Daniel Moody

The “Physics” of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering

Visual notations form an integral part of the language of software engineering (SE). Yet historically, SE researchers and notation designers have ignored or undervalued issues of visual representation. In evaluating and comparing notations, details of visual syntax are rarely discussed. In designing notations, the majority of effort is spent on semantics, with graphical conventions largely an afterthought. Typically, no design rationale, scientific or otherwise, is provided for visual representation choices. While SE has developed mature methods for evaluating and designing semantics, it lacks equivalent methods for visual syntax. This paper defines a set of principles for designing cognitively effective visual notations: ones that are optimized for human communication and problem solving. Together these form a design theory, called the Physics of Notations as it focuses on the physical (perceptual) properties of notations rather than their logical (semantic) properties. The principles were synthesized from theory and empirical evidence from a wide range of fields and rest on an explicit theory of how visual notations communicate. They can be used to evaluate, compare, and improve existing visual notations as well as to construct new ones. The paper identifies serious design flaws in some of the leading SE notations, together with practical suggestions for improving them. It also showcases some examples of visual notation design excellence from SE and other fields.

Evaluating the Visual Syntax of UML: An Analysis of the Cognitive Effectiveness of the UML Family of Diagrams

UML is a visual language. However surprisingly, there has been very little attention in either research or practice to the visual notations used in UML . Both academic analyses and official revisions to the standard have focused almost exclusively on semantic issues, with little debate about the visual syntax. We believe this is a major oversight and that as a result, UML s visual development is lagging behind its semantic development. The lack of attention to visual aspects is surprising given that the form of visual representations is known to have an equal if not greater effect on understanding and problem solving performance than their content. The UML visual notations were developed in a bottom-up manner, by reusing and synthesising existing notations, with choice of graphical conventions based on expert consensus. We argue that this is an inappropriate basis for making visual representation decisions and they should be based on theory and empirical evidence about cognitive effectiveness. This paper evaluates the visual syntax of UML using a set of evidence-based principles for designing cognitively effective visual notations. The analysis reveals some serious design flaws in the UML visual notations together with practical recommendations for fixing them.

Visual syntax does matter: improving the cognitive effectiveness of the i * visual notation

Goal-oriented modelling is one of the most important research developments in the requirements engineering (RE) field. This paper conducts a systematic analysis of the visual syntax of i*, one of the leading goal-oriented languages. Like most RE notations, i* is highly visual. Yet surprisingly, there has been little debate about or modification to its graphical conventions since it was proposed more than a decade ago. We evaluate the i* visual notation using a set of principles for designing cognitively effective visual notations (the Physics of Notations). The analysis reveals some serious flaws in the notation together with some practical recommendations for improvement. The results can be used to improve its effectiveness in practice, particularly for communicating with end users. A broader goal of the paper is to raise awareness about the importance of visual representation in RE research, which has historically received little attention.

Improving the Effectiveness of Visual Representations in Requirements Engineering: An Evaluation of i* Visual Syntax

Goal-oriented modelling is one of the most important research developments in the RE field. This paper conducts a systematic analysis of the visual syntax of i*, one of the leading goal-oriented languages. Like most RE notations, i* is highly visual. Yet surprisingly, there has been little debate about or modification to its graphical conventions since it was proposed more than a decade ago. We evaluate the notation using a set of evidence-based principles for visual notation design. The paper identifies some serious flaws in the i* visual notation together with some recommendations for improvement. A broader goal of the paper is to raise the level of debate and stimulate discussion about visual representation in RE research.

Visual notation design 2.0: Towards user comprehensible requirements engineering notations

The success of requirements engineering depends critically on effective communication between business analysts and end users, yet empirical studies show that business stakeholders understand RE notations very poorly. This paper proposes a novel approach to designing RE visual notations that actively involves naïve users in the process. We use i*, one of the most influential RE notations, to demonstrate the approach, but the same approach could be applied to any RE notation. We present the results of 5 related empirical studies that show that novices outperform experts in designing symbols that are comprehensible to novices: the differences are both statistically significant and practically meaningful. Symbols designed by novices increased semantic transparency (their ability to be spontaneously interpreted by other novices) by almost 300% compared to the existing i* notation. The results challenge the conventional wisdom about visual notation design: that it should be conducted by a small group of experts; our research suggests that it should instead be conducted by large numbers of novices. The approach is consistent with Web 2.0, in that it harnesses the collective intelligence of end users and actively involves them in the notation design process as “prosumers” rather than passive consumers. We believe this approach has the potential to radically change the way visual notations are designed in the future.

