In-Situ Visual Programming

Brandstätter, Ulrich; Schenkenfelder, Bernhard

doi:10.4230/OASIcs.Programming.2025.7

In-Situ Visual Programming

Ulrich Brandstätter

Software Competence Center Hagenberg GmbH (SCCH), Austria Bernhard Schenkenfelder

Software Competence Center Hagenberg GmbH (SCCH), Austria

Abstract

Most Visual Programming Environments (VPEs) available today aim to make software development more accessible for specific domains, such as automation, business intelligence, data science, education, or real-time media processing. In their niches, VPEs offer several advantages over traditional text-based programming, including shorter training times, immediate visual feedback, and lower barriers to entry. With this work, we introduce In-Situ Visual Programming (ISVP), a novel programming paradigm to enable users to create, modify, and contribute to software via visual programming in physical contexts. User-created and pre-built programs can be attached to and interlinked with physical objects – in an Augmented Reality (AR) environment. We believe that the spatial and contextual proximity of processing code and physical objects will make software development more intuitive, and we argue this position based on two model use cases.

Keywords and phrases:

Visual programming, End-user programming, Programming paradigm

Copyright and License:

2012 ACM Subject Classification:

Human-centered computing

\rightarrow

Ubiquitous and mobile computing theory, concepts and paradigms

Funding:

The research reported in this paper has been funded by the Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology (BMK), the Federal Ministry for Labour and Economy (BMAW), and the State of Upper Austria in the frame of the SCCH competence center INTEGRATE (FFG grant no. 892418) in the COMET – Competence Centers for Excellent Technologies Programme managed by Austrian Research Promotion Agency FFG.

DOI:

10.4230/OASIcs.Programming.2025.7

Event:

Companion Proceedings of the 9th International Conference on the Art, Science, and Engineering of Programming (Programming 2025)

Editors:

Jonathan Edwards, Roly Perera, and Tomas Petricek

Series and Publisher:

Open Access Series in Informatics, Schloss Dagstuhl – Leibniz-Zentrum für Informatik

1 Introduction and Motivation

Visual Programming Environments (VPEs) allow software developers to write code using visual building blocks instead of, or in addition to, textual programming instructions. Instead of separate implementation files, module declarations, include directives, and function calls, these components are linked together using specific visual paradigms, such as edge connections for flow-based VPEs or jigsaw-like aggregations for block-based VPEs [3]. Either way, they promise a shallow learning curve and increased accessibility, especially when compared to traditional textual programming languages. They empower users of different backgrounds to contribute to and participate in the software development process. While people without a background or training in software development but with expertise in an application domain can benefit from the low barrier to entry of the visual paradigm, professional developers can be more productive [45].

In particular, multi-user capabilities for real-time collaboration allow many people to not only contribute ideas to creative tasks, but to work with the VPE at the same time, which has been shown to improve the quality compared to single-user systems. Working in parallel also makes visual programs more scalable [15]. In the context of learning to program, the benefits include a reduced collaboration effort and improved results, not only when groups work around shared tabletops, but also when using cross-device, co-located VPEs [40].

When Context-Oriented Programming (COP) was introduced more than two decades ago, the idea was to provide explicit support for spatial, temporal, or hardware-related domain-specific and technology-dependent attributes in programming languages. System designs in areas such as personalization, location awareness, and pervasive computing, where there is a great deal of variability due to the constantly changing properties, would benefit from not having to anticipate these dimensions of variability [21, 22].

By combining the above concepts, In-Situ Visual Programming (ISVP) takes software development to the next level. It is a novel programming paradigm based on real physical objects overlaid with and attached to virtual information. Their inherent spatial and contextual proximity is mapped in an AR-based environment, and the use of visual programming to manipulate these objects seamlessly blends into this paradigm. We see In-Situ Visual Programming as a concept with the potential to create a paradigm shift for collaborative software development. The simultaneous alignment and manipulation of physical and virtual objects with visual programming in AR environments can make software development processes more accessible and relatable, but also more playful and fun. Figure 1 illustrates the key motivation for ISVP:

$\blacksquare$

Users can attach programs directly to the physical objects on which they operate, rather than just abstracting their spatial relationships.
$\blacksquare$

Users can more accurately capture everything from requirements to results through an immersive experience with immediate feedback in the live domain.
$\blacksquare$

Flow-based visual programming has a low barrier to entry for software development, reducing the software development effort and facilitating the understanding of cause-and-effect chains through their visualization.
$\blacksquare$

Finally, by allowing multiple users to work either in parallel or collaboratively as they move through physical space, ISVP creates the conditions for engaging and fun virtual and real-world interactions.

