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Low-Code as Enabler of Digital Transformation in Manufacturing Industry


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Currently, enterprises have to make quick and resilient responses to changing market requirements. In light of this, low-code development platforms provide the technology mechanisms to facilitate and automate the development of software applications to support current enterprise needs and promote digital transformation. Based on a theory-building research methodology through the literature and other information sources review, the main contribution of this paper is the current characterisation of the emerging low-code domain following the foundations of the computer-aided software engineering field. A context analysis, focused on the current status of research related to the low-code development platforms, is performed. Moreover, benchmarking among the existing low-code development platforms addressed to manufacturing industry is analysed to identify the current lacking features. As an illustrative example of the emerging low-code paradigm and respond to the identified uncovered features, the virtual factory open operating system (vf-OS) platform is described as an open multi-sided low-code framework able to manage the overall network of a collaborative manufacturing and logistics environment that enables humans, applications, and Internet of Things (IoT) devices to seamlessly communicate and interoperate in the interconnected environment, promoting resilient digital transformation.
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Appl. Sci. 2020, 10, 12; doi:10.3390/app10010012
Low-Code as Enabler of Digital Transformation in
Manufacturing Industry
Raquel Sanchis
*, Óscar García-Perales
, Francisco Fraile
and Raul Poler
Escuela Politécnica Superior de Alcoy, Research Centre on Production Management and Engineering,
Universitat Politècnica de València, Calle Alarcón, 03801 Alcoy (Alicante), Spain;
Information Catalyst SL. Ptda Tosal de la Cometa, 1-F-1-D, BL 3501, 03710 Calpe (Alicante), Spain;
Research Centre on Production Management and Engineering, Universitat Politècnica de València, Camino
de Vera s/n, 46022 Valencia, Spain;
* Correspondence:
Received: 23 November 2019; Accepted: 15 December 2019; Published: 18 December 2019
Abstract: Currently, enterprises have to make quick and resilient responses to changing market
requirements. In light of this, low-code development platforms provide the technology
mechanisms to facilitate and automate the development of software applications to support current
enterprise needs and promote digital transformation. Based on a theory-building research
methodology through the literature and other information sources review, the main contribution of
this paper is the current characterisation of the emerging low-code domain following the
foundations of the computer-aided software engineering field. A context analysis, focused on the
current status of research related to the low-code development platforms, is performed. Moreover,
benchmarking among the existing low-code development platforms addressed to manufacturing
industry is analysed to identify the current lacking features. As an illustrative example of the
emerging low-code paradigm and respond to the identified uncovered features, the virtual factory
open operating system (vf-OS) platform is described as an open multi-sided low-code framework
able to manage the overall network of a collaborative manufacturing and logistics environment
that enables humans, applications, and Internet of Things (IoT) devices to seamlessly communicate
and interoperate in the interconnected environment, promoting resilient digital transformation.
Keywords: low-code; trend; vf-OS; digital; platform; apps
1. Introduction
Currently, enterprises have to face increasingly difficult problems due to the increasing
complexity of their internal operations and the number and intensity of the relationships between
the company and the entities of its supply network. Moreover, the changing market means
enterprises need a rapid and flexible response to fulfil the variable requirements of the environment.
For this reason, companies require the capacity to withstand the stresses of environmental loading.
This capacity has been defined as enterprise resilience. Sanchis and Poler [1] defines it as the capacity
to prevent and anticipate; to change enterprises’ nature and adapt to the changing environment; and
to respond to the dynamic requirements.
Additionally, it is also unquestionable that enterprises have to give a response to these varying
market requirements quickly. Therefore, rapidity is a very important factor in the current context.
In order to enhance the resilience capacity of enterprises to make rapid and efficient responses
to the market needs, efforts have been focused on development of software solutions for companies.
A vast amount of research efforts in the history of computer science have been focused on the same
objective: enabling the construction of software applications without recurring to traditional
Appl. Sci. 2020, 10, 12 2 of 19
hand-coding and programming [2]. This is the reason why the use of agile methodologies is rising in
the current context to support the digital transformation of companies. The results of the survey
performed by [3] concludes that digital transformation is a work in progress, as the survey evaluates
the enterprises’ progress with digital transformation on a six-point scale. Respondents awarded their
organisations a score of 3.74, meaning that digital transformation efforts are typically widespread,
but not yet strategic or continuous. In light of this, low-code development platforms are considered
as a trendy mechanism to facilitate the rapid development of software applications (apps) and also
its automation to support the current enterprise needs and facilitate resilient digital transformation.
The term “low-code” was firstly coined by Forrester Research in 2014 (Cambridge, MA, USA)
[4], which states that firms prefer to choose low-code alternatives for fast, continuous, and
test-and-learn delivery. Low-code development platforms are ecosystems with which apps can be
developed, minimizing hand-code definition manually, because it is already built and prefigured.
Low-code development platforms emphasize visual interfaces to enable people, without a
technological background, to create and deploy business apps with relative ease [5]. The main
objective of the low-code development platforms is to allow enterprises to develop apps without
complex engineering facilitating their configuration, and then achieving, rapidity and agility.
Moreover, these platforms also offer enterprises a more economical way to fulfil the market and/or
enterprises internal requirements. With the low-code development platforms, enterprises can create
programs or apps for mobile or desktop devices, multifunctional and with high
information-management capabilities.
Many experts [3,4,6] point out the successful future of these platforms, highlighting their main
Privacy. As the apps can be developed by users without a deep expertise in technical issues,
enterprises trust their staff and these development tasks are not usually outsourced to third
parties but performed internally which increases the confidentiality [3].
Rapidity. As the main part of the code is already developed, users only have to visually
configure the apps instead of hand-coding them or make the necessary adjustments to develop
the apps they need [3]. As the development time is reduced, the availability of the apps is very
fast. A survey performed by Forrester [6] showed that low-code development platforms
accelerated development by 5 to 10 times.
Cost reduction. Due to the reduction in the development cycle from a time viewpoint, the cost is
also reduced whether the app is developed by the company or by external developers [4].
Complexity reduction. As the apps are not built from scratch, the apps development is
simplified and this fact enables to focus more on customizing the software to fulfil users’
Easy maintenance. The maintenance phase of software is vital to be able to quickly change what
already has been developed to guarantee a permanent alignment between the service offered by
the app and the business requirements. In light of this, as the essentials of the low-code
development platforms are to offer little code, there is little code to maintain [3].
Involvement of business profiles. These platforms provide simple and intuitive interfaces as a
development environment for the deployment of apps. In this context, no technological
knowledge is required, and the final users of these apps become the developers of such apps as
they are the ones who have a deep knowledge about the business needs [5]. According to [3]
44% of the low-code development platform users are business users in collaboration with IT.
Minimisation of unstable or inconsistent requirements. In the current software development
process, potential conflicts might arise among requirements and the impacts on the app design
of requirements’ changes. However, following the idea of the previous benefit, the use of
low-code means that developers quickly build minimum viable products to validate ideas and
customer requirements before wasting resources on features and functionalities that customers
may not value [6].
Based on the ‘The State of Application Development’ report [3] that shows the results obtained
through a survey answered by more than 3300 IT professionals across different continents, the main
Appl. Sci. 2020, 10, 12 3 of 19
reasons for using low-code development platforms are detailed in Figure 1. Of the respondents, 66%
chose accelerate digital transformation and increase responsiveness to the business as the main
motives why they use or will use low-code development platforms; 45% of the surveyed
professionals pointed to the reduction of dependency on hard-to-hire technical skills.
Figure 1. Main reasons for using low-code development platforms.
Richardson and Rymer [6] state that low-code development platforms bring several benefits,
but some risks have also to be taken into consideration. Based on the previous advantages,
low-code development platforms provide useful solutions in automating and speeding application
delivery, and high vendor growth rates. However, Richardson and Rymer [6] also highlight the risk
of dozens of small vendors selling outside of tech management, and customers with little consensus
about how low-code development platforms fit into their broader portfolios. Tisi et al. [2] also
highlight three main limitations that hamper the use of the low-code development platforms:
Scalability: the authors point out that low-code development platforms are mainly addressed
for the development of small apps but their application in large-scale projects and
mission-critical enterprise applications is not covered currently.
Fragmentation: different low-code development paradigms can be defined depending on each
vendor and their specific programming model.
Software-only systems: while enterprise developers have little expertise of programming, they
are often experts in some other engineering areas. These experts expect to be able to use their
knowledge in the application, at the right level of abstraction and using familiar formalisms.
Along the same lines, the survey conducted by [3] shows that the main reasons why
organisations are not using a low-code platform, or are not thinking to use one are the lack of
knowledge closely followed by concerns about lock-in, flexibility, scalability, and security (Figure
Based on this, the objective of this paper is to depict the status of the existing automation
software development tools focusing on the characterisation of low-code development platforms
following the foundations of the computer-aided software engineering field. This research also
pursues the identification of the potential low-code challenges for further research.
