Designing as Construction of Representations: A Dynamic Viewpoint in Cognitive Design Research

This article presents a cognitively oriented viewpoint on design. It focuses on cognitive, dynamic aspects of real design, i.e., the actual cognitive activity implemented by designers during their work on professional design projects. Rather than conceiving de-signing as problem solving - Simon's symbolic information processing (SIP) approach - or as a reflective practice or some other form of situated activity - the situativity (SIT) approach - we consider that, from a cognitive viewpoint, designing is most appropriately characterised as a construction of representations. After a critical discussion of the SIP and SIT approaches to design, we present our view-point. This presentation concerns the evolving nature of representations regarding levels of abstraction and degrees of precision, the function of external representations, and specific qualities of representation in collective design. Designing is described at three levels: the organisation of the activity, its strategies, and its design-representation construction activities (different ways to generate, trans-form, and evaluate representations). Even if we adopt a "generic design" stance, we claim that design can take different forms depending on the nature of the artefact, and we propose some candidates for dimensions that allow a distinction to be made between these forms of design. We discuss the potential specificity of HCI design, and the lack of cognitive design research occupied with the quality of design. We close our discussion of representational structures and activities by an outline of some directions regarding their functional linkages

International conference on software engineering and knowledge engineering: Session chair

The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing. The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome

Choosing effective methods for design diversity - How to progress from intuition to science

Design diversity is a popular defence against design faults in safety critical systems. Design diversity is at times pursued by simply isolating the development teams of the different versions, but it is presumably better to "force" diversity, by appropriate prescriptions to the teams. There are many ways of forcing diversity. Yet, managers who have to choose a cost-effective combination of these have little guidance except their own intuition. We argue the need for more scientifically based recommendations, and outline the problems with producing them. We focus on what we think is the standard basis for most recommendations: the belief that, in order to produce failure diversity among versions, project decisions should aim at causing "diversity" among the faults in the versions. We attempt to clarify what these beliefs mean, in which cases they may be justified and how they can be checked or disproved experimentally

Design: One, but in different forms

This overview paper defends an augmented cognitively oriented generic-design hypothesis: there are both significant similarities between the design activities implemented in different situations and crucial differences between these and other cognitive activities; yet, characteristics of a design situation (related to the design process, the designers, and the artefact) introduce specificities in the corresponding cognitive activities and structures that are used, and in the resulting designs. We thus augment the classical generic-design hypothesis with that of different forms of designing. We review the data available in the cognitive design research literature and propose a series of candidates underlying such forms of design, outlining a number of directions requiring further elaboration

What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

Towards a shared ontology: a generic classification of cognitive processes in conceptual design

Towards addressing ontological issues in design cognition research, this paper presents the first generic classification of cognitive processes investigated in protocol studies on conceptual design cognition. The classification is based on a systematic review of 47 studies published over the past 30 years. Three viewpoints on the nature of design cognition are outlined (search, exploration and design activities), highlighting considerable differences in the concepts and terminology applied to describe cognition. To provide a more unified view of the cognitive processes fundamentally under study, we map specific descriptions of cognitive processes provided in protocol studies to more generic, established definitions in the cognitive psychology literature. This reveals a set of 6 categories of cognitive process that appear to be commonly studied and are therefore likely to be prevalent in conceptual design: (1) long-term memory; (2) semantic processing; (3) visual perception; (4) mental imagery processing; (5) creative output production and (6) executive functions. The categories and their constituent processes are formalised in the generic classification. The classification provides the basis for a generic, shared ontology of cognitive processes in design that is conceptually and terminologically consistent with the ontology of cognitive psychology and neuroscience. In addition, the work highlights 6 key avenues for future empirical research: (1) the role of episodic and semantic memory; (2) consistent definitions of semantic processes; (3) the role of sketching from alternative theoretical perspectives on perception and mental imagery; (4) the role of working memory; (5) the meaning and nature of synthesis and (6) unidentified cognitive processes implicated in conceptual design elsewhere in the literature

Happy software developers solve problems better: psychological measurements in empirical software engineering

For more than 30 years, it has been claimed that a way to improve software developers' productivity and software quality is to focus on people and to provide incentives to make developers satisfied and happy. This claim has rarely been verified in software engineering research, which faces an additional challenge in comparison to more traditional engineering fields: software development is an intellectual activity and is dominated by often-neglected human aspects. Among the skills required for software development, developers must possess high analytical problem-solving skills and creativity for the software construction process. According to psychology research, affects-emotions and moods-deeply influence the cognitive processing abilities and performance of workers, including creativity and analytical problem solving. Nonetheless, little research has investigated the correlation between the affective states, creativity, and analytical problem-solving performance of programmers. This article echoes the call to employ psychological measurements in software engineering research. We report a study with 42 participants to investigate the relationship between the affective states, creativity, and analytical problem-solving skills of software developers. The results offer support for the claim that happy developers are indeed better problem solvers in terms of their analytical abilities. The following contributions are made by this study: (1) providing a better understanding of the impact of affective states on the creativity and analytical problem-solving capacities of developers, (2) introducing and validating psychological measurements, theories, and concepts of affective states, creativity, and analytical-problem-solving skills in empirical software engineering, and (3) raising the need for studying the human factors of software engineering by employing a multidisciplinary viewpoint.Comment: 33 pages, 11 figures, published at Peer

Observational models of requirements evolution

Requirements Evolution is one of the main issues that affect development activities as well as system features (e.g., system dependability). Although researchers and practitioners recognise the importance of requirements evolution, research results and experience are still patchy. This points out a lack of methodologies that address requirements evolution. This thesis investigates the current understanding of requirements evolution and explores new directions in requirements evolution research. The empirical analysis of industrial case studies highlights software requirements evolution as an important issue. Unfortunately, traditional requirements engineering methodologies provide limited support to capture requirements evolution. Heterogeneous engineering provides a comprehensive account of system requirements. Heterogeneous engineering stresses a holistic viewpoint that allows us to understand the underlying mechanisms of evolution of socio-technical systems. Requirements, as mappings between socio-technical solutions and problems, represent an account of the history of socio-technical issues arising and being solved within industrial settings. The formal extension of a heterogeneous account of requirements provides a framework to model and capture requirements evolution. The application of the proposed framework provides further evidence that it is possible to capture and model evolutionary information about requirements. The discussion of scenarios of use stresses practical necessities for methodologies addressing requirements evolution. Finally, the identification of a broad spectrum of evolutions in socio-technical systems points out strong contingencies between system evolution and dependability. This thesis argues that the better our understanding of socio-techn..

Review of research in feature-based design

Research in feature-based design is reviewed. Feature-based design is regarded as a key factor towards CAD/CAPP integration from a process planning point of view. From a design point of view, feature-based design offers possibilities for supporting the design process better than current CAD systems do. The evolution of feature definitions is briefly discussed. Features and their role in the design process and as representatives of design-objects and design-object knowledge are discussed. The main research issues related to feature-based design are outlined. These are: feature representation, features and tolerances, feature validation, multiple viewpoints towards features, features and standardization, and features and languages. An overview of some academic feature-based design systems is provided. Future research issues in feature-based design are outlined. The conclusion is that feature-based design is still in its infancy, and that more research is needed for a better support of the design process and better integration with manufacturing, although major advances have already been made