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.

[1]  A. Paivio.  Mental Representations: A Dual Coding Approach , 1986 .

[2]  Colin Wheildon,et al.  Type & Layout: Are You Communicating or Just Making Pretty Shapes? , 2005 .

[3]  Fausto Giunchiglia,et al.  Tropos: An Agent-Oriented Software Development Methodology , 2004, Autonomous Agents and Multi-Agent Systems.

[4]  Janis A. Bubenko,et al.  Information System Methodologies - A Research View , 1986, Information Systems Design Methodologies: Improving the Practice.

[5]  Ramesh Sharda,et al.  Supporting systems analysis and design through fisheye views , 2004, CACM.

[6]  Zheng Ye Yang,et al.  Factors influencing distance-education graduate students' use of information sources: A user study , 2004 .

[7]  John Mylopoulos,et al.  An Empirical Evaluation of the i* Framework in a Model-Based Software Generation Environment , 2006, CAiSE.

[8]  Eric S. K. Yu,et al.  Towards modelling and reasoning support for early-phase requirements engineering , 1997, Proceedings of ISRE '97: 3rd IEEE International Symposium on Requirements Engineering.

[9]  Neil A. M. Maiden,et al.  REDEPEND: Tool Support for i* Modelling in Large-scale Industrial Projects , 2008, CAiSE Forum.

[10]  S. Kosslyn.  Understanding charts and graphs , 1989 .

[11]  N. Goodman,et al.  Languages of art : an approach to a theory of symbols , 1979 .

[12]  Jinwoo Kim,et al.  How Do We Understand a System with (So) Many Diagrams? Cognitive Integration Processes in Diagrammatic Reasoning , 2000, Inf. Syst. Res..

[13]  M. Bar,et al.  Humans Prefer Curved Visual Objects , 2006, Psychological science.

[14]  Daniel Moody,et al.  What Makes a Good Diagram? Improving the Cognitive Effectiveness of Diagrams in IS Development , 2006 .

[15]  Marian Petre,et al.  Usability Analysis of Visual Programming Environments: A 'Cognitive Dimensions' Framework , 1996, J. Vis. Lang. Comput..

[16]  Ron Weber,et al.  An Ontological Model of an Information System , 1990, IEEE Trans. Software Eng..

[17]  Graeme G. Shanks,et al.  Understanding corporate data models , 1999, Inf. Manag..

[18]  Jock D. Mackinlay,et al.  The structure of the information visualization design space , 1997, Proceedings of VIZ '97: Visualization Conference, Information Visualization Symposium and Parallel Rendering Symposium.

[19]  Sara Jones,et al.  The untrained eye: how languages for software specification support understanding in untrained users , 1999 .

[20]  Anna Perini,et al.  The Tropos visual modeling language . A MOF 1 . 4 compliant meta-model , 2005 .

[21]  Jan Mendling,et al.  Activity labeling in process modeling: Empirical insights and recommendations , 2010, Inf. Syst..

[22]  Iris Vessey,et al.  Cognitive Fit: A Theory‐Based Analysis of the Graphs Versus Tables Literature* , 1991 .

[23]  Eric Yu,et al.  Modeling Strategic Relationships for Process Reengineering , 1995, Social Modeling for Requirements Engineering.

[24]  Pourang Irani,et al.  Diagramming information structures using 3D perceptual primitives , 2003, TCHI.

[25]  Dennis F. Galletta,et al.  Cognitive Fit: An Empirical Study of Information Acquisition , 1991, Inf. Syst. Res..

[26]  D. L. Moody.  Dealing with "Map Shock": A Systematic Approach to Managing Complexity in Requirements Analysis , 2006 .

[27]  Martha E. Crosby,et al.  The effect of graphic style on data model interpretation , 1999, Inf. Syst. J..

[28]  Daniel L. Moody,et al.  Complexity effects on end user understanding of data models : An experimental comparison of large data model representation methods , 2002, ECIS.

[29]  Graeme Simsion,et al.  Data Modeling Essentials 2nd Edition: A Comprehensive Guide to Data Analysis, Design, and Innovation , 2000 .