In light of this, the paper is addressed to the depiction of existing knowledge on low-code to
describe the current context of the research focused on this topic and identify uncovered challenges
and promising directions to provide foresight into the future of low-code research. As such, this
study builds upon two research questions:
Accelerate digital
Increase responsiveness
to the business
Reduce dependency on
hard-to-hire technical
Escape legacy debt
Protect against
technology churn
Enable citizen
developers to improve
internal processes
Appl. Sci. 2020, 10, 12 4 of 19
Figure 2. Main reasons for not using or considering low-code development platforms.
RQ1. What is the status about existing automation software development tools?
RQ2. What are the potential challenges in the context of automation software development
tools for further research?
The paper is structured as follows. Section 2 offers an overview of the context analysis,
describing the concept of computer-aided software engineering as a predecessor attempt to facilitate
the automation of software development and then focusing on the current status of research related
to the low-code development platforms. Section 3 performs a comparative analysis among the
existing low-code development platforms targeting to manufacturing industry and describes the
vf-OS (virtual factory open operating system) platform from a broad-spectrum and low-code
viewpoints. Finally, in Section 4 the main conclusions, limitations and further research lines and
trends are detailed.
2. Context Analysis
Software and apps development is increasingly necessary to deal with the great amount of
information and data (big data) that companies have to manage, which is also becoming a more
complex process. In order to facilitate the software and apps development, companies specialised in
software development are demanding a higher level of automation in their software development
work. Moreover, currently different technologies have become more accessible for non-professional
users [7]. In consequence, there is an increasingly need for more efficient methods and tools for
automatically developing and maintaining computer systems [8]. To deal with these needs, in the
late 1980s the concept of computer-aided software engineering (CASE) emerged.
CASE technology encompasses a collection of automated tools and methods that assist software
engineering in the phases of the software development life cycle [9]. Lundell and Lings [10] define
CASE technology as an interoperable, computerised tool set designed to support stakeholder tasks
and processes over the full information systems development lifecycle. CASE-tools are often based
on the object-oriented approach to visual modelling of the unified modeling language (UML),
content management systems and business process management systems [7].
Fuggetta [11] classifies CASE products in the production process technology into three
Tools considered as software components supporting a specific task in the software-production
process. Such tool are in turn also classified as: editing tools (textual and graphical editors),
Lack of knowledge
about low-code
Concern about “lock-
in” with a no-
Don't believe we
could build the types
of app we need
Concern about
scalability of the
apps created
Concern about
security of the apps
Appl. Sci. 2020, 10, 12 5 of 19
programming tools (coding and debugging tools, code generators and code restructurers);
verification and validation tools (Static and dynamic analysers, comparators, symbolic
executors, emulators/simulators, correctness proof assistants, test-case generators and
test-management tools); configuration-management tools (version management, item
identification, configuration building, change control, library management); metrics and
measurement tools (code analysers, execution monitor’s timing analysers); project management
(cost-estimation tools, project-planning tools, conference desks, e-mail, bulletin boards, project
agendas, project note books), miscellaneous tools (hypertext systems and spreadsheets).
Workbenches that integrate in a single application, several tools supporting specific
software-process activities. Among them, the author highlights business planning and
modelling; analysis and design; user-interface development; programming; verification and
validation; maintenance and reverse engineering; configuration management and project
Environments defined as a collection of tools and workbenches that support the software
process. The environments involve: toolkits; language-centred; integrated; fourth generation
and process-centred.
Little recent evidence of the use of CASE technology to develop tools is found in the literature
(through the search of a set of keywords related to CASE in the Web of Science database). Some of
the latest works (from 2017 to 2019) related to the development of CASE-tools are: Vileiniskis et al.,
[12] perform the conceptual design and implementation of a practical lightweight approach to
model traceability in a CASE tool. Madoš et al. [13] who develop a CASE-tool, that supports
programming the experimental multi-core tile-based system-on-a-chip. The proposed tool allows
the creation of the program code in graphical form using data flow graph or in text representation
using assembly language or machine code. Automatic transformations between those
representations are supported. Al-Ashwal et al. [8] who develop a prototype of a CASE-tool for
Java logical errors detecting using static and dynamic testing techniques. Their research utilizes the
Junit and PMD (programming mistake detector) tools to detect the logical errors and analyse the
potential causes of these errors based on Java common logical errors lists. Tarasiev et al. [7] who
develop a prototype of CASE-tool to create automation systems based on web applications using
code generation. Hadj Sassi et al. [14] propose a CASE-tool that supports the design of business
intelligence for Internet of Things (IoT) architecture based on knowledge.
However, the adoption of CASE technology has been poor [10]. Troy and McQueen [15]
developed a methodology for designing domain-specific CASE tools supporting model-based
analysis and automatic code generation. Nevertheless, the authors, after producing a prototype
methodology companion designed to assist the task of developing control software for
programmable logic controllers in batch process manufacturing, point out that the mode of code
generation limits the feasibility of functional description maintenance and automatic code
generation. It is determined by [10] that one of the main reasons for the poor adoption of CASE
technologies may be that expectations of CASE are unrealistic. Another reason highlighted by [10]
may be that real user requirements are not being adequately met by CASE products. Huff [16]
mentions that CASE tools are quite expensive and related training costs may exceed the original
price of the tool. Orlikowski [17] underlines that the benefits of CASE do not accrue homogeneously
to all interested groups affected, leading to opposition by some groups. Iivari [18] in his article:
‘Why are CASE tools not used?’ declares that the actual use of CASE technology was much less than
one would expect. Some of his conclusions point at the fact that the productivity and quality of
software development through CASE tools is overrated. Moreover, complexity is also found as a
significant, negatively related, predictor of CASE effectiveness. Currently, all these findings are
corroborated by some experts who state that CASE systems still have a number of shortcomings and
cannot always be applied.
We do not know whether these limitations have motivated the emergence of low-code
technology in the current context, however, what is unquestionable is that the low-code paradigm
has burst strongly into the automation of software development. Waszkowski [5] highlights that
Appl. Sci. 2020, 10, 12 6 of 19
there is an important potential for the development of low-code solutions. He justified this by the
lack of software and apps developers and the growing requirements as to the scope and rate of
changes introduced in IT systems. Hand-coding is time-consuming and labour-intensive. Therefore,
in order to overcome all these barriers, this paper analyses the current research context related to
the low-code paradigm as with this technology, programming is not necessary to build applications
To analyse the context of the low-code development platforms, and based on a theory-building
research methodology a systematic literature review has been performed through two databases
(Scopus and Web of Science), covering all the range of years and domain categories. As the results
were very scarce, then the search on Google Academic was added for the context analysis. The first
approximation is focused on the definition of sets of general keywords to quantify the number of
publications related to low-code solutions. Table 1 shows a summary of the results obtained.
Table 1. Number of publications according to the diverse searches performed in the literature
“Low-Code” And “Application” And “Platform” And “App”
Scopus 184 37 11 1
Web of Science 208 10 4 1
Google Academic 5290 3450 1410 548
The first set of keywords: “low-code” is then extended with “applications”, “platform” and
“app”. These sets of keywords provide a smaller number of results. In Scopus, only 11 publications
are identified to be related to “low-code” and “platform”. In the Web of Science, this number
decreases to only 4 publications. One important aspect to be taken into account is the publication
year. Based on the 11 Scopus publications, 4 were published in 2018 and 4 more in 2019. The other 3
are from 2008, 2009 and 2012, however they are not related to the low-code scope of the present
research. In light of this, it is evinced that there are very few publications related to low-code aspects
and they are from the last two years, demonstrating its emerging trend.
2.1. Scientific Literature Review
One of the results found in the literature is a summary-report of the Forum session at the 2018
Enterprise Engineering Working Conference (EEWC 2018) [19]. In this report, it is highlighted the
use of low-code development platforms to further increase the speed and robustness of the digital
transformation by a gradual expansion of the meta-model of the enterprise design approach,
continuously applied on real-life cases.
Zolotas et al. [20] presents RESTsec, a low-code platform based on representational state
transfer (REST) that supports rapid security requirements modelling for enterprise services, abiding
by the state of the art attribute-based access control (ABAC) authorisation scheme. According to the
authors, RESTsec enables developers to embed the desired access control policy and generate the
service, the security infrastructure, and the code in a rapid and automated way. Another of the
results related to low-code aspects is focused on the domain-specific languages (DSLs) used in the
development environment of OutSystems Platform (Boston, MA, USA) [21]. In this case, authors
study the problematic of the DSLs for process modelling (business process technology, BPT), as it
has a low adoption rate and is perceived as having usability problems hampering its adoption. For
this reason, they develop and test a new version of BPT to improve developers’ experience.
Another result is focused on the development of an integrated software platform (INTELLIT),
(Institute of History and Literary Theory “G. Călinescu” of the Romanian Academy, “Lucian Blaga”
University of Sibiu, National Institute for Research and Development in Informatics and Polytechnic
University of Bucharest, Romania, 2018) as a support for the Virtual Library of Romanian Literature
to contribute to preserving and capitalizing on the Romanian literary heritage. This publication
highlights the importance of the low-code paradigm for choosing the technologies and models used
Appl. Sci. 2020, 10, 12 7 of 19
in the development of the INTELLIT Platform [22]. However, the focus of its research is far from the
main objective of the present study.
