Lawshe validation method has been used to validate the research findings. ResultsIn the meta-synthesis method, all the factors extracted from previous studies are considered as codes and concepts are obtained from the collection of these codes. Using the opinion of experts and considering the concept of each of these codes, codes with similar concepts were placed next to each other and new concepts were formed. This procedure was repeated in converting the concepts into categories and the proposed framework was identified. This framework consists of 27 codes, 10 concepts, and 4 categories (Table 1).Table 1: Codes, concepts, and categories extracted from the sourcescategoryConceptCodeNo.TrustSecurityHardware Security1Network Security2Software Security3Confidentiality4Control5Guarantee and AssuranceAccessibility6Stability7Facing ThreatsTechnical Risk8Center for Security Measures9TechnologyEfficiencyService Delivery Efficiency10Interactivity11Hardware and Network InfrastructureConfiguration and Change12Capacity (Memory, CPU, Disk)13Functionality Flexibility14Usability15Accuracy16Service Response Time17Ease of use18ManagerialMaintenanceEducation and Awareness19Customer Communication Channels20StrategicLegal Issues21Data Analysis22Service Level Agreement23CommercialCustomer SatisfactionResponsiveness24Customer Feedback25CostSubscription Fee26Implementation Cost27The lack of a common framework for evaluating cloud service providers is compounded by the fact that no two providers are the same, so that this issue complicates the process of choosing the right provider for each organization. Figure 1 shows the proposed comprehensive framework including 4 categories and 10 concepts covering the issue of choosing cloud service providers. These factors are useful in determining the provider that best matches the personal and organizational needs of the service recipient. The main categories are: trust building, technology, management, and business, which will be explained in the following.Figure 1: Cloud service provider selection framework 5- ConclusionBy comprehensively examining the factors affecting the choice, this research introduces specific areas such as trust building, technology, management, and business as the main areas of cloud service provider selection and add to the previous areas. The category of building trust between the customer, and the cloud service provider is of particular importance. In this research, the concepts related to trust building are: security (including hardware security, network security, software security, confidentiality and control), (availability, stability and stability), and facing threats (technical risk). In 36% of the articles, the concept of trust is mentioned, but in each study, only a limited number of factors affecting this category are discussed. This research takes a comprehensive look at the category of technology, the concepts of productivity (including service delivery efficiency, interactivity), hardware and network infrastructure (including configuration and repair, capacity (memory, processor, disk)), and performance (including flexibility, usability, accuracy of operation, service response time, ease of use). Considering the variety of services on different cloud platforms, service recipients must ensure that the provision of services is managed easily and in the shortest possible time by the cloud provider. The commercial aspect of service delivery deals with the two concepts of customer satisfaction (including responsiveness, customer feedback) and service rates (including: subscription cost and implementation cost), which are of interest to many businesses. The results of this research will help the decision makers of using the cloud space (both organizational managers and cloud customers) in choosing the best cloud service provider to have a comprehensive view of the effective factors before choosing and plan according to their needs.
Fatemeh Saghafi; Mohammad Reza Taghizadeh Yazdi; Sedighe Rezaeian Fardoie; Mansoureh Hourali; Banafsheh Khani
Abstract
Given the importance of service delivery speed and material handling in the perishable food supply chain, the use of the IOT transformation technology can provide a competitive advantage for manufacturing firms. Recently, some food companies have started using IOT technology in their supply chains. Background ...
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Given the importance of service delivery speed and material handling in the perishable food supply chain, the use of the IOT transformation technology can provide a competitive advantage for manufacturing firms. Recently, some food companies have started using IOT technology in their supply chains. Background review showed that three categories of technological, organizational and environmental factors can affect supply chain performance. Therefore, the purpose of this study is to investigate these three factors on the process of the perishable food supply chain based on IOT. First, by reviewing supply chain processes, a 5-step process was selected as the comprehensive process. Then the dimensions of these factors became from the literature and the conceptual model of the research was drawn by combining the effect of these factors on the supply chain process. The information was obtained through the distribution of a 24-item questionnaire among 203 managers of food production units as a research community and was analyzed by correlation analysis and structural equation modeling. The analysis unit of the Department of Spicy Food is that it uses levels of IOT. The results showed that environmental factors as a whole and technological factors affect the sustainable food supply chain from 4 dimensions. But organizational factors were not confirmed in 3 hypotheses. This will be a warning for managers who are interested in their companies being successful.
Changiz Valmohammadi; Maryam Sadat Mazaheri
Abstract
Nowadays, with the development and growth of information and communication technologies, employees resist to adopt such technologies, leading to the failure of the implementation and operationalization of these kinds of new technologies. Given increased usage of cloud computing as a new paradigm of communication ...
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Nowadays, with the development and growth of information and communication technologies, employees resist to adopt such technologies, leading to the failure of the implementation and operationalization of these kinds of new technologies. Given increased usage of cloud computing as a new paradigm of communication in organizations, the analysis of information systems users’ behavior is essential in organizations. This study uses the Technology Acceptance Model (TAM) presented by Davis to clarify the factors influencing technology acceptance and the decision to use cloud computing technology among IRIB employees. To do so, a structured questionnaire was designed and distributed among 230 IRIB personnel in the field of information technology. The calculated reliability using Cronbach method was 0.84. Then the exploratory and confirmatory factor analysis were performed. Based on path analysis coefficient it is confirmed that the most important factor influencing the decision to use cloud computing is perceived usefulness' factor. The obtained result could be employed as a guidelines by managers of the surveyed organization towards more effective decision making.
