Feature-oriented Modeling for Collaborative Virtual Environment Construction

Abstract

-Collaborative Virtual Environments (CVEs) introduce significant improvements to communication and interaction by offering a simulated visualization for data representation and synchronized exchange. Participants can share their context and information in a consistent, integrated environment even if they are geographically distributed. These characteristics greatly enhance the virtualization of collaborative applications such as combat training, distance education, and a broad range of domain-specific needs. However, there are many accidental complexities involved in the creation of such environments that make it very challenging for end-users who do not have software development expertise. Our proposed work seeks to simplify and customize CVEs through feature-oriented modeling. The objective of this Ph.D. investigation is to provide a step-wise collaborative environment construction approach for end-users, thus allowing non-experts to create CVEs simply by choosing system features. Specific research challenges in using feature models for this specific application approach will be introduced along with our vision for investigating these issues as a doctoral dissertation.

I. INTRODUCTION AND PROBLEM

Virtual Reality (VR) is a computer-based technique that simulates a physical presence wherein users are able to interact with a virtual world and gain sensory experiences (e.g., visual, haptic, aural). Although an exact definition of VR is hard to formulate (the earliest existence of this concept comes from a science fiction novel written by Weinbaum [ 8 ]), the great benefit of this technique is easy to see —“going nowhere but experiencing anywhere” with equipment (such as headsets and remote controllers). There are many areas that VR could apply, such as education (distance learning), military (combat training), health (surgery simulation), and civil engineering (urban planning). A Collaborative Virtual Environment (CVE) is an extension of a networked virtual environment that provides a context for cooperation combining both the participants and their information into a common display space with integration and persistence.

The construction of CVEs is challenging, both from a hardware aspect ([ 17 ], [ 16 ], [ 3 ]) and software aspect. Software challenges, which are the focus of my research, mainly involve how to facilitate the CVE construction process. Although there are several development tools (such as Unity 3D1, Blender2, 1https://unity3d.com/ 2https://www.blender.org/ JMonkeyEngine3) supporting CVE construction, these tools are highly expertized and developers need programming skills to implement systems using these tools. Such activities always introduce many accidental complexities [ 5 ] to the environment construction.

Model-Driven Engineering focuses more on problem solving from domain aspects rather than a focus on the underlying technology space. The promise of MDE — improving system portability, reuseability and adaptability [ 19 ] [ 15 ] [ 24 ] — makes it an acceptable development methodology both in academic and industrial fields. Feature-oriented software development (FOSD), a MDE-based software development paradigm, involves product synthesis and customization based on system features. Feature models, the core assets in FOSD, encapsulate the commonalities and variabilities of software products. The set of these products builds up a Software Product Line (SPL) [ 21 ]. Feature modeling allows developers to concentrate on a particular domain at an abstract level without knowing implementation details. Though FOSD has been applied to several application domains successfully [ 18 ], employing feature-oriented modeling to virtual environment construction is still new.

In summary, my Ph.D. research aims to answer the following questions:

RQ1 — Methodology: Can we design a novel step-wise feature-oriented approach based on feature priority for software development? RQ2 — Design: Can we design collaborative virtual environments through step-wise feature modeling? RQ3 — Evaluation: To what extent do end-users benefit from feature-oriented CVEs?

II. RELATED WORK

Applying FOSD to CVE construction is still a new research field. Few works attempt to provide CVE construction through feature-oriented approaches. In this section, we review some existing literature related to two research fields: CVE construction and FOSD.

CVEs aim at the synchronization of communication among different participants in one virtual environment. Greenhalgh et al. proposed a collaborative virtual teleconferencing system [ 9 ]. Though this is one of the earliest papers discussing CVEs, the focus of this work is how to process interactions between a human and a computer. For research aiming at the construction of virtual environments, Herna´ndez et al. [ 10 ] proposed a 3D real-time CVE for GUI sketching. In this work, the authors focus on collaborative GUI sketching and implemented a prototype called WeSketch. A similar tool is Teleplace4, a 3D application for virtual on-line meetings. In the industrial context, there are some tools (e.g., Unity 3D, Blender) that allow users to develop a customized virtual environment. However, these tools are highly-expertized and developers need some programming skills to accomplish specific tasks. None of these industrial tools provide support for real-time collaboration.

FOSD deals with external system features in a specific domain. In FOSD, features are treated separately and designers do not need to consider implementation details. A feature model is an abstraction of system features and consists of all the functional and non-functional elements in the system. Feature diagrams [ 11 ] and formal semantics [ 20 ] are widely used to represent feature models. Though FOSD decomposes the complexity of system design, it increases the complexity when integrating and organizing all the system features [ 4 ]. Lee et al. proposed a guideline for solving this problem from domain planning and feature identification [ 13 ]. Although feature prioritization and feature selection are not novel ideas [ 2 ] [ 23 ], there still lacks related work toward applying a selection process to CVE construction. FOSD has been applied to many application domains, such as reverse engineering [ 7 ], computer networks [ 22 ] and image processing [ 6 ].