The paper is organized as follows. In Section 2, we discuss related work, including both related scientific literature (2.1) and a review of VPEs (2.2). We then detail ISVP from a technical perspective in Section 3, followed by two use cases that illustrate how ISVP could be applied in these example domains (Section 4). We end the paper with our conclusions and ideas for future work (Section 5).

Refer to caption — Figure 1: Following the ISVP paradigm, users can attach visual programs directly to physical objects through an immersive experience and collaboratively manipulate them.

2 Related Work

Our vision of In-Situ Visual Programming (ISVP) is related to Visual Programming (VP), Low-Code Development (LCD), collaborative or multi-user software development, and immersive programming (Section 2.1) as well as context-oriented programming (Section 1). We also provide an overview of Visual Programming Environments (VPEs) that facilitate programming in XR or for XR (Extended Reality), which inspired our vision of ISVP (Section 2.2).

2.1 Literature Review

Common goals of Visual Programming Environments (VPEs) include increased accessibility, improved correctness, and improved code output performance [10]. VPEs involve a higher-level program description, and may make programming and debugging easier even for expert programmers [31]. They are often used in IoT and educational domains [26] as well as in more creative contexts [25]. VPEs can be used to better explain the inner workings of a system [28], to exchange information about software design [45], and to reduce the barrier to entry represented by syntax [30].

Specific VPE advantages are more explicit relationships [11, 8], immediate visual feedback [11], and the preservation of physical spatial relationships [28]. In literature, they are often considered an appropriate interface for parallel software development [8, 34] as well as for large-scale computing [37, 36]. Concerning teaching and learning scenarios, VPEs can be used to motivate students [31, 28], to more easily convey the joy of creating something [23], to attend more exploratory programming domains, e.g., by learning through play [4], and to convey computational thinking [27, 41]. Currently evolving interesting new application scenarios for VPEs include deep learning [42], Large Language Model (LLM) programming [46, 14], and (real-time) data science and machine learning [18]. A more traditional field of application where VPEs slowly start to shine concerns network programming [7, 35].

However, VPEs also involve several drawbacks. Concerning the interface, the limitations of physical screen space are often discussed in the context of VPEs [31, 11, 19], as are the difficulties with large programs and large data [3], also understanding visual programs is often considered challenging [31, 5, 3]. In terms of application areas, VPEs are often domain-specific, lack general functionality, and in many cases provide only a limited set of data types and relevant operators [31, 5, 3]. Additionally, many engineering problems are not inherently spatial [28], challenging the wide-ranging applicability of VPEs. Also, their overall efficiency is often brought into question [31, 11, 3], as is their portability and integrability with programs created in different languages [3]. Another downside concerns documentation, as visual programs are often considered poorly documented and unstructured [31, 11, 3]. Finally, the tools and user interfaces of VPEs are often seen as needing improvement, while at the same time VPEs are considered difficult to create and develop [28, 3].

Low-Code Development (LCD) is a human-centered programming paradigm that empowers end users without software engineering training to address their software requirements themselves. A Low-Code Development Platform (LCDP) helps users to increase their productivity and reduce the complexity of their tasks [13] by providing abstraction techniques that go beyond traditional textual programming [23, 33]. LCD has been around – under various names – for decades: Computer-Aided Software Engineering (CASE) in the 1980s, Rapid Application Development (RAD) in the 1990s, End-User Programming (EUP) in the 2000s, and Model-Driven Engineering (MDE) since 2000 are all aiming at reducing handwritten code in textual programming languages [16]. Many authors use the terms LCD and Visual Programming (VP) interchangeably [20, 38, 2, 9, 33]. However, in a study that examines LCD from a programming model perspective, Hirzel establishes a different taxonomy that groups the techniques of Visual Programming Languages (VPLs), Programming by Demonstration (PBD), and Programming by Natural Language (PBNL) side by side under the Low-Code umbrella [23].

Advantages of LCD that also apply to VP include the potential to alleviate the shortage of skilled personnel, to reduce or even avoid tedious tasks and the involved mistakes, and to multiply time-savings by deploying tasks to colleagues [12, 23] as well as their applicability for rapid prototyping [9]. In addition, a visual Low-Code Development Platform (LCDP) for generating Programmable Logic Controller (PLC) code is reported in an interview study as a common denominator used throughout the company. Intuitive and easy to understand, it allows the various departments involved, such as project planning, construction, and commissioning, to describe and discuss issues related to the machines represented in this visual language [39].

Multi-user and Immersive Programming.

