ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information

Requirements elicitation requires extensive knowledge and deep understanding of the problem domain where the final system will be situated. However, in many software development projects, analysts are required to elicit the requirements from an unfamiliar domain, which often causes communication barriers between analysts and stakeholders. In this paper, we propose a requirements ELICitation Aid tool (ELICA) to help analysts better understand the target application domain by dynamic extraction and labeling of requirements-relevant knowledge. To extract the relevant terms, we leverage the flexibility and power of Weighted Finite State Transducers (WFSTs) in dynamic modeling of natural language processing tasks. In addition to the information conveyed through text, ELICA captures and processes non-linguistic information about the intention of speakers such as their confidence level, analytical tone, and emotions. The extracted information is made available to the analysts as a set of labeled snippets with highlighted relevant terms which can also be exported as an artifact of the Requirements Engineering (RE) process. The application and usefulness of ELICA are demonstrated through a case study. This study shows how pre-existing relevant information about the application domain and the information captured during an elicitation meeting, such as the conversation and stakeholders' intentions, can be captured and used to support analysts achieving their tasks.Comment: 2018 IEEE 26th International Requirements Engineering Conference Workshop

Using mobile RE tools to give end-users their own voice

Researchers highlight end-user involvement in system design as an important concept for developing useful and usable solutions. However, end-user involvement in software engineering is still an open-ended topic. Novel paradigms such as service-oriented computing strengthen the need for more active end-user involvement in order to provide systems that are tailored to individual end-user needs. Our work is based on the fact that the majority of end-users are familiar with mobile devices and use an increasing number of mobile applications. A mobile tool enabling end-user led requirements elicitation could be just one of many applications installed on end-users' mobile devices. In this paper, we present a framework of end-user involvement in requirements elicitation which motivates our research. The main contribution of our research is a tool-supported requirements elicitation approach allowing end-users to document needs in situ. Furthermore, we present first evaluation results to highlight the feasibility of on-site end-user led requirements elicitation

A video life-world approach to consultation practice: The relevance of a socio-phenomenological approach

This article discusses the [development and] use of a video life-world schema to explore alternative orientations to the shared health consultation. It is anticipated that this schema can be used by practitioners and consumers alike to understand the dynamics of videoed health consultations, the role of the participants within it and the potential to consciously alter the outcome by altering behaviour during the process of interaction. The study examines health consultation participation and develops an interpretative method of analysis that includes image elicitation (via videos), phenomenology (to identify the components of the analytic framework), narrative (to depict the stories of interactions) and a reflexive mode (to develop shared meaning through a conceptual framework for analysis). The analytic framework is derived from a life-world conception of human mutual shared interaction which is presented here as a novel approach to understanding patient-centred care. The video materials used in this study were derived from consultations in a Walk-in Centre (WiC) in East London. The conceptual framework produced through the process of video analysis is comprised of different combinations of movement, knowledge and emotional conversations that are used to classify objective or engaged WiC health care interactions. The videoed interactions organise along an active or passive, facilitative or directive typical situation continuum illustrating different kinds of textual approaches to practice that are in tension or harmony. The schema demonstrates how practitioners and consumers interact to produce these outcomes and indicates the potential for both consumers and practitioners to be educated to develop practice dynamics that support patient-centred care and impact on health outcomes

Developing a Framework for Managing Tacit Knowledge in Research using Knowledge Management Models

This research investigates whether and how selected models from Knowledge Management (KM) can be used to devise a framework for building coherent and rigorous methodologies for research in the creative and practice-led disciplines (CPD). This research has arisen from methodological problems of research in art and design in the UK concerning how, and the extent to which, non-propositional and tacit kinds of knowledge (e.g. experiential, procedural) can be included and communicated within research. The proposed research builds on previous studies by the authors into the role and relationship of different kinds of knowledge in research (Niedderer, 2007a, 2007b), and into how knowledge management (KM) and creative disciplines provide complementary insights on how knowledge can be managed and transferred (Imani, 2007). The research investigates whether and how the SECI model (Nonaka &amp; Takeuchi, 1995; Nonaka, 2000) can be used to develop a framework for managing different kinds of knowledge in research. Our research goes beyond existing approaches by offering a generic and flexible framework which researchers can use to better understand and build their own research methodologies and to integrate individual methods with regard to managing different kinds of knowledge.</p

Using language technologies to support individual formative feedback

In modern educational environments for group learning it is often challenging for tutors to provide timely individual formative feedback to learners. Taking the case of undergraduate Medicine, we have found that formative feedback is generally provided to learners on an ad-hoc basis, usually at the group, rather than individual, level. Consequently, conceptual issues for individuals often remain undetected until summative assessment. In many subject domains, learners will typically produce written materials to record their study activities. One way for tutors to diagnose conceptual development issues for an individual learner would be to analyse the contents of the learning materials they produce, which would be a significant undertaking. CONSPECT is one of six core web-based services of the Language Technologies for Lifelong Learning (LTfLL) project. This European Union Framework 7-funded project seeks to make use of Language Technologies to provide semi-automated analysis of the large quantities of text generated by learners through the course of their learning. CONSPECT aims to provide formative feedback and monitoring of learners’ conceptual development. It uses a Natural Language Processing method, based on Latent Semantic Analysis, to compare learner materials to reference models generated from reference or learning materials. This paper provides a summary of the service development alongside results from validation of Version 1.0 of the service

Exploring the user experience through collage

We explore the use of collage in requirements elicitation, as a tool to support potential end-users in expressing their impressions, understanding, and emotions regarding a system

ACon: A learning-based approach to deal with uncertainty in contextual requirements at runtime

Context: Runtime uncertainty such as unpredictable operational environment and failure of sensors that gather environmental data is a well-known challenge for adaptive systems. Objective: To execute requirements that depend on context correctly, the system needs up-to-date knowledge about the context relevant to such requirements. Techniques to cope with uncertainty in contextual requirements are currently underrepresented. In this paper we present ACon (Adaptation of Contextual requirements), a data-mining approach to deal with runtime uncertainty affecting contextual requirements. Method: ACon uses feedback loops to maintain up-to-date knowledge about contextual requirements based on current context information in which contextual requirements are valid at runtime. Upon detecting that contextual requirements are affected by runtime uncertainty, ACon analyses and mines contextual data, to (re-)operationalize context and therefore update the information about contextual requirements. Results: We evaluate ACon in an empirical study of an activity scheduling system used by a crew of 4 rowers in a wild and unpredictable environment using a complex monitoring infrastructure. Our study focused on evaluating the data mining part of ACon and analysed the sensor data collected onboard from 46 sensors and 90,748 measurements per sensor. Conclusion: ACon is an important step in dealing with uncertainty affecting contextual requirements at runtime while considering end-user interaction. ACon supports systems in analysing the environment to adapt contextual requirements and complements existing requirements monitoring approaches by keeping the requirements monitoring specification up-to-date. Consequently, it avoids manual analysis that is usually costly in today’s complex system environments.Peer ReviewedPostprint (author's final draft