The "physics" of notations: a scientific approach to designing visual notations in software engineering

Visual notations form an integral part of the language of software engineering (SE). Yet historically, SE researchers and notation designers have ignored or undervalued issues of visual representation. In evaluating and comparing notations, details of visual syntax are rarely discussed. In designing notations, the majority of effort is spent on semantics, with graphical conventions often an afterthought. Typically no design rationale, scientific or otherwise, is provided for visual representation choices. While SE has developed mature methods for evaluating and designing semantics, it lacks equivalent methods for visual syntax. This tutorial defines a set of principles for designing cognitively effective visual notations: ones that are optimised for human communication and problem solving. Together these form a design theory, called the Physics of Notations as it focuses on the physical (perceptual) properties of notations rather than their logical (semantic) properties. The principles were synthesised from theory and empirical evidence from a wide range of fields and rest on an explicit theory of how visual notations communicate. They can be used to evaluate, compare and improve existing visual notations as well as to construct new ones. The tutorial identifies serious design flaws in some of the leading SE notations together with practical suggestions for improving them. It also showcases some examples of visual notation design excellence from SE and other fields.

Theory development in visual language research: Beyond the cognitive dimensions of notations

The Cognitive Dimensions of Notations (CDs) framework has become the predominant theoretical paradigm for analysing visual languages (VLs). This paper evaluates the CDs framework using established conceptual frameworks for analysing scientific theories. It concludes that while it is a paradigm, it is not scientific according to standards normally applied in scientific research. It also represents the earliest evolutionary form of theory, which is appropriate when no prior theory exists. This paper asks whether such a theory is an appropriate paradigm for VL research after a quarter of a century of research in this field. The CDs framework has performed a valuable role in advancing the analysis of VLs beyond the level of intuition, but should not be seen as the end point for theory development in this field. This paper proposes a more powerful, domain-specific theory (the Physics of Notations) as an alternative paradigm for VL research.

Representing Classes of Things and Properties in General in Conceptual Modelling: An Empirical Evaluation

How classes of things and properties in general should be represented in conceptual models is a fundamental issue. For example, proponents of object-role modelling argue that no distinction should be made between the two constructs, whereas proponents of entity-relationship modelling argue the distinction is important but provide ambiguous guidelines about how the distinction should be made. In this paper, the authors use ontological theory and cognition theory to provide guidelines about how classification should be represented in conceptual models. The authors experimented to test whether clearly distinguishing between classes of things and properties in general enabled users of conceptual models to better understand a domain. They describe a cognitive processing study that examined whether clearly distinguishing between classes of things and properties in general impacts the cognitive behaviours of the users. The results support the use of ontologically sound representations of classes of things and properties in conceptual modelling.

Towards a more semantically transparent i* visual syntax

[Context and motivation]i* is one of the most popular modelling languages in Requirements Engineering. i* models are meant to support communication between technical and non-technical stakeholders about the goals of the future system. Recent research has established that the effectiveness of model-mediated communication heavily depends on the visual syntax of the modelling language. A number of flaws in the visual syntax of i* have been uncovered and possible improvements have been suggested. [Question/problem] Producing effective visual notations is a complex task that requires taking into account various interacting quality criteria. In this paper, we focus on one of those criteria: Semantic Transparency, that is, the ability of notation symbols to suggest their meaning. [Principal ideas/results] Complementarily to previous research, we take an empirical approach. We give a preview of a series of experiments designed to identify a new symbol set for i* and to evaluate its semantic transparency. [Contribution] The reported work is an important milestone on the path towards cognitively effective requirements modelling notations. Although it does not solve all the problems in the i* notation, it illustrates the usefulness of an empirical approach to visual syntax definition. This approach can later be transposed to other quality criteria and other notations.

The Physics of Notations: Improving the Usability and Communicability of Visual Notations in Requirements Engineering

isual notations form an integral part of the language of requirements engineering (RE), and have dominated RE research and practice from its earliest beginnings. An RE method without a visual representation is almost unheard-of. The primary reason for using visual notations is to exploit the power of human visual processing and thereby optimise human communication and problem solving. Visual representations play a particularly critical role in communicating with end users and customers, as diagrams are believed to convey information more effectively to non-technical people than text. Surprisingly, RE researchers and notation designers have ignored or undervalued issues of visual representation. In evaluating and comparing notations, details of visual syntax are rarely discussed. In designing notations, the majority of effort is spent on semantics, with graphical conventions largely an afterthought. Decisions about graphical representation tend to be made in a subjective way, without reference to theory or empirical evidence, or justifications of any kind (design rationale). Finally, while RE has developed mature methods for evaluating and designing semantics of notations, it lacks equivalent methods for visual syntax.