[30]  Iris Vessey,et al.  The Role of Cognitive Fit in the Relationship Between Software Comprehension and Modification , 2006, MIS Q..

[31]  Jock D. Mackinlay,et al.  Automating the design of graphical presentations of relational information , 1986, TOGS.

[32]  Stefaan Decoene,et al.  Measurement, design, and analysis - an integrated approach - pedhazur,ej, schmelkin,lp , 1995 .

[33]  Jon Oberlander.  Grice for graphics: Pragmatic implicature in network diagrams , 1995 .

[34]  Christopher Alexander.  Notes on the Synthesis of Form , 1964 .

[35]  Patrick Heymans,et al.  Improving the Effectiveness of Visual Representations in Requirements Engineering: An Evaluation of the i* Visual Notation (Best paper award) , 2009 .

[36]  Daniel L. Moody,et al.  The “Physics” of Notations: Toward a Scientific Basis for Constructing Visual Notations in Software Engineering , 2009, IEEE Transactions on Software Engineering.

[37]  Edward R. Tufte,et al.  Envisioning Information , 1990 .

[38]  W. Winn.  Encoding and retrieval of information in maps and diagrams , 1990 .

[39]  David Harel,et al.  On visual formalisms , 1988, CACM.

[40]  Thomas A. Corbi,et al.  The dawning of the autonomic computing era , 2003, IBM Syst. J..

[41]  Gerald L. Lohse,et al.  A Cognitive Model for Understanding Graphical Perception , 1993, Hum. Comput. Interact..

[42]  Charles S. Peirce,et al.  Charles S. Peirce : the essential writings , 1998 .

[43]  Carme Quer,et al.  A Comparative Analysis of i*-Based Agent-Oriented Modeling Languages , 2005, SEKE.

[44]  Marta Indulska,et al.  How do practitioners use conceptual modeling in practice? , 2006, Data Knowl. Eng..

[45]  Steve Hitchman,et al.  The Details of Conceptual Modelling Notations are Important - A Comparison of Relationship Normative Language , 2002, Commun. Assoc. Inf. Syst..

[46]  G. A. Miller.  THE PSYCHOLOGICAL REVIEW THE MAGICAL NUMBER SEVEN, PLUS OR MINUS TWO: SOME LIMITS ON OUR CAPACITY FOR PROCESSING INFORMATION 1 , 1956 .

[47]  Patrick Heymans,et al.  Improving the Effectiveness of Visual Representations in Requirements Engineering: An Evaluation of i* Visual Syntax , 2009, 2009 17th IEEE International Requirements Engineering Conference.

[48]  Betty H. C. Cheng,et al.  Research Directions in Requirements Engineering , 2007, Future of Software Engineering (FOSE '07).

[49]  Neil A. Ernst,et al.  Visualizing non-functional requirements , 2006, 2006 First International Workshop on Requirements Engineering Visualization (REV'06 - RE'06 Workshop).

[50]  Sara Jones,et al.  The Untrained Eye: How Languages for Software Specification Support Understanding in Untrained Users , 1999, Hum. Comput. Interact..

[51]  Bernhard Rumpe,et al.  Meaningful modeling: what's the semantics of "semantics"? , 2004, Computer.

[52]  Matthias Jarke,et al.  Telos: representing knowledge about information systems , 1990, TOIS.

[53]  Ewart R. Carson,et al.  Dealing with Complexity , 1988, Springer US.

[54]  Keng Siau,et al.  Informational and Computational Equivalence in Comparing Information Modeling Methods , 2004, J. Database Manag..

[55]  R. Mayer,et al.  Nine Ways to Reduce Cognitive Load in Multimedia Learning , 2003 .

[56]  Jos van Hillegersberg,et al.  Evaluating the Visual Syntax of UML: An Analysis of the Cognitive Effectiveness of the UMLFamily of Diagrams , 2009, SLE.

[57]  Giancarlo Guizzardi,et al.  Ontological foundations for structural conceptual models , 2005 .

[58]  Wayne Citrin.  Strategic directions in visual languages research , 1996, CSUR.