Tisi et al. [2] presents the project: Lowcomote, that is an innovative training network (ITN)
aiming to train professionals in the design, development and operation of low-code development
platforms. The motivation of this project is to overcome the limitations that low-code platform
presents by being scalable (able to develop largescale applications); open (based on interoperable
programming models and standards); and heterogeneous (supporting with models coming from
diverse engineering areas).
Pantelimon et al. [23] describe NETIoT, an IoT platform built following the hpaPaaS principles,
centred around the applications being supported by a set of IoT devices owned by a user. This study
is focused on how to efficiently bring measurements from heterogeneous IoT hardware devices to
the NETIoT platform in a low-code manner, with zero intervention on hardware and minimum
configuration effort platform-wise. Along the same lines, Waszkowski [5] describes the use of the
Aure BPM low-code platform for automating business processes in manufacturing.
Wu et al.’s [24] study is focused on the technical question and answer (Q&A) platforms, such as
Stack Overflow. This platform is an instrument for users to ask and answer questions related to a
wide variety of programming topics. Moreover, it offers hundreds of thousands of lines of source
code that can be used by developers. One of the objectives of this study is to identify barriers that
hinder code reuse. After an exploratory study and a survey, the authors found 3 main barriers to
reuse code from Stack Overflow: (i) too much code modification required to fit in their projects, (ii)
incomprehensive code, and (iii) low-code quality. This third barrier requires the need for
next-generation Q&A platforms to improve or verify the code quality of source code snippets and
highlights the current importance of the low-code.
2.2. Other Information Sources
As the number of results obtained in the search performed in scientific databases is scarce, due
to the novelty of this domain, alternative information sources are used to analyse the current status
of the low-code paradigm. For this purpose, Google Academic is the information source selected. As
it is shown in Table 1, the number of results found is higher than in the other two scientific
When the search is more narrowed down, adding “application, “platform” and “app” to the set
of originals keywords (“low-code”), the number of results decreases considerably. Moreover, it is
worth mentioning that more than 40% of the results identified in the search do not correspond to the
purpose of the present research, as they are focused on the low code-rates when they are studying
the error corrections codes. This concept is used for controlling errors in data over unreliable or
noisy communication channels. To avoid problems, redundant bits are added to support the
decodification and find out the true message encoded in the communication. The code-rate is
defined as the ratio between the number of information bits and the total number of bits in a specific
communication channel. A low code-rate close to zero means a strong code that uses many
redundant bits to achieve a good performance, while a large code-rate close to 1 implies a weak code
Taking this into account, it seems that low-code development platforms that provide the
necessary functionalities to users to configure operational apps are a novel topic that currently is
emerging. Narrowing down the results of the search “low-code” from 2014, that is the year when
“low-code” was firstly coined to 2019; and deleting those related to “low-code rates”, the total
results are only 33% of the original results, what evinced that not too many references study this
With regard to the type of documents, google academic provides as results, scientific
publications but also other documents such as reports developed by prestigious global enterprise
software companies and market research companies such as OutSystems [27] and Forrester [28].
These companies perform technological vigilance and report the results of such observance.
Moreover, they perform surveys addressed to application developers, managers, or information
Appl. Sci. 2020, 10, 12 8 of 19
technology (IT) leaders to analyse their challenges with digital transformation, application
development, delivery speed, among others.
The market of the low-code development platforms (based on 42 suppliers of these services)
generated $1.7 billion in revenue during 2015 [6]. Moreover, in a survey addressed to developers,
23% reported that they used low-code development platforms in 2018, and another 22% planned to
do so within a year [29]. Fryling [30] points out that the average cost of a software development
project ranges from $434,000 for projects implemented in small and medium-sized enterprise (SMEs)
to $2,322,000 for larger projects [31]. Besides these figures, authors state that 31.1% of projects are not
finished and they are finally cancelled, 52.7% of the projects exceed the budget in an 89% more, and
only 16.2% are completed according to the planned schedule and budget [31].
Based on these results it seems that the low-code topic, more specifically its application
through platforms, is a reality and will be a trend in coming years. However, when this topic is
searched in scientific sources, not too many evidences are found, what points out the fact that this
topic seems to be under-researched and only few low-code development platforms have been
developed and launched. This is also more critical when the target markets are the industrial sector
where the apps should also take into account Industry 4.0 aspects such as for example data coming
IoT devices.
3. Low-Code Development Platforms
Whilst a visual programming language (VPL) is any programming language allowing software
developers to craft programs and applications by graphically manipulating elements rather than by
hand-coding [32,33], a low-code development platform is a software environment that allows these
software developers to create application software through user interfaces (UIs) and configuration
instead of traditional computer programming. In other words, VPL allows programming with visual
expressions, or spatial arrangements of text and graphic symbols, while low-code development
platforms may focus on design and development of a particular kind of application: such as
databases, business processes, or user interfaces such as web applications.
For example, many VPLs (known as dataflow or diagrammatic programming) [34] are based on
the idea of “boxes and arrows”, where boxes or other screen objects are treated as entities, connected
by arrows, lines or arcs which represent relations, while low-code development platforms may
produce entirely operational applications, or require additional coding for specific situations.
These platforms are usually accessible through free or low-cost self-service offerings. They are
based on free and freemium models. Most low-code development platforms are available as public
cloud services [6]. The low-cost platforms normally do not require training for developers to get
started. The exploitation business model for such platforms is usually based on fees for users and
deployed apps. As mentioned, one of the most advantageous aspects of the low-code development
platforms is the speed with which developers and their business partners test a business idea
through an app, gain feedback, and iterate toward a finished product [6]. Low-code development
platforms can also lower the initial cost of setup, training, and deployment [4].
3.1. General Overview of Virtual Factory Open Operating System (vf-OS) Platform
vf-OS is a project funded by the H2020 Framework Programme of the European Commission
under Grant Agreement 723710 and conducted in the period October 2016 until August 2019.
Further information can be found at [35].
As mentioned, traditional factories will increasingly be transformed into digital manufacturing
environments but currently the full potential for ICT in manufacturing is far from being fully
exploited [36]. This is the motivation for the vf-OS project.
In order to facilitate the app-building process and not to be dependent on off-the-shelf and
third-party software, low-code development platforms are emerging quickly to design, build,
customize, and deploy business apps minimizing hand coding. Moreover, as indicated by [6] the
next wave of innovation is apps that include IoT devices. The next source of organic growth for
low-code platforms will be applications that incorporate sensors and actuators. In this sense, vf-OS is
Appl. Sci. 2020, 10, 12 9 of 19
an open multi-sided framework able to manage the overall network of a collaborative
manufacturing and logistics environment that enables humans, applications, and devices (IoT) to
seamlessly communicate and interoperate in the interconnected environment, giving response to the
requirement identified as a trend in 2016 by [6].
vf-OS can be deployed in-cloud and on premises. vf-OS provides different services to connected
factories of the future to integrate better manufacturing and logistics processes, allowing
collaborative manufacturing based on cross-organisational manufacturing support, and allowing
mobile manufacturing [37]. Table 2 shows the functionalities that vf-OS offers [38].
Table 2. Description of virtual factory open operating system (vf-OS) functionalities.
Virtual Factory Input/Output Interface (vf-IO)
It is a set of modules that virtualise factory’s real assets and connect them to their images in vf-OS. vf-IO
implements plug-and-play mechanisms and device drivers for seamless/open access and smart virtualisation of
the factory resources; it is composed by devices drivers, application programming interface (API) connectors,
security, and data access. Thus, the vf-IO is composed of the modules that enable connectivity to assets like
legacy enterprise resource planning (ERPs) or customer relationship management (CRMs), cyber-physical
systems (CPSs), smart objects or wireless sensor networks.
Virtual Factory System Kernel (vf-SK)
It is the core of the operating system, responsible for providing key system resources and a set of specific
services, which is open and accessible to other components of the system.
Virtual Factory Devices Drivers and Open Application Programming Interfaces (APIs).
Open APIs, interconnection modules and drivers serve as interoperability mechanisms between the
factory and vf-OS applications. The integration between both is seamless and secure. It provides interfaces to
physical assets (e.g., sensors) and virtual assets (e.g., ERP systems and data) and eases their use in vf-OS.
