Leveraging topic modeling and part-of-speech tagging to support combinational creativity in requirements engineering

Abstract

Requirements engineering (RE), framed as a creative problem solving process, plays a key role in innovating more useful and novel requirements and improving a software system's sustainability. Existing approaches, such as creativity workshops and feature mining from web services, facilitate creativity by exploring a search space of partial and complete possibilities of requirements. To further advance the literature, we study creativity from a combinational perspective, i.e., making unfamiliar connections between familiar possibilities of requirements. In particular, we propose a novel framework that extracts familiar ideas from the requirements and stakeholders' comments using topic modeling, and automatically generates requirements by obtaining unfamiliar idea combinations by means of flipping the part-of-speech of identified topics. We apply our framework on two largescale open-source software systems (Firefox and Mylyn) and report two studies to assess the viability of combinational creativity in RE. The results show that the creativity merit of requirements generated by our framework judged by human experts is comparable to that of requirements created manually. Meanwhile, the cost of our framework is significantly less than manual work, measured by time spent generating requirements. Our work illuminates a possible improvement toward interactive generation of creative requirements using mechanism's outputs.

Creative goal modeling for innovative requirements

“…Other work in creative RE introduces and evaluates specic creativity techniques [46,5,56]. This work is also complementary, and we could explore the integration of these techniques into Creative Leaf, trying to make an eective map to the underlying goal model.…”

“…This raises interesting questions about nding pairs: should we work to nd similar pairs, dissimilar pairs, or let the users nd pairs via chance? In initial versions of pairwise comparison, we used the semantic similarity score used in the evaluation in order to try to nd pairs that were not too similar or dissimilar (bearing similarities to recent work by Bhowmik et al[46]). After evaluation, we decided there was not enough text in individual elements for the scores to be relevant, and abandoned this line of design.…”

O Uso de Design Thinking no Apoio ao Desenvolvimento de Software: Um Estudo de Caso no Contexto de Academias de Musculação

“…A Engenharia de Requisitos busca entender o que o software deve fazer e como se comportar para atender as necessidades dos stakeholders [20]. Com uma indústria altamente competitiva e havendo várias aplicações do mesmo domínio para atender aos usuários, um produto de software precisa se destacar perante os similares, satisfazendo seus usuários com características novas e úteis [4]. Neste contexto, o Design Thinking (DT) surge como um conjunto de práticas inspiradas no design para resolução e desenvolvimento de problemas, utilizando a empatia, a criatividade e a racionalidade para atender às necessidades dos usuários e concretizar os objetivos [26].…”

Semi-supervised learning of local structured output predictors

“…However, in many these applications, the forms of outputs of the prediction may be beyond binary class labels and continues responses. For example, in the part-ofspeech tagging problem of natural language processing, given a sequence of words, we want to predict the tags of the part-of-speech of the works, and the output of the prediction is a sequence of parts-of-speech [26,27,28,29,30]. In the problem of hierarchical image classification problem, the class labels of images are organized as a tree structure, and the outputs of the prediction problem are the leaves of a tree [31,32,33,34].…”