A study of remote pair programming and code comprehension reports that developers working in VR solved twice as many bugs in less time than programmers using a state-of-the-art screen-sharing system, highlighting both the effectiveness and efficiency of this paradigm [17]. Another study found that immersive authoring, i.e., creating VR content while being immersed in VR, can help users to prototype and modify programs by providing immediate feedback, thus reducing the learning curve, and some study participants found the dataflow authoring tool “fun and engaging to work with”. Based on their findings, however, they do not see the benefit of giving users complete 3D freedom; instead, they suggest a combination of 2D and 3D interactions. First, nodes and operators should be connected on a 2D plane, and then they can in turn be connected to 3D objects [47]. This is also one of the core ideas of ISVP. Thomas et al. introduce the concept of Situated Analytics to facilitate sensemaking in the big data domain by associating information with physical objects, natural information exploration, and comprehensive information analysis. Many of their design considerations for the physical and logical worlds are also applicable to the programming of physical objects [43]. In an exploratory user study with seven expert users, Merino et al. observed highly interactive and engaging sessions. They found that the participants were willing to spend a lot of time, even on optional tasks, and were able to complete them while immersed. In addition, their implementation of an expressive yet simple language enabled the participants to take advantage of various visualization features. Again, some of these findings can be applied to the programming of physical objects [29].

2.2 Market Review

VPEs are frequently employed in conjunction with XR environments. Widely-used graphical programming environments, such as vvvv¹¹1https://www.visualprogramming.net/, a Visual Programming Environment for creative coding by the vvvv group, or Blockly²²2https://developers.google.com/blockly/, a popular web-based visual code editor by MIT and Google, often provide specific functions for XR use cases. vvvv for instance features a scene graph API, nodes for user tracking, a variety of input devices, and interfaces with several XR output devices. BlocklyAR [32] on the other hand is a research-driven AR extension for Blockly, it has the ambition to enable non-programmers to write AR applications using a web-based programming frontend. SimpleAR [1] is a high-level content design AR framework for users without programming knowledge; it underwent usability tests based on ISO 9241-11 and was found effective, efficient, and highly acceptable. All these examples use desktop-based development settings, i.e., although the results categorize as XR projects, they are created using 2D development environments.

Approaches that shift software development into XR environments are rarer, and these immersive development approaches primarily target VR. There are domain-specific applications, such as virtual robot programming. Using digital twins, sequences of movements are specified via motion tracking or inversed kinematics based on the spatial reference points given by the user [24]. Concerning XR, the available approaches can either be classified as brute-force or as experimental methods. Brute-force concepts normally use some form of desktop mirroring, with developers capturing the screens of their IDEs and rendering them on 2D VR planes. Although these virtual desktops suffer from various shortcomings of consumer-grade VR equipment, foremost the limited display resolutions, there is already a community sharing this ambition. Experimental general-purpose approaches originate from the worlds of gaming and research. Feature-wise, some of them are quite powerful, for example RecRoom³³3https://recroom.com/, a VR multi-player online game by Against Gravity, features an in-world spatial VR programming language, whereas Cubley [44] focuses on Minecraft-style logic blocks. Of particular interest is NeosVR⁴⁴4https://neos.com/, a free-to-play VR multiplayer online app by Solarix, featuring multi-user capability on top of visual programming in VR.

3 ISVP Platform

The idea behind ISVP is to propose a novel programming paradigm that shifts development to AR environments. At the core of its implementation, the ISVP platform, is a flow-based visual language that allows multiple users to collaboratively develop programs that are directly attached to the real-world physical objects they interact with through an immersive AR experience. This section describes the underlying two-layer approach with a Visual Programming Kernel (VPK) as the base and an AR Visual Programming Interaction Frontend (ARF) on top.

The kernel implements a general-purpose, flow-based, high-performance, real-time visual programming language, including a scheduler, core and domain-specific nodes, graph handling, and multi-user support. To address several shortcomings of current VPEs discussed in literature while preserving their strengths, the authors present design considerations such as color-coded edge activation visualization, runtime deadlock visualization, a strongly typed input/output system with index sharing, edge data type limitation, user cursor visualizations, and session chat windows for the VPK in [6].

The frontend layer provides a set of functions to integrate the kernel, physical objects, and end users. First, a web-based user interface based on state-of-the-art technologies will be developed to visualize and modify the VPK in 2D, taking into account different devices (responsive design) and interaction modes such as click and touch. Then, detected and identified objects are visualized to anchor the VPK and assign specific functionality to these objects. And vice versa, the camera is used to select objects in the first place. In other words, the ARF provides AR-specific nodes for user and object tracking, multi-modal interaction, scene representation and rendering, and node visualization and manipulation tools.