Virtual Factory Middleware (vf-MW)
It consists of system services and a data bus, which provide a set of modules to integrate data from
arbitrary sources, including, but not limited to CPS, smart objects, radio frequency identification (RFID)
devices, and wireless sensor networks. Moreover, the use of cloud-based data storage avoids vendor lock-in
issues and minimises the risk of system failures. Accessibility of data is facilitated through connectors and
Virtual Factory Open Applications Development Kit (vf-OAK)
A complete and fully open development kit addressed to the software producing community. The aim is
addressed to guarantee the growth of specific applications running in vf-OS across all industrial sectors and
scenarios. It is composed of a software development kit (SDK) to develop applications, a system dashboard, the
OAK Frontend Environment, the OAK Development Studio and a developer engagement hub to engage
developers. The SDK implements all the necessary APIs needed to develop vApps. The OAK System
Dashboard represents the core software services for allowing system monitoring and configuration; the OAK
Frontend Environment provides a framework that facilitates a general ‘look, feel, and composition’ to vApps
and assists rapid development, by providing a compilation of UI elements including business logic via the OAK
Studio; the vf-OS Development Studio is a desktop development environment that facilitates software
developers to compose their applications for running within vf-OS. Additionally, the Developer Engagement
Hub is a collaboration platform for developers to support each other.
vf-OS Applications (vApps)
Manufacturing smart applications enables and optimise communication and collaboration among supply
networks across all manufacturing sectors and in all the stages of manufacturing and logistic processes:
demand forecast, planning, supply, manufacturing, distribution, storage, replacement, and recycling.
vf-OS Store (vf-Store)
Virtual Factory Manufacturing Application Store offers fundamental services of a modern e-Commerce
platform for consumer and developers. On one hand, vf-Store enables software developers to offer assets
(demanded or initiative), and on the other hand, users can search for, obtain and rate existing vApps.
Furthermore, the vf-Store acts as a mediator between developers and users. Therefore, the vf-Store is the central
point for developers to get in contact with users. In addition to view/set ratings, review, and provide technical
information about the asset’s behaviour, the vf-Store supports users to get in contact with developers to offer
Appl. Sci. 2020, 10, 12 10 of 19
ideas for new assets.
Virtual Factory Platform (vf-P)
This is a holistic service platform, which is the foundation for all services and end user applications that
vf-OS provides. vf-P encapsulates and acts as the interface and runtime environment between the components,
connectors, OAK functions, marketplace, the service framework (supporting the running of intrinsic services
and vApps) and the end user applications/developers. The vf-P can run locally and in cloud environments.
The Virtual Factory Platform is a multi-sided market platform that can create benefits for each
of the customer segments presented in Figure 3 and described in Table 3.
Figure 3. vf-OS big picture.
Table 3. Customer segments that can profit from vf-OS.
Software Developers
These users can access a new promising and high-growth potential market for the development
of vApps. These are developed using the vf-OAK to quickly build applications running over the
vf-SK and using the vf-IO and the vf-MW. The software developers can be independent or work
within IT departments of particular manufacturers.
Manufacturing and Logistics Users
This group of users can search vApps in the vf-Store. The search can be filtered based on
features, cost, or ratings amongst others. These users can request specific requirements to the vf-OS
software development community when demanding custom vApps.
Manufacturing and Logistics Solution Provider
This segment exposes their ICT interfaces and manufacturing connections to the vApps. They
are also able to contribute to the development of vApps that may be added and commercialised in
Appl. Sci. 2020, 10, 12 11 of 19
the v
External Service Providers
These users provide services (hosting, storage, connected cloud services, etc.) including those
based on developed solutions.
All in all, vf-OS proposes an open platform, linked by strong network externalities and
exploiting advanced information and communication technology (ICT) (i.e., cyber-physical systems
(CPS), IoT, cloud-models, machine to machine-M2M, security by design, etc.), fulfilling the actual
need on the market for open services for interoperability based on data exchange. vf-OS provides a
set of open services, rooted in the cloud, and instantiated via vf-P that move from the device-centric
to the user-centric paradigm. These are implemented through a multi-sided market exploitation
strategy and with clear value proposition to manufacturers, machine and device providers, logistic
operators, and end users. Moreover, vf-OS profits from existing technologies (e.g., FIWARE, Talend,
etc.) to quickly provide value to final users and developers.
For hardware functions, such as a factory’s input and output sensors, the operating system acts
as an intermediary between the application behaviour of the factory and the factory hardware itself.
This enables the factory functionalities and services to be virtualised or executed directly by the
hardware, allowing system calls to the operating system function to appropriately manage the
manufacturing requirements.
3.2. Analysis of the Current Low-Code Development Platforms
There are only some low-code development platforms addressed to different industrial sectors.
However, there is a lack of transversal platforms developed on open standards to create an
ecosystem for building and deploying, in an automated manner, working apps to complete a specific
task or solve a particular industrial problem. The following solutions have been identified as
low-code development platforms: (i) Siemens MindSphere, (ii) PTC ThingWorx, (iii) GE Predix, (iv)
IBM Cloud (formerly IBM BlueMix), (v) Microsoft Azure IOT Suite, and (vi) Software AG ADAMOS
[39]. Table 4 shows the description and main characteristics of each one, including vf-OS, that will be
described in the following sections.
Based on [39], analysis and comparison of the previously existing and commercial low-code
development platforms have been performed against the vf-OS platform that will be described in the
following section. Firstly, the main features of a low-code development platform have been
identified. Based on this, the second step has been focused on analysing and performing a
benchmarking among the different low-code development platforms using the following
nomenclature: supported, supported to some extent, and - not supported. Table 5 shows the
results of this analysis.
It is worth mentioning, as a limitation of this study, that this benchmarking has been performed
based only on the available information of references [35, 40-45]. Moreover, the comparison is only
against vf-OS and Table 4 main goal is not addressed to directly compare the other products
Table 4. Description of the existing and low-code development platforms.
Low-code development platforms and its description
Siemens MindSphere (Version 3.0, Siemens, Berlin, Germany, 2019) [40]
Appl. Sci. 2020, 10, 12 12 of 19
MindSphere is Siemens’ cloud-based, open Internet of Things (IoT) operating system that
connects real things to the digital world and enables powerful industry applications and digital
services to drive business success. MindSphere’s open PaaS enables a rich partner ecosystem to
develop and deliver new applications. MindSphere allows users to:
Connect real things to the digital world, by including secure connectivity, an easy to set up
environment, and using open standards for connectivity.
Use Cloud-based services, PaaS, with support, open application development, and data/
metadata characterisation.
Use built-in apps and real use-cases to shorten the deployment time, e.g., fleet management,
building performance, or control loop performance analytics.
PTC ThingWorx (Version 8.5, PTC, Boston, MA, USA, 2019) [41]
ThingWorx provides the ability to source, contextualise and synthesise data while orchestrating
processes and delivering powerful web, mobile and AR experiences. As claimed in their product
page, ThingWorx is the fastest way to deliver industrial innovation through:
Leverage connected and enterprise system data to improve the performance of services and
customer experience, support and usability.
Optimise business processes, combining real-time data with existing enterprise systems to
increase efficiency.
Drive new revenue streams to unlock new business models and opportunities.
Differentiate product and service offerings to increase the pace of innovation.
GE Predix (GE, Boston, MA, USA, 2019) [42]
Predix combines sophisticated asset modelling, big data processing, analytics, and applications
to provide the IT foundation for industrial operations as follows:
Edge-to-cloud platform to deploy processing and analytics power to control edge assets in real
time or analyse big data in the cloud.
Digital twin to understand, predict, and optimise asset performance.
Analytics and machine learning to use the industrial analytics library to create and deploy
machine learning models that detect anomalies and predict maintenance.
Applications catalogue for building custom apps and end-to-end solutions.
Secure and resilient by design, includes edge-to-cloud data protection, security standards
support, full tenant segregation and access controls.
Comprehensive developer environment with all the right services, tools, techniques, and
supporting community to rapidly develop and deploy Industrial Internet of Things (IIoT) apps.
IBM Cloud (formerly IBM BlueMix) (IBM, Armonk, NY, USA, 2019) [43]
IBM Cloud (Bluemix) is a cloud PaaS that supports several programming languages and
services as well as integrated DevOps to build, run, deploy and manage applications on the cloud.
Bluemix comes with a catalogue, where own and third-party applications have been uploaded for
their deployment with the following features:
IT Infrastructure, either a dedicated server or a virtual server, for load balancing, process
deployment, shared storage and cloud infrastructure.
Means for developing mobile apps and extracting all the knowledge from the data.
Connection to different sources of data including IoT, unstructured data (through Watson) and
integration of third-party sources through the application programming interface (API)
Connect Secure Gateway.
A secure environment through hardware security module and leveraging Intel trusted
execution technology. All applications are SSL-Certified
Technologies such as blockchain for developing the rules of the message hub, or containers in
Kubernetes clusters for deploying secure and highly available apps.
Appl. Sci. 2020, 10, 12 13 of 19
Microsoft Azure IoT Suite (Microsoft, Redmond, WA USA, 2019) [44]
Azure IoT Suite is a set of preconfigured solutions that facilitates a quick start and can be
customisable to meet specific requirements from the customer. It is an open source implementation
of a common IoT solution patterns that can be deployed to Azure using the subscription means of
the customer. Each preconfigured solution combines custom code and Azure services to implement
a specific IoT scenario or scenarios. It features:
Scenarios covered: data visualisation, rules and alarm configuration, device management jobs
scheduling, physical and/or virtual devices provision, and troubleshooting.
Solutions available: remote monitoring, predictive maintenance, and connected factory.
Azure services available: IoT Hub, Event Hubs, Time series insights, container services, stream
analytics, web apps, cosmos DB, Azure storage..