III. PROPOSED SOLUTION

We propose a step-wise feature-oriented modeling approach for CVE construction. Figure 1 shows the framework for our proposed solution. In the following subsections, we discuss the details in each step and possible tools used to support each step.

4https://telexlr8.wordpress.com/openqwaq/teleplace/

A. Feature Model Construction

In feature model construction, we will first build a prioritized feature model. A prioritized feature diagram is a feature diagram with all the features defined with priorities. For same level nodes, the priorities are labeled as 1,2,3...N. For parent-children nodes, the priorities are labeled as 11, 1-2, 1-3...1-N. When features have the same priorities, their labels are the same. Then, we transform this prioritized feature diagram to a feature table. This table is organized according to priorities and presented to end-users. In order to simplify the construction process and avoid construction problems (e.g., feature interaction [ 14 ] may violate cross-tree dependencies), we propose a step-wise construction for CVEs from a feature table. Users choose features from the feature table step-by-step. For example, if feature A excludes feature B and feature A has higher priority, then if feature A is chosen, feature B is automatically disabled in later steps. For features that have child nodes, when such features are chosen, the feature table will automatically extend to allow users to choose their child feature nodes. There are several tools that support feature modeling construction, such as Feature Modeling Plugin (fmp) [ 1 ] and FeatureIDE [ 12 ]. We plan to implement our approach based on FeatureIDE, which supports all phases of FOSD and is fully integrated in the Eclipse IDE.

B. Product Configuration

In the system implementation phase, the input of this step is the summation of all the features selected by the user from the feature table and the output is a CVE. We plan to design two parts of a user interface — one part is the feature table allowing end-users to choose system features they want and the other part is the real-time generation of the CVE. This phase will be achieved using MDE, which means that CVE construction is generated automatically. Eclipse and FeatureIDE would be our preferred tools for this step. FeatureIDE enables code generation from feature diagram, helping users to jump from high-level abstraction to system implementation. However, FeatureIDE only supports the automated generation of static part in the system. A model for behavioral aspects for the system need to be added in this step. For the convenience of our development, Java will be the hosting language because Eclipse provides an integrated environment for Java development.

C. Collaborative Communication

In the system collaboration phase, we will connect different users who are geographically distributed after the construction of the virtual environment. In our proposed framework, collaborative here means real-time collaboration — data is shared with timely synchronization. One user could see another participant’s actions with low latency. There are some tools supporting real-time CVE development, such as Photon unity networking5 and JMonkeyEngine6. In this step, we plan to apply JMonkeyEngine as an implementation tool because it supports Java development, which is consistent with implementation languages in previous steps.

IV. EVALUATION AND EXPECTED CONTRIBUTION

In order to evaluate our proposed framework, we plan to implement an application based on a feature-oriented CVE — a collaborative virtual classroom. This prototype will implement some basic teaching tasks in a real classroom, such as realtime communication among participants. We plan to test this simple collaborative virtual classroom to real scenarios and test its performance. The analysis could include both qualitative evaluation (such as delay time and storage requirement) and quantitative evaluation (such as semi-structured interview with users and post-surveys).

The contribution of this Ph.D. project is two-fold. We expect that this research will be both beneficial to academia and industry:

In academia, we expect the proposal of step-wise feature modeling could solve part of existing challenges in FOSD and provide related researchers a new aspect to the system construction for product lines from feature modeling. In industry, the contribution to the community may be the new approach for building easy and customized CVEs (software aspects) by non-experts across many domains.

V. CURRENT STATUS

This dissertation work is still in a very early age. At present, we achieved several tasks. First, we performed some existing literature reviews to understand challenges in current FOSD approaches. Furthermore, we tested several mainstream virtual environment building tools. From this testing, we found some issues that prevent an easy and fast way to CVE construction for non-experts. To make the customization of CVEs more accessible to non-experts, we propose applying MDE to overcome these challenges. The next steps of our work include step-wise feature model construction design and implementation, applying step-wise feature modeling approach to build CVEs, and system testing. shows a proposed timeline for completion. The highlights of proposed timeline are shown as follows: 5https://www.photonengine.com/en/Photon 6http://jmonkeyengine.org – 06/2017 — 11/2017: feature table construction – 12/2017 — 05/2018: feature-based virtual environment construction – 12/2017 — 06/2018: feature-based virtual environment testing – 07/2018 — 10/2018: feature-based CVE construction – 07/2018 — 11/2018: feature-based CVE testing – 12/2018 — 04/2019: collaborative virtual classroom implementation – 12/2018 — 05/2019: collaborative virtual classroom testing – 06/2019 — 08/2019: empirical evaluation of featurebased CVE construction – 09/2019 — 12/2019: dissertation and defense

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