1,655 research outputs found

    NL-based automated software requirements elicitation and specification

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    This paper presents a novel approach to automate the process of software requirements elicitation and specification. The software requirements elicitation is perhaps the most important phase of software development as a small error at this stage can result in absurd software designs and implementations. The automation of the initial phase (such as requirement elicitation) phase can also contribute to a long standing challenge of automated software development. The presented approach is based on Semantic of Business Vocabulary and Rules (SBVR), an