Software AG ADAMOS ( DMG MORI, Dürr, Software AG and ZEISS as well as ASM PT,
Germany, 2019)[45]
The ADAMOS IIoT platform’s basic functionality is offered in the core areas of device
connectivity & management, real-time analytics and visualisation, workflow automation and
enterprise & cloud integration. ADAMOS is an open and manufacturer-neutral IIoT platform that
envisions a world of digitally networked manufacturing, and intelligent services around existing
products for machinery and plant engineering enterprises with the following features:
Platform infrastructure, being available on demand as a cloud service. It is
infrastructure-independent and can be operated flexibly according to requirements with any
infrastructure provider.
Machine learning: machine data can be evaluated in real time by machine learning models to
optimise decision-making in manufacturing (e.g., predictive maintenance).
Real-time analytics: use of predefined or individual analytics rules that are evaluated in real
time on the platform and are reusable in a wide range of applications.
Data storage: access to data within the platform (e.g., machine and sensor data).
Security: use of state-of-the-art security concepts and standards for physical safety, network,
access, and application security.
Device connectivity: flexible connectivity options for heterogeneous machine landscapes based
on certified gateways, IoT protocols and SDKs.
Device management: device life-cycle management for efficient device usage from on- to
off-boarding, such as firmware and software management, real-time alarm management,
connection and configuration management.
Dashboards: individually configurable and expandable real-time dashboards for monitoring
and analysing, for example, machine status and anomalies.
Integration: support of all IIoT integration scenarios to digitise the entire value chain, from
machine to cloud integration and through applications.
Table 5 provides the foundations to give response to the research question RQ1 related to the
status about existing automation software development tools. In this case, and focused on low-code
development platforms, it seems that vf-OS is well positioned as software platform within IIoT
domain. Of the 16 features considered, all the analysed low-code development platforms (except GE
Predix), are considered as operating systems and highlight security, as one of their main features.
Moreover all the platforms provide IIoT connectivity in terms of protocols with different
coverage degrees and OnPremise deployment and InCloud, with the exception of MS Azure IOT
Suite, unless a further Microsoft license is acquired. A marketplace; different analytics functionalities
and features covering a good spectrum of algorithms, methodologies, data ingestion, and ETL; and
messaging and Pub/Sub also belong to the common features offered by all the analysed platforms.
There are some features that are well covered by many of the software platforms analysed.
BlueMix and Software AG’s ADAMOS up-front provide application programming interfaces (APIs)
Appl. Sci. 2020, 10, 12 14 of 19
to access third party software. Within the rest of platforms, the APIs are offered through a
configuration facility. In addition, MindSphere, BlueMix and ADAMOS have a good coverage in
terms of development environment. However, this is not included, by default, in the MS Azure IOT
Suite. In the case of PTC, they have different tools for different purposes and for GE Predix the
development environment is under development.
Table 5. Benchmarking of the existing and low-code development platforms against vf-OS.
Feature Siemens
System -
Security by
APIs to
access third
1 1 1 -
InCloud -
Marketplace - 2
Environment 3 4 -
- - - -
Analytics - -
Ingestion and
Hub - - - -
Open Source - - -
and Pub/Sub
- - 5
1 via configuration, 2 through Digital Marketplace, 3 different tools for different purposes, 4
under development, 5 via vf-OS Assets.
With regard to the main differences between the analysed platforms and vf-OS, it is worth
mentioning that only two platforms: PTC ThingWorx and BlueMix have the business process
modelling feature. Moreover, the developers’ hub is only offered by the MS Azure IOT Suite and
vf-OS. Finally, from an open source viewpoint, only Siemens MindSphere and MS Azure IOT Suite
are considered (themselves) as open source platforms while Microsoft specifies that the IOT Suite is
open source but not the complete version of the Azure Platform.
Appl. Sci. 2020, 10, 12 15 of 19
3.3. vf-OS Platform from the Low-Code Viewpoint
The vf-OS Platform integrates different tools and components to facilitate the development of
new applications and foster development best practices, particularly code reusability,
interoperability, and security-by-design. As mentioned above, the vf-OS OAK provides developers
with a complete development kit to develop new applications. The vf-OS Integrated Development
Environment (IDE) integrates the different development tools that facilitate application
development. The micro-service architecture of vf-OS is a central part of the value proposal to
developers, since it allows application functionalities to be decomposed into several micro-services
and deliver specialised tools to develop specific application functionalities. There are development
tools to facilitate the development of frontend micro-services and backend micro-services.
The Frontend Environment is an intuitive what you see is what you get (WYSIWYG) tool to
develop application frontends. Based on the principles of web components, the frontend
environment allows to compose the application frontend by combining reusable UI components
(e.g., buttons, images, panels, tables, graphs) through either a palette and drag’n’drop canvas or a
plain text editor with XML tags representing UI components. From this basic representation, the
FrontEnd Environment generates a fully functional frontend service based on web standards and
technologies such as HTML (hypertext markup language), CSS (Cascading Style Sheets) and
JavaScript. Developers can visualize and test the generated code as they type, allowing to create the
application frontend and connect it to backend services in minutes.
At the backend, the Process Designer allows to build the business logic of the application by
drawing diagrams representing the orchestration of different vf-OS Platform micro-services. The
diagrams use a business process model notation (BPMN)-like workflow, where each artefact
represents a micro-service and each connection object a connection between different micro-services.
The graphical user interface allows developers to drag’n’drop available micro-services to the canvas
and access micro-service configuration by double-clicking the artefact, thus allowing to design
complex business logic workflows with few mouse clicks.
Developers have additional tools to develop new vf-OS assets that can be later integrated into
the business logic of the application, and even make them available to other developers through the
marketplace under different use terms (e.g., free or licensed). In this sense, the Input/Output (IO)
toolkit is a software generator that facilitates the development of gateway micro-services to
interconnect the vf-OS Platform with legacy devices or software applications. The user prompts
guide the developer in the creation of a micro-service scaffold that implements standard interfaces to
interconnect to other vf-OS components. Developers can use available templates to integrate
well-known communication standards like the object linking and embedding for process control
unified architecture (OPC UA) or Open Data Protocol (OData) in a secure way, reusing already
tested libraries. The Data Analytics model generator facilitates the development of analytic services,
including machine learning services, providing development tools and user interfaces to train and
test models. Data analytics assets are packaged as simple objects that can loaded and executed in the
Data Analytics component. The data integration generator allows users to create complex data
extraction-transformation-load (ETL) processes using a graphical user interface to define data
integration workflows. Again, data integration assets are distributed as objects that can be loaded
and executed in the Data Harmonisation component. These generators are integrated into the vf-OS
Platform in such a way that allows developers to build, deploy, test, and validate new vf-OS assets
locally before they are eventually published to the marketplace. For this purpose, the vf-OS
platform implements a staging area to test new micro-services and means to deploy them locally.
Additionally, developers can publish their newly developed assets in the curated vf-OS
Marketplace, so that they can be used by other applications.
All in all, it seems that low-code development platforms are the future direction for time and
cost reduction in the software development context. However, and in order to give response to
research question RQ2, it is worth mentioning that aspects such as integration, interoperability,
communication, real-time data processing, homogenisation, ergonomics and security to mention
some, should be addressed properly to facilitate adoption of the low-code paradigm.
Appl. Sci. 2020, 10, 12 16 of 19
vf-OS has been tested in three different manufacturing domains: manufacturing and
logistics/automation, construction-industrialisation, and manufacturing assembly and collaboration.
In these domains, a total of 21 vApps (smart manufacturing applications) have been developed
involving topics such as failure prevention and monitoring, collaboration analysis, quality control,
product identification or document management. These vApps have been developed to meet users’
needs and, as such, they have also been validated against their needs and metrics. The vf-OS
platform has been applied in the European project “Zero Defects Manufacturing Platform” (ZDMP)
for the development of apps related to products’ and processes’ quality to support industrial
companies with the achievement of zero-defects in manufacturing.
To offer an overview of the ease with which a vApp is developed, the steps for its development
are described as follows: (i) developer (D) logs in to the vf-OS Platform, where D has access and
opens the vf-Studio; (ii) D uses the different components to create the vApps, mainly the process
designer, for the skeleton or backend, and the frontend environment, for the UI. When the skeleton
is being created, D has access to the vf-Store for purchasing vf-OS assets that have some packed
functionality, such as access to machine-learning or ETL routines, or access to drivers, etc.; (iii) D
uses then the vf-Studio again to finish off the development of the vApp (e.g., bug fixing or test-run of
the vApp) before publication; (iv) once the vApp has been stabilised, D can publish the vApp in the
vf-Store providing details such as the price or description; (v) industrial user, (IU) access the vf-Store
and seek for a vApp that does what they need. If no vApp is found, then the IU can create a request
for a new vApp (which then reaches a developer that proceeds following the steps before); (vi) IU
purchases the desired vApp and, after payment, UI receives a link to download the vApp; and (vii)
IU logs into their vf-OS platform and, through the system dashboard, they can install the purchased
vApp. When this process is compared to the traditional one, some benefits such as rapidity, cost and
complexity reduction arise.