[59]  Ravindra S. Goonetilleke,et al.  Effects of training and representational characteristics in icon design , 2001, Int. J. Hum. Comput. Stud..

[60]  Janis A. Bubenko,et al.  Requirements Engineering and Technology Transfer: Obstacles, Incentives and Improvement Agenda , 2002, Requirements Engineering.

[61]  William Winn,et al.  An Account of How Readers Search for Information in Diagrams , 1993 .

[62]  Ewart R. Carson,et al.  Dealing with complexity: an introduction to the theory & applications of systemsscience , 1988 .

[63]  Owen Astrachan,et al.  On the Cruelty of Really Teaching Computer Science redux , 2005 .

[64]  Ramana Rao,et al.  The Hyperbolic Browser: A Focus + Context Technique for Visualizing Large Hierarchies , 1996, J. Vis. Lang. Comput..

[65]  Jinwoo Kim,et al.  Why Are Some Diagrams Easier to Work With? : Effects of Diagrammatic Representation on the Cognitive Integration Process of Systems Analysis and Design , 1999 .

[66]  Marian Petre,et al.  Why looking isn't always seeing: readership skills and graphical programming , 1995, CACM.

[67]  A. Treisman.  Perceptual grouping and attention in visual search for features and for objects. , 1982, Journal of experimental psychology. Human perception and performance.

[68]  Xavier Franch,et al.  Towards a Catalogue of Patterns for defining Metrics over i* Models , 2008, JISBD.

[69]  Stephen Fickas,et al.  Goal-Directed Requirements Acquisition , 1993, Sci. Comput. Program..

[70]  Stephen Michael Kosslyn,et al.  Graph Design for the Eye and Mind , 2006 .

[71]  Richard R. Weber.  Ontological Foundations of Information Systems: Coopers and Lybrand , 1997 .

[72]  Nelson Goodman,et al.  Languages of Art, an Approach to a Theory of Symbols , 1970 .

[73]  Andrew Gemino,et al.  Using Iconic Graphics in Entity-Relationship Diagrams: The Impact on Understanding , 2008, J. Database Manag..

[74]  Peter Checkland,et al.  Soft Systems Methodology in Action , 1990 .

[75]  Paul G. Sorenson,et al.  Structured systems analysis using SPSL/SPSA , 1985, Inf. Manag..

[76]  Mary Elizabeth Lynch,et al.  The externalized retina: Selection and mathematization in the visual documentation of objects in the life sciences , 1988 .

[77]  Neil Maiden,et al.  Analysing i * System Models for Dependability Properties : The Uberlingen Accident , 2006 .

[78]  N. Schwarz,et al.  Processing Fluency and Aesthetic Pleasure: Is Beauty in the Perceiver's Processing Experience? , 2004, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.

[79]  R. Atkinson,et al.  Structuring the Transition From Example Study to Problem Solving in Cognitive Skill Acquisition: A Cognitive Load Perspective , 2003 .

[80]  Yvonne Rogers,et al.  External cognition: how do graphical representations work? , 1996, Int. J. Hum. Comput. Stud..

[81]  Chris Gane,et al.  Structured Systems Analysis: Tools and Techniques , 1977 .

[82]  Gennaro Costagliola,et al.  A framework for modeling and implementing visual notations with applications to software engineering , 2004, TSEM.

[83]  Herbert A. Simon,et al.  Why a Diagram is (Sometimes) Worth Ten Thousand Words , 1987, Cogn. Sci..

[84]  Graeme C. Simsion.  Data modeling essentials - analysis, design, and innovation , 1993, VNR computer library.

[85]  David John Jankowski,et al.  A cognitive information processing and information theory approach to diagram clarity: A synthesis and experimental investigation , 1999, J. Syst. Softw..

[86]  Jacques Bertin,et al.  Semiology of Graphics - Diagrams, Networks, Maps , 2010 .

[87]  Elazar J. Pedhazur,et al.  Measurement, Design, and Analysis: An Integrated Approach , 1994 .

[88]  Corin A. Gurr,et al.  Effective Diagrammatic Communication: Syntactic, Semantic and Pragmatic Issues , 1999, J. Vis. Lang. Comput..