A General Introduction To Graph Visualization Techniques

Generally, a graph is an abstract data type used to represent relations among a given set of data entities. Graphs are used in numerous applications within the field of information visualization, such as VLSI (circuit schematics), state-transition diagrams, and social networks. The size and complexity of graphs easily reach dimensions at which the task of exploring and navigating gets crucial. Moreover, additional requirements have to be met in order to provide proper visualizations. In this context, many techniques already have been introduced. This survey aims to provide an introduction on graph visualization techniques helping the reader to gain a first insight into the most fundamental techniques. Furthermore, a brief introduction about navigation and interaction tools is provided

Software architecture visualisation

Tracing the history of software engineering reveals a series of abstractions. In early days, software engineers would construct software using machine code. As time progressed, software engineers and computer scientists developed higher levels of abstraction in order to provide tools to assist in building larger software systems. This has resulted in high-level languages, modelling languages, design patterns, and software architecture. Software architecture has been recognised as an important tool for designing and building software. Some research takes the view that the success or failure of a software development project depends heavily on the quality of the software architecture. For any software system, there are a number of individuals who have some interest in the architecture. These stakeholders have differing requirements of the software architecture depending on the role that they take. Stakeholders include the architects, designers, developers and also the sales, services and support teams and even the customer for the software. Communication and understanding of the architecture is essential in ensuring that each stakeholder can play their role during the design, development and deployment of that software system. Software visualisation has traditionally been focused on aiding the understanding of software systems by those who perform development and maintenance tasks on that software. In supporting developers and maintainers, software visualisation has been largely concerned with representing static and dynamic aspects of software at the code level. Typically, a software visualisation will represent control flow, classes, objects, import relations and other such low level abstractions of the software. This research identifies the fundamental issues concerning software architecture visualisation. It does this by identifying the practical use of software architecture in the real world, and considers the application of software visualisation techniques to the visualisation of software architecture. The aim of this research is to explore the ways in which software architecture visualisation can assist in the tasks undertaken by the differing stakeholders in a software system and its architecture. A prototype tool, named ArchVis, has been developed to enable the exploration of some of the fundamental issues in software architecture visualisation. ArchVis is a new approach to software architecture visualisation that is capable of utilising multiple sources and representations of architecture in order to generate multiple views of software architecture. The mechanism by which views are generated means that they can be more relevant to a wider collection of stakeholders in that architecture. During evaluation ArchVis demonstrates the capability of utilising a number of data sources in order to produce architecture visualisations. Arch Vis' view model is capable of generating the necessary views for architecture stakeholders and those stakeholders can navigate through the views and data in order to obtain relevant information. The results of evaluating ArchVis using a framework and scenarios demonstrate that the majority of the objectives of this research have been achieved

A Systematic Literature Review of Software Visualization Evaluation

Abstract Context: Software visualizations can help developers to analyze multiple aspects of complex software systems, but their effectiveness is often uncertain due to the lack of evaluation guidelines. Objective: We identify common problems in the evaluation of software visualizations with the goal of formulating guidelines to improve future evaluations. Method: We review the complete literature body of 387 full papers published in the SOFTVIS/VISSOFT conferences, and study 181 of those from which we could extract evaluation strategies, data collection methods, and other aspects of the evaluation. Results: Of the proposed software visualization approaches, 62 lack a strong evaluation. We argue that an effective software visualization should not only boost time and correctness but also recollection, usability, engagement, and other emotions. Conclusion: We call on researchers proposing new software visualizations to provide evidence of their effectiveness by conducting thorough (i) case studies for approaches that must be studied in situ, and when variables can be controlled, (ii) experiments with randomly selected participants of the target audience and real-world open source software systems to promote reproducibility and replicability. We present guidelines to increase the evidence of the effectiveness of software visualization approaches, thus improving their adoption rate

A Focus+Context Approach to Alleviate Cognitive Challenges of Editing and Debugging UML Models

Copyright (c) 2019 IEEE Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Model-Driven Engineering has been proposed to increase the productivity of developing a software system. Despite its benefits, it has not been fully adopted in the software industry. Research has shown that modelling tools are amongst the top barriers for the adoption of MDE by industry. Recently, researchers have conducted empirical studies to identify the most severe cognitive difficulties of modellers when using UML model editors. Their analyses show that users’ prominent challenges are in remembering the contextual information when performing a particular modelling task; and locating, understanding, and fixing errors in the models. To alleviate these difficulties, we propose two Focus+Context user interfaces that provide enhanced cognitive support and automation in the user’s interaction with a model editor. Moreover, we conducted two empirical studies to assess the effectiveness of our interfaces on human users. Our results reveal that our interfaces help users 1) improve their ability to successfully fulfil their tasks, 2) avoid unnecessary switches among diagrams, 3) produce more error-free models, 4) remember contextual information, and 5) reduce time on tasks.NSERC CREATE 465463-2015 NSERC Discovery Grant 15524

A brief history of models and model based systems engineering and the case for relational orientation