4. Conclusions
Given the scant references found in the literature related to low-code, it can be stated that
low-code is still a young emerging technology. Forrester Research forecasts [29] total spending on
low-code issues of $21.2 billion by 2022. If the forecast is accurate, it seems that low-code
development platforms will be regularly accepted as a common mean to build apps.
During the development of this analysis, aspects such as improved agility, cost reduction, faster
apps building and delivery, among others have been highlighted as key factors in the automation of
software development tools. To this end, CASE technology emerged in the late 1980s, however its
poor adoption has currently led to search for alternative technologies such as the low-code
development platforms. However, it is worth mentioning that the use of low-code development
platforms also presents some barriers. Humans are by nature reluctant to change and the universal
adoption of low-code may be diminished due to the resistance to change by companies. Otherwise,
the impatience in its adoption can also lead to ‘shadow IT’ since the IT department of a company
does not test and approve the technology that the company is using. This can also lead to risks with
compliance and security. The future of low-code paradigm is still uncertain. So, to provide some
certainty in this domain, and after analysing the literature, it can be concluded that the low-code
technology as an automation software development tools is under-researched.
As the results from the literature are scant, the main features that a low-code development
platforms should have and offer (open source, developers’ hub, messaging and Pub/Su) have been
identified. Then, benchmarking among existing low-code development platforms has been
performed against vf-OS. This has resulted in a set of findings that highlight the lack of transversal
platforms developed on open standards to create ecosystems for building and deploying, in an
automated manner, apps. All this indicates that the issues addressed in the research question RQ1
have been answered.
Based on these findings, vf-OS platform emerges to facilitate the app-building process and to
not be dependent on off-the-shelf and third-party software.
Appl. Sci. 2020, 10, 12 17 of 19
Based on the RQ2, one of the key challenge is to address the issues of real-time data processing
these applications require [6]. In light of this, the fundamental aspect for further study is the linkage
between low-code development platforms and IoT devices to consolidate Industry 4.0. Doing so
requires new further attempts focused on low-code research for the apps development that
facilitates the communication and optimisation of intelligent, interconnected equipment and
products along the entire value chain. To this end, vf-OS was born. vf-OS is an open multi-sided
framework able to manage the overall network of a collaborative manufacturing and logistics
environment that enables humans, applications, and devices (IoT) to seamlessly communicate and
interoperate in the interconnected environment, promoting digital transformation. vf-OS may be
considered as an example from where future research efforts should be directed, taking into account
its multi-sided and transversal characteristics. In light of this, one of the main challenges of the
current approach is the integration of the different development environments in a single IDE. To
provide a satisfactory user experience for developers, it is necessary to deliver a high-level of
integration between the different development tools, not only enabling access to the different tools
in an integrated environment, but also implementing the same look and feel design and usability
considerations across different tools to improve user experience. Also, the development of wizards
that guide developers through the development steps across the different development tools can
improve significantly the user experience when developing new applications.
Another important challenge is the integration of secure code analysis into the development
workflows. Currently, the development tools provide static security code analysis reports when
building new applications, based on the source code provided. However, there is no integration
with dynamic application security analysis tools that test vulnerabilities during runtime. Integration
of this type of tools into the vf-OS Platform via the vf-OS Privacy and Security component is another
line of future work.
Finally, experts predict that low-code will be possibly crucial for working efficiently and being
competitive. In the literature, there are examples of many companies that saw their business
continuity in danger because they were not resilient enough and they did not adapt quickly to the
new wave of digital technology promoted by Industry 4.0. Enterprises need to develop new digital
solutions much faster than their competitors and automation software development tools such as the
low-code development platforms may be the response to these new companies’ digital
Author Contributions: Conceptualization, R.S. and R.P.; Investigation, F.F., O.G.-P., R.S.; Methodology, R.S.
and R.P.; Project administration, R.P.; Resources, R.P.; Supervision, R.P. and O.G.-P.; Writing—original draft,
F.F., O.G.-P. R.S.; Writing—review and editing, F.F., R.S., R.P. and O.G.-P. All authors have read and agreed to
the published version of the manuscript.
Funding: This work was supported in part by the European Commission under the Grant Agreements No.
723710 and 825631.
Acknowledgments: The authors would like to acknowledge the support of the researchers participating in the
collaborative projects “Virtual Factory Open Operating System” (vf-OS) ( and “Zero Defects
Manufacturing Platform (ZDMP) (
Conflicts of Interest: The authors declare no conflict of interest.
1. Sanchis, R.; Poler, R. Enterprise Resilience Assessment-A Quantitative Approach. Sustainability 2019, 11,
2. Tisi, M.; Mottu, J.M.; Kolovos, D.; De Lara, J.; Guerra, E.; Di Ruscio, D.; Pierantonio, A.; Wimmer, M.
Lowcomote: Training the Next Generation of Experts in Scalable Low-Code Engineering Platforms. 2019.
Available online:
ng-platforms/ (accessed on 4 December 2019).
3. OutSystems. The State of Application Development. Is IT Ready for Disruption? OutSystems: Boston, MA, USA,
Appl. Sci. 2020, 10, 12 18 of 19
4. Richardson, C.; Rymer, J.R. New Development Platforms Emerge For Customer-Facing Applications; Forrester:
Cambridge, MA, USA, 2014.
5. Waszkowski, R. Low-code platform for automating business processes in manufacturing.
IFAC-PapersOnLine 2019, 52, 376–381.
6. Richardson, C.; Rymer, J.R. Vendor Landscape: The Fractured, Fertile Terrain of Low-Code Application Platforms;
Forrester: Cambridge, MA, USA, 2016.
7. Tarasiev, A.; Filippova, M.; Aksyonov, K.; Aksyonova, O. Developing Prototype of CASE-Tool to Create
Automation Systems Based on Web Applications Using Code Generation. In Proceedings of the XII
International Scientific and Technical Conference Dynamics of Systems, Mechanisms and Machines,
Omsk, Russia, 13–15 November 2018; IEEE: Piscataway, NJ, USA, 2019; pp. 1–4.
8. Al-ashwal, D.; Al-Sewari, E.Z.; Al-Shargabi, A.A. A CASE Tool for JAVA Programs Logical Errors
Detection: Static and Dynamic Testing. In Proceedings of the 2018 International Arab Conference on
Information Technology (ACIT), Sidon, Lebanon, 28–30 November 2018; pp. 1–6.
9. Glover, N.; Dudley, T. Practical Error Correction Design for Engineers; Data Systems Technology
Corporation: Reston, VA, USA, 1991.
10. Lundell, B.; Lings, B. Changing perceptions of CASE technology. J. Syst. Softw. 2004, 72, 271–280.
11. Fuggetta, A. A Classification of CASE Technology. Comput. J. 1993, 35, 25–38.
12. Vileiniskis, T.; Skersys, T.; Pavalkis, S.; Butleris, R.; Butkiene, R. Lightweight approach to model
traceability in a CASE tool. In AIP Conference Proceedings, Proceedings of the ICNAAM 2017, Thessaloniki,
Greece, 25–30 September 2017; American Institute of Physics: College Park, MD, USA, 2017; Volume 1863.
13. Madoš, B.; Ádám, N.; Baláz, A.; Šinal’ová, K. The CASE tool for programming of the multi-core
System-on-a-Chip with the data flow computation control. In Proceedings of the IEEE 15th International
Symposium on Applied Machine Intelligence and Informatics (SAMI 2017), Herl’any, Slovakia, 26–28
January 2017; pp. 165–168.
14. Sassi, M.S.H.; Jedidi, F.G.; Fourati, L.C. Computer-aided software engineering (CASE) tool for big data
and IoT architecture. In Proceedings of the 2019 15th International Wireless Communications & Mobile
Computing Conference (IWCMC), Tangier, Morocco, June 24–28, 2019; pp. 1403–1410.
15. Troy, D.; McQueen, R. An approach for developing domain specific CASE tools and its application to
manufacturing process control. J. Syst. Softw. 1997, 38, 165–192.
16. Huff, C.C. Elements of a realistic CASE tool adoption budget. Commun. ACM 1992, 35, 45–55.
17. Orlikowski, W.J. CASE Tools as Organizational Change: Investigating Incremental and Radical Changes
in Systems Development. MIS Q. 1993, 17, 309–340.
18. Iivari, J. Why Are CASE Tools Not Used? Commun. ACM 1996, 39, 94–103.
19. Land, O.; Der Zanden, V. Enterprise Design—A practice-driven response for generating and
implementing business models. In Proceedings of the 8th Enterprise Engineering Working Conference
(EEWC 2018), Luxembourg, 28 May–1 June 2018.
20. Zolotas, C.; Chatzidimitriou, K.C.; Symeonidis, A.L. RESTsec: A low-code platform for generating secure
by design enterprise services. Enterp. Inf. Syst. 2018, 12, 1007–1033.
21. Henriques, H.; Lourenço, H.; Amaral, V.; Goulão, M. Improving the developer experience with a low-code
process modelling language. In Proceedings of the 21th ACM/IEEE International Conference on Model
Driven Engineering Languages and Systems, Copenhagen, Denmark, 14–19 October 2018; pp. 200–210.