The platform’s modular kernel architecture allows the system to be extended with plug-ins, and extensions with third-party functionality can be realized by developers with access to the source code or plug-in API. The relevant functionality for both VPK and ARF is provided as nodes that contain related data, functions, input, and output. An illustration of the relevant components is shown in Figure 2. As we develop the ISVP platform, including both the VPK and ARF layers, the nodes will be determined by the requirements of the specific use cases provided by the industry-academic collaborations in which the authors are involved. The authors have implemented a VPK prototype following the dataflow programming paradigm and including an extensible stronly typed type system, a generalized UI widget system with relative and absolute anchoring, multi-layer serialization, a node registry supporting compile-time as well as run-time registration, drop-in profiling support, and real-time recursion detection [6]. However, the ARF is still in the design phase.

Figure 2: An overview of the ISVP platform with its main components and features.

4 Use Cases

In this section, we present two model application domains, namely home automation and industrial training, which helped us to discuss, scope and design ISVP internally with fellow developers and externally with other stakeholders such as interested industry partners.

4.1 Home Automation

The first use case is home automation, where the goal is to determine whether the physical proximity of sensors, actuators, or displays and their actual programming is beneficial in practice. Sophisticated home automation systems often have centralized controls where users can change parameters and behaviors. Typically, they can be programmed via mobile applications or dedicated control units. As a result, there is a spatial discrepancy between the location of the physical object to be programmed and the location where the programming takes place, making it difficult to test and understand cause-and-effect chains. With ISVP, it is possible to align the programming with the objects. For example, all the effects of the light sensor in a hallway can be reviewed and modified in situ, bypassed altogether, or linked to additional conditions such as blinds or external factors such as sunlight or temperature. It also makes it easier for other people in the home to modify the home automation programming because the code is easier to find and, more importantly, to understand.

4.2 Industrial Training

The second use case is AR training scenarios. Especially in industrial contexts, AR training is often created by specialized companies or machine manufacturers. They are typically provided as ready-made scenarios with limited support for on-site modifications. With ISVP, it would not only be possible to modify such scenes according to individual needs, but also to create them from scratch. Existing production lines can be augmented with the virtual functionality relevant to training scenarios, such as playing safety training videos, simulating interaction consequences, emergency stop settings, simulated power failures, or visualizing production processes. For the creation and modification of AR trainings, we again consider the spatial proximity of an object and its programming as highly advantageous. Together with the accessible visual programming paradigm, it becomes easier for domain experts to share their knowledge. This use case could also include the ability to assess and react to the skills of training participants, as provided by the visual programming interface.

Given that digital twins not only know the state of the physical objects they mirror, but are also able to communicate back to set their state, the above use cases are also related to digital twins. When programming a physical device in context, e.g., a lamp as shown in Figure 1, ISVP needs to reflect not only the properties of the physical object for programming (i.e., $class=lamp,property=isOn$ ), but also the current state (i.e., $isOn=true$ ). Therefore, it is necessary to read the current state of the device in real time, which is usually provided by a digital twin.

5 Conclusions and Future Work

This vision paper outlines In-Situ Visual Programming (ISVP), a new programming paradigm that aims to move development into AR environments by providing a graphical frontend (AR Visual Programming Interaction Frontend, ARF) to a dataflow-oriented language (Visual Programming Kernel, VPK). ISVP increases the importance of spatial arrangements by using AR technology. Graphical programming blocks can be placed near and attached to physical objects, making the programming more intuitive and facilitating relatable cause-and-effect chains. These issues become even more interesting when considering ISVP’s multi-user capability. As the physical space becomes one with the virtual programming canvas, users can arrange available building blocks, ready-made abstractions, and custom programs in 3D space. By enabling non-expert programmers to contribute to software development with a low barrier to entry, ISVP can alleviate the shortage of skilled workers in various domains. Users can more easily acquire programming skills and collaboratively adapt available solutions to individual needs.

The ISVP platform is being continuously developed as part of industry-academia collaborations in which the authors are involved. While a first prototype of the VPK is already under development, the ARF is still in the design phase. The future development of the ISVP platform is also accompanied by a scientific review that addresses research questions such as the following:

$\blacksquare$

How does the spatial proximity of physical objects and executable code make it easier to understand abstract concepts?
$\blacksquare$

How does the current state of the physical objects being programmed play a role in ISVP, and how can it be taken into account?
$\blacksquare$

How does ISVP foster collaboration between expert programmers, domain experts, and citizen developers?
$\blacksquare$

How does ISVP address the shortcomings of traditional visual programming environments?
$\blacksquare$

How does ISVP affect coordination and collaboration among programmers?
$\blacksquare$

How does ISVP make coding more fun?

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