KBRE: a framework for knowledge-based requirements engineering

Detecting inconsistencies is a critical part of requirements engineering (RE) and has been a topic of interest for several decades. Domain knowledge and semantics of requirements not only play important roles in elaborating requirements but are also a crucial way to detect conflicts among them. In this paper, we present a novel knowledge-based RE framework (KBRE) in which domain knowledge and semantics of requirements are central to elaboration, structuring, and management of captured requirements. Moreover, we also show how they facilitate the identification of requirements inconsistencies and other-related problems. In our KBRE model, description logic (DL) is used as the fundamental logical system for requirements analysis and reasoning. In addition, the application of DL in the form of Manchester OWL Syntax brings simplicity to the formalization of requirements while preserving sufficient expressive power. A tool has been developed and applied to an industrial use case to validate our approach.

A taxonomy and mapping of computer-based critiquing tools

Critics have emerged in recent times as a specific tool feature to support users in computer-mediated tasks. These computer-supported critics provide proactive guidelines or suggestions for improvement to designs, code, and other digital artifacts. The concept of a critic has been adopted in various domains, including medical, programming, software engineering, design sketching, and others. Critics have been shown to be an effective mechanism for providing feedback to users. We propose a new critic taxonomy based on extensive review of the critic literature. The groups and elements of our critic taxonomy are presented and explained collectively with examples, including the mapping of 13 existing critic tools, predominantly for software engineering and programming education tasks to the taxonomy. We believe this critic taxonomy will assist others in identifying, categorizing, developing, and deploying computer-supported critics in a range of domains.

Future integrated factories: a system of systems engineering perspective

The manufacturing sector has gone through tremendous change in the last decade. We have witnessed the transformation from stand alone, manual processes to smart and integrated systems, from hand written reports to interactive computer-based dashboards. Future integrated factories will operate as a system of systems through intelligent machines, human factors integration, and integrated supply chains. To effectively operate and manage these emerging enterprises, a systems science approach is required. Modelling and simulation is recognised as a key enabling technology, with application from stakeholder engagement and knowledge elicitation to operational decision support through self-tuning and self-assembling simulations. Our research has led to the introduction of effective modelling and simulation methods and tools to enable real time planning, dynamic risk analysis and effective visualisation for production processes, resources and systems. This paper discusses industrial applicable concepts for real-time simulation and decision support, and the implications to future integrated factories, or factories of the future, are explored through relevant case studies from aerospace manufacturing to mining and materials processing enterprises.

A text analytics evaluation of a first-year engineering project-based unit

In the undergraduate engineering program at Griffith University in Australia, the unit 1006ENG Design and Professional Skills aims to provide an introduction to engineering design and professional practice through a project-based learning (PBL) approach to problem solving. It provides students with an experience of PBL in the first-year of their programme. The unit comprises an underpinning lecture series, design work including group project activities, an individual computer-aided drawing exercise/s and an oral presentation. Griffith University employs a ‘Student Experience of Course’ (SEC) online survey as part of its student evaluation of teaching, quality improvement and staff performance management processes. As well as numerical response scale items, it includes the following two questions inviting open-ended text responses from students: i) What did you find particularly good about this course? and ii) How could this course be improved? The collection of textual data in in student surveys is commonplace, due to the rich descriptions of respondent experiences they can provide at relatively low cost. However, historically these data have been underutilised because they are time consuming to analyse manually, and there has been a lack of automated tools to exploit such data efficiently. Text analytics approaches offer analysis methods that result in visual representations of comment data that highlight key individual themes in these data and the relationships between those themes. We present a text analytics-based evaluation of the SEC open-ended comments received in the first two years of offer of the PBL unit 1006ENG. We discuss the results obtained in detail. The method developed and documented here is a practical and useful approach to analysing/visualising open-ended comment data that could be applied by others with similar comment data sets.