64 research outputs found

    Creativity and conceptual modeling for requirements engineering

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    Creativity techniques have been applied to Requirements Engineering (RE) in order to find novel requirements, facilitating system and business innovation. Creativity has typically been applied to RE as part of an intensive, often multi-day workshop. Ideas are generated and recorded in a free-form, manual fashion, with much guidance from experienced human facilitators. Although this format has been successful, economic, time, and geographical pressures make this intensive process less feasible. The free-form representation of creative output (text and informal diagrams) provides flexibility in order to support creative thought, but the output of this form is not able to take advantage of much of the (semi-) automated analysis developed for RE, including trade-off analysis. In this work we address two major challenges 1) the limitations of existing creativity RE workshops, particularly their costliness and need for expert guidance, and 2) capturing creative output in a structured form, better amenable to (semi-) automated analysis and downstream development. We address these as part of a 2-3 year project focusing on integrating RE creativity techniques with conceptual modeling techniques such as goal modeling, with a focus on developing online, distributed creative support tools for RE

    Incorporating Modules into the i* Framework

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    Assessing composition in modeling approaches

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    Modeling approaches are based on various paradigms, e.g., aspect-oriented, feature-oriented, object-oriented, and logic-based. Modeling approaches may cover requirements models to low-level design models, are developed for various purposes, use various means of composition, and thus are difficult to compare. However, such comparisons are critical to help practitioners know under which conditions approaches are most applicable, and how they might be successfully generalized and combined to achieve end-to-end methods. This paper reports on work done at the 2nd International Comparing Modeling Approaches (CMA) workshop towards the goal of identifying potential comprehensive modeling methodologies with a particular emphasis on composition: (i) an improved set of comparison criteria; (ii) 19 assessments of modeling approaches based on the comparison criteria and a common, focused case study

    Supporting Materials for Creative Goal Modeling for Innovative Requirements

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    Data supporting IST paper : Creative Goal Modeling for Innovative Requirements J. Horkoff, N. A. Maiden, D. Asboth Abstract [Context] When determining the functions and qualities (a.k.a. requirements) for a system, creativity is key to drive innovation and foster business success. However, creative requirements must be practically operationalized, grounded in concrete functions and system interactions. Requirements Engineering (RE) has produced a wealth of methods centered around goal modeling, in order to graphically explore the space of alternative requirements, linking functions to goals and dependencies. In parallel work, creativity theories from the social sciences have been applied to the design of creative requirements workshops, pushing stakeholders to develop innovative systems. Goal models tend to focus on what is known, while creativity workshops are expensive, require a specic skill set to facilitate, and produce mainly paper-based, unstructured outputs. [Objective] Our aim in this work is to explore benecial combinations of the two areas of work in order to overcome these and other limitations, facilitating creative requirements elicitation, supported by a simple extension of a well-known and structured requirements modeling technique. [Method] We take a Design Science approach, iterating over exploratory studies, design, and summative validation studies. [Results] The result is the Creative Leaf tool and method supporting creative goal modeling for RE. [Conclusion] We support creative RE by making creativity techniques more accessible, producing structured digital outputs which better match to existing RE methods with associated analysis procedures and transformations
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