22. Gavrila, V.; Bajenaru, L.; Dobre, C. Modern Single Page Application Architecture: A. Case Study. Stud.
Inform. Control 2019, 28, 231–238.
23. Pantelimon, S.G.; Rogojanu, T.; Braileanu, A.; Stanciu, V.D.; Dobre, C. Towards a seamless integration of
iot devices with iot platforms using a low-code approach. In Proceedings of the IEEE 5th World Forum
Internet Things, WF-IoT 2019, Limerick, Ireland, 15–18 April 2019; pp. 566–571.
24. Wu, Y.; Wang, S.; Bezemer, C.P.; Inoue, K. How do developers utilize source code from stack overflow?
Empir. Softw. Eng. 2019, 24, 637–673.
25. Hamming, R.W. Error detecting and error correcting codes. Bell Syst. Tech. J. 1950, 29, 147–160.
26. Tse, D. Fundamentals of Wireless Communication1; Cambridge University Press: Cambridge, UK, 2004.
27. OutSystems. Build Enterprise-Grade Apps Incredibly Fast; OutSystems: Boston, MA, USA, 2019. Available
online: (accessed on 18 September 2019).
28. Forrester. Available online: (accessed on 18 September 2019).
Appl. Sci. 2020, 10, 12 19 of 19
29. Rymer, J.R.; Koplowitz, R. The Forrester Wave
: Low-Code Development Platforms for AD&D Professionals, Q1
2019; Forrester: Cambridge, MA, USA, 2019.
30. Fryling, M. Low code app development. J. Comput. Sci. Coll. 2019, 34, 119.
31. Clancy, T. The Standish Group Chaos Report; Standish Group: West Yarmouth, MA, USA, 2014.
32. Jost, B.; Ketterl, M.; Budde, R.; Leimbach, T. Graphical programming environments for educational
Robots: Open Roberta—Yet another one? In Proceedings of the 2014 IEEE International Symposium on
Multimedia ISM 2014, Taichung, Taiwan, 10–12 December 2014; pp. 381–386.
33. Dehouck, R.E.M.I. The Maturity of Visual Programming. Режим доступу. 2015. Available online:
http://www. craft. ai/blog/the-maturity-of-visualprogramming (accessed on 17 December 2019).
34. Bragg, S.D.; Driskill, C.G. Diagrammatic-graphical programming languages and DoD-STD-2167A. In
Proceedings of the AUTOTESTCON ’94, Anaheim, CA, USA, 20–22 September 1994; pp. 211–220.
35. Virtual Factory Operating System. 2019. Available online: (accessed on 2 September 2019).
36. Thompson, H. Road4FAME Consultation Event “Digital Revolution in Europe: Converging Visions for a
Smarter World”. In Proceedings of the Road4FAME Consultation, Brussels, Belgium, 22 May 2015.
37. García-Perales, O. vf-OS D1.1: Vision Consensus. 2017. Available Online:
(accessed on 20 October 2019).
38. vf-OS Wiki. Available online:
(accessed on 10 September 2019).
39. García-Perales, O. vf-OS D2.1: Global Architecture Definition. 2017. Available Online: (accessed on 10 October 2019).
40. Siemens MindSphere. 2019. Available online: (accessed on: 10 November 2019).
41. PTC ThingWorx Platform. 2019. Available online: (accessed on 20 October 2019).
42. GE Predix. 2019. Available online: (accessed on 3 October 2019).
43. IBM Cloud. 2019. Available online: (accessed on 30 September 2019).
44. Microsoft Azure IOT Suite. 2019. Available online:
(accessed on 10 November 2019).
45. Software AG ADAMOS. 2019. Available online: (accessed on: 17 November 2019).
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (
... Similar definitions appear in other peer-reviewed papers as well - [1], [6], [7], [12]- [22]. Consequently, to capture the multifaceted nature of low-code development and to ensure comprehensiveness, the following definition is proposed and used in this article: Low-code software development is a development approach that enhances rapid, flexible, and iterative software development by enabling quick business requirements translation through visual programming with a graphical interface, visual abstraction, and minimal hand-coding; and involving practitioners with various backgrounds and software development experience. ...
... A feature that supports the connection of application to various data sources -relational databases, non-relational databases, or files [19], [24] Interoperability with external services A feature that provides functionality to incorporate various external services, commonly through APIs [19], [24] Business logic specification mechanisms Business rules engine A feature that allows for establishing the logic and executing business rules helping to manage data according to requirements [8], [19] Graphical workflow editor A feature that enables visual-based specification of business rules, where workflows are defined using graphical diagrams similar to business process model and notation [6], [19] AI-enabled business logic A feature that is learning attributes behavior and replicates it conforming to artificial intelligence-based learning mechanisms [19] Development automation features Automatic development A feature that enables the automatic generation of applications (for instance, automatically generating an application from a spreadsheet) [9], [12] Automation of low-level details A feature that automates low-level concerns in application development, such as object-relational mapping, load balancing, data integrity, query optimization, services, messaging, authentication, and more [8], [19] Collaborative development support ...
... Acceleration of the development cycle [1], [5], [6], [10], [11], [13], [14], [19], [26], [27], [29], [32], [35], [40]- [42] BE2 Involvement of citizen developers [1], [5], [6], [10]- [12], [14], [19], [26], [35], [38], [41]- [43] BE3 Decreased costs [1], [5], [6], [11], [14], [19], [27], [32], [35], [40], [44] BE4 ...
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Low-code development provides the ability to create software using visual application development tools, predefined components, and automation, minimizing the reliance on manual coding. Furthermore, it enables individuals with limited programming expertise to actively contribute to software development in collaboration with information technology (IT) professionals, improving the alignment between customer or business requirements and the developed solution. This approach speeds up the development process, fosters closer collaboration between software development and business teams, and enhances the organization’s ability to respond to business and market demands or changes. In this article, existing knowledge of low-code development from multiple perspectives is summarized, including the definitions, used tools, applied development lifecycles, application areas, potential benefits, challenges, and, consequently, relevant development and delivery principles.
... Developing these cloud-native applications necessitates grappling with various Cloud Infrastructure Procedures (CIPs). Building a cloud infrastructure from scratch is complex, error-prone, and time-consuming, requiring specialized knowledge and skills to design, develop, and integrate it [2][3][4][5][6][7]. As such, a substantial amount of automation is necessary to simplify the development and deployment process in the cloud. ...
... Companies are focused on increasing their speed in cloud computing adoption, aiming for quicker deployments, release cycles, and recovery times [1]. The latest studies highlight various strategies to streamline cloud infrastructure management: Command-Line Interface scripting (CLI) [1][2], low code/no-code platforms (LPC) [4][5], Continuous Integration and Deployment (CI/CD) [6][7], and Infrastructure as Code (IaC) [8][9][10][11][12][13]. Despite these strategies, cloud deployment still faces obstacles. ...
... A Low Code Platform (LCP) is a software development approach highlighting visual logic representation, drag-and-drop component positioning, and automatic asset integration [4]. LCP enables rapid delivery tailored to market and internal needs [5]. LCP barriers include the inability of architectural diagrams to represent complex software, detailed application logic, and infrastructure environments; the superior productivity of common programming languages to capture more sophisticated logic; a lack of precise representation standards across LCP vendors (CIPs 3, 7, 8, and14; and minimal effect on applications security, data protection, and optimization (CIPs 10-13). ...
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Cloud computing embodies a conundrum. On one side, it offers virtually limitless computational resources, a flexible pay-per-use approach, and various software services that can be broadly applied to digital evolution. On the other hand, managing a cloud environment is complex, requires high computational costs, and can be intimidating for organizations and individuals lacking access to cloud specialists. We identified 14 fundamental "Cloud Infrastructure Procedures" (CIPs) applicable to software development processes on the public cloud and the challenges associated with each one. We then evaluated the capabilities of leading cloud automation technologies, such as Infrastructure as Code (IaC), and pinpointed their gaps in enabling the CIPs. Cloud software development with the cloud SDK and deployment automation using IaC templates has significant limitations. Both the SDK and the IaC are of a low level, require specialized knowledge that takes time to acquire, are disconnected from one another, and are frequently developed by separate engineering teams. Using SDK + IaC in multiple tests, staging, and production environments exacerbates size and complexity concerns. In response to the revealed gaps, we established and empirically validated the "Infrastructure from Python Code" (IfC) approach as a significant advance in the field of IaC to tackle the CIP challenges. IfC is a recent trend in cloud DevOps automation that aims to generate cloud deployment templates from application source code automatically. IfC interprets standard programming language code and automatically generates the cloud environment configuration specifications. We evaluated IfC within a real-world application development case study by 24 different development teams.
... 6,16 For example, research by Forrester shows that low-code platforms speed up development about five to ten times. 18 According to Gartner, 7 low-code will account for more than 70 percent of software-development activity by 2025. This article presents one of the first research-based studies focused on productivity differences among types of development technology. ...
This article aims to provide new insights on the subject by presenting the results of laboratory experiments carried out with code-based, low-code, and extreme low-code technologies to study differences in productivity. Low-code technologies have clearly shown higher levels of productivity, providing strong arguments for low-code to dominate the software development mainstream in the short/medium term. The article reports the procedure and protocols, results, limitations, and opportunities for future research.