Models are at the heart of science and engineering. Model-based approaches to software development and systems engineering use technologies to include graphical modeling languages, such as the Systems Modeling Language, that support system design and analysis through machine readable models. This paper traces key historical contributions of software and systems engineers over the past five decades to show a coherent concept of models and how they can be used for software and systems engineering. Recent model-based systems engineering methodologies supported by commercially available modeling tools are also summarized. Relational orientation is seen to be the underlying viewpoint that expresses and binds these approaches. Relational orientation for systems engineering (ROSE) is then specified using a general systems methodology. Systems are seen to access each other's models in ROSE much like classes in object orientation access each other's objects. Object-oriented frames for software engineering are extended to relational frames to specify an innovative framework for system design and analysis. This generalizes the axiomatic design approach of N. P. Suh. A repeatable procedure supporting greater concurrency between design and verification is also demonstrated for searching the solution space in linear axiomatic design

Formal methods adoption in the commercial world

: leaves 122-134There have been numerous studies on formal methods but little utilisation of formal methods in the commercial world. This can be attributed to many factors, such as that few specialists know how to use formal methods. Moreover, the use of mathematical notation leads to the perception that formal methods are difficult. Formal methods can be described as system design methods by which complex computer systems are built using mathematical notation and logic. Formal methods have been used in the software development world since 1940, that is to say, from the earliest stage of computer development. To date, there has been a slow adoption of formal methods, which are mostly used for mission-critical projects in, for example, the military and the aviation industry. Researchers worldwide are conducting studies on formal methods, but the research mostly deals with path planning and control and not the runtime verification of autonomous systems. The main focus of this dissertation is the question of how to increase the pace at which formal methods are adopted in the business or commercial world. As part of this dissertation, a framework was developed to facilitate the use of formal methods in the commercial world. The framework mainly focuses on education, support tools, buy-in and remuneration. The framework was validated using a case study to illustrate its practicality. This dissertation also focuses on different types of formal methods and how they are used, as well as the link between formal methods and other software development techniques. An ERP system specification is presented in both natural language (informal) and formal notation, which demonstrates how a formal specification can be derived from an informal specification using the enhanced established strategy for constructing a Z specification as a guideline. Success stories of companies that are applying formal methods in the commercial world are also presented.School of ComputingM. Sc. (Computing

A User-Centric Approach to Improve the Quality of UML-like Modelling Tools and Reduce the Efforts of Modelling

As software systems grow in size and complexity, their development and maintenance are becoming increasingly challenging. Model-Driven Engineering (MDE) has been proposed as a means to increase the developer's productivity of such large-scale complex software systems. Despite its benefits, MDE has not been fully adopted in the software industry due to several barriers. Research has shown that modelling tools are amongst the top barriers for the industry's reluctance to adopt MDE, mostly because there is a little investigation of the modellers' interactions with modelling tools when editing and debugging models, which are cognitively difficult tasks. More specifically, MDE tool research has not considered 1) a thorough analysis of modellers and their tasks, to understand their challenges of using modelling tools, 2) the underlying human-cognitive factors, and 3) a systematic assessment of the effectiveness of proposed solutions (i.e., tooling techniques) on human users. This thesis argues that MDE tools can be enhanced to overcome (some of) the challenges of adoption by considering human-cognitive factors (i.e., user-centric) when designing and proposing model-easing techniques for model editors. We advance our thesis in three main steps. As a first step, we conducted an empirical study to identify the most-severe cognitive difficulties of modellers when using UML model editors. In our study, we asked the recruited subjects to perform several model-editing and model-debugging tasks. We collected information during the sessions that could help us understand the subjects' cognitive challenges. The results show that users face multiple challenges, amongst which the most prominent challenges are remembering contextual information when performing a particular modelling task; and locating, understanding, and fixing errors in the models. In the second step, we identified the cognitive factors that drive the most prominent challenges and subsequently devised several tooling advancements that provide enhanced cognitive support and automation in the users' interaction with a model editor. The philosophy behind our tooling advancements is to provide the contextual information that are relevant to performing a particular modelling task, thereby, alleviating the modellers' cognitive challenges of recollecting information from different diagrams. We also proposed an on-the-fly error-resolution technique that aims at resolving errors as they occur. We implemented our Eclipse-based model-editor and embedded our tooling techniques in the tool. Lastly, we conducted two empirical studies to assess the effectiveness of our model-editor on human users. The Context study aimed at evaluating our tool's ability to reduce the challenges of remembering contextual information, whereas the Debugging study aimed at assessing our tool's ability to improve the users' experience of debugging models. Our results reveal that our interfaces help users 1) improve their ability to successfully fulfil their tasks, 2) avoid unnecessary context switches among diagrams, 3) produce more error-free models, 4) remember contextual information, and 5) reduce time on tasks

mel - Model Extraction Language and Interpreter

There is a large body of research on extracting models from code-related artifacts to enable model-based analyses of large software systems. However, engineers do not always have access to the entire code base of a system: some components may be procured from third-party suppliers based on a model specification or their code may be generated automatically from models. Additionally, the development of software systems does not produce only source code as its output. Modern large software system have various artifacts relevant to them, such as software models, build scripts, test scripts, version control history data, and more. In order to produce a more complete view of a modern software system heterogeneous fact extraction of various artifacts is necessary - not just of source code. This thesis introduces mel— a model extraction language and interpreter for extracting “facts” from models represented in XMI; these facts can be combined with facts extracted from other system components to form a lightweight model of an entire software system. We provide preliminary evidence that mel is sufficient to specify fact extraction from models that have very different XMI representations. We also show that it can be easier to use mel to create a fact extractor for a particular model representation than to develop a specialized fact extractor for the model from scratch