... This causes a lot of costs in terms of time, money, and effort. The developer needs to have good experience and knowledge in the development activities and programming languages to be able to develop an application [2] [3]. ...
... The authors conclude that faster development (i.e., higher efficiency) and lower development complexity are the most often discussed drivers for LCDP adoption. The authors of [37] research LCDP adoption on an organisational level by surveying IT experts and find that accelerated digital transformation and reduced dependency on IT developers are the main drivers for LCDP adoption. Another paper that researches LCDP adoption on an organisational level is [1]. ...
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Although adopting Low Code Development Platforms (LCDPs) promises significant efficiency and effectiveness improvements for application development, its adoption still needs further empirical research. This paper uses a combinatorial approach to research LCDP adoption and presents the results of a multiple mini case study with 36 cases on LCDP adoption. A combination of the Socio-Technical Systems theory and the Technology-Organisational-Environment model is used as a theoretical lens. In this paper, we show that LCDP adoption is a multifaceted phenomenon and identify three archetypes for LCDP adoption (i.e., IT Resource Shortage Mitigators, Application Development Democratisers, and Synergy Realisers) and one archetype for LCDP non-adoption (i.e., Intricacy Adversaries). Each archetype can be interpreted as an individual path towards LCDP (non-)adoption. Based on these archetypes, we derive seven starting points for practitioners to adopt LCDPs in work systems. Moreover, by using the theoretical lenses, the paper shows that for an LCDP adoption to occur, an optimisation of the social and technical sub-systems is required.
... LCSD is a semi-automated visual approach to software development. The core idea is that by using LCSD, a software engineer can abstract and semi-automate every aspect of a software system development lifecycle while also accelerating the delivery of the numerous applicational modules that compose it (Bucaioni et al., 2022;Sanchis et al., 2019;Sarkar, 2022). ...
... Other professionals use Low Code and No-Code tools for their work [51]. These tools are distinguished by their holistic comprehension of content and ability to automate processes while offering a user-friendly interface [13,52]. These environments find widespread adoption among various categories of knowledge workers. ...
Low-code and no-code applications are increasingly becoming the technology of choice for many professionals in the digital workplace. According to Gartner data, 70% of new apps built by enterprises will employ low-code or no-code technologies by 2025, up from less than 25% in 2020. The proliferation of these platforms is fueling the rise of citizen development. The objective of this chapter is to discuss briefly how they are different from our traditional software development and evaluate the risks, vulnerabilities, threats, and security concerns associated with auditing them. Also, after assessing these risks, the authors will identify controls that can be used to mitigate these risks. The key security concerns and proposed security measures to safeguard low-code/no-code platforms were analyzed using a systematic approach. The study concluded that, while these platforms provide several advantages, they also pose new security issues that must be addressed. The outcomes of this research can assist businesses in making educated decisions about employing low-code/no-code platforms.
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The low-code platform enables quick generation and delivery of business applications with minimum effort to write in a coding language and requires the least possible effort for the installation and configuration of environments, and training and implementation. With a rapidly growing number of companies, the use of low-code solutions can be a significant step forward in creating essential business applications. This paper describes the use of the Aurea BPM low-code platform for automating business processes in manufacturing.
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Enterprise resilience is a key capacity to guarantee enterprises’ long-term continuity. This paper proposes a quantitative approach to enhance enterprise resilience by selecting optimal preventive actions to be activated to cushion the impact of disruptive events and to improve preparedness capability, one of the pillars of the enterprise resilience capacity. The proposed algorithms combine the dynamic programming approach with attenuation formulas to model real improvements when a combined set of preventive actions is activated for the same disruptive event. A numerical example is presented that shows remarkable reductions in the expected annual cost due to potential disruptive events.
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This paper presents the latest technologies and methodologies available today with a view to creating a high performance, unique and user-experience centric platform. The Client application is a Single Page Application (SPA) and is the most complex component due to its extremely modular architecture. This is not a simple webpage but a stand-alone application, divided into components according to their role. The modular and complex component-based architecture proposed at all levels of the application, ranging from the client all the way up to the storage level, underlies the INTELLIT platform. The INTELLIT platform aims to provide an easy access to information about the life and work of Romanian authors, the most important moments in our culture, the complete calendar of events from 1994 to 2000, the canonical work of different national authors. The new approach also addresses the identification of new ways to modulate and structure such a platform, both on the client side and on the server side, so that individual testing of the various components and any subsequent changes can be achieved as easily as possible. The main reasons these technologies and models were chosen are performance, low code duplication, modularity and reuse of components.
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The increasing volatility and complexity of business models call for a fast and yet robust approach to continuous transformation. Enterprise Design is an emerging and practice-driven response for generating and implementing business models, while integrating innovative and disruptive Information Technology. At a limited scale, practical experience has been gained in several industry environments. To establish a research program to further enhance, develop and mature Enterprise Design, a ½ day Industry-meets-Academia forum on Enterprise Design was conducted, exploring the strengths and weaknesses of this approach, and seeking for opportunities for further research collaboration with industrial relevance. It appeared to be crucial to further increase the speed and robustness of transformation by a gradual expansion of the meta-model of the ED approach, continuously applied on real-life cases (e.g. supported by low-code platforms). Also of major relevance is the creation of a governance model for Enterprise Design that is able to handle interventions in the context of disruptive innovations; also these governance models should be applied and monitored in real-life cases to establish best-practices in timings, iterations, order of working and the relationship with achieved benefits.
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Technical question and answer Q&A platforms, such as Stack Overflow, provide a platform for users to ask and answer questions about a wide variety of programming topics. These platforms accumulate a large amount of knowledge, including hundreds of thousands lines of source code. Developers can benefit from the source code that is attached to the questions and answers on Q&A platforms by copying or learning from (parts of) it. By understanding how developers utilize source code from Q&A platforms, we can provide insights for researchers which can be used to improve next-generation Q&A platforms to help developers reuse source code fast and easily. In this paper, we first conduct an exploratory study on 289 files from 182 open-source projects, which contain source code that has an explicit reference to a Stack Overflow post. Our goal is to understand how developers utilize code from Q&A platforms and to reveal barriers that may make code reuse more difficult. In 31.5% of the studied files, developers needed to modify source code from Stack Overflow to make it work in their own projects. The degree of required modification varied from simply renaming variables to rewriting the whole algorithm. Developers sometimes chose to implement an algorithm from scratch based on the descriptions from Stack Overflow answers, even if there was an implementation readily available in the post. In 35.5% of the studied files, developers used Stack Overflow posts as an information source for later reference. To further understand the barriers of reusing code and to obtain suggestions for improving the code reuse process on Q&A platforms, we conducted a survey with 453 open-source developers who are also on Stack Overflow. We found that the top 3 barriers that make it difficult for developers to reuse code from Stack Overflow are: (1) too much code modification required to t in their projects, (2) incomprehensive code, and (3) low code quality. We summarized and analyzed all survey responses and we identified that developers suggest improvements for future Q&A platforms along the following dimensions: code quality, information enhancement & management, data organization, license, and the human factor. For instance, developers suggest to improve the code quality by adding an integrated validator that can test source code online, and an outdated code detection mechanism. Our findings can be used as a roadmap for researchers and developers to improve code reuse.
Conference Paper
During testing of programs, developers face two types of errors: syntax errors, and logical errors. Generally, logical errors in programming are more difficult to detect. To figure out the reason of that errors, it should trace the source code manually to find the potential instructions that may cause the problem. Consequently the testing will spend a lot of time, effort, and cost. The cost will be problematic with large-scale systems, and the cost will doubled in evolution, confirmation testing, and regression testing. This paper introduces a prototype of a CASE tool for Java logical errors detecting using static and dynamic testing techniques. This research utilizes the Junit and PMD tools to detect the logical errors and analyze the potential causes of these errors based on Java common logical errors lists. The prototype is tested according to some Java programs under different conditions.
Conference Paper
Context: The OutSystems Platform is a development environment composed of several DSLs, used to specify, quickly build and validate web and mobile applications. The DSLs allow users to model different perspectives such as interfaces and data models, define custom business logic and construct process models. Problem: The DSL for process modelling (Business Process Technology (BPT)), has a low adoption rate and is perceived as having usability problems hampering its adoption. This is problematic given the language maintenance costs. Method: We used a combination of interviews, a critical review of BPT using the "Physics of Notation" and empirical evaluations of BPT using the System Usability Scale (SUS) and the NASA Task Load indeX (TLX), to develop a new version of BPT, taking these inputs and Outsystems' engineers culture into account. Results: Evaluations conducted with 25 professional software engineers showed an increase of the semantic transparency on the new version, from 31% to 69%, an increase in the correctness of responses, from 51% to 89%, an increase in the SUS score, from 42.25 to 64.78, and a decrease of the TLX score, from 36.50 to 20.78. These differences were statistically significant. Conclusions: These results suggest the new version of BPT significantly improved the developer experience of the previous version. The end users background with OutSystems had a relevant impact on the final concrete syntax choices and achieved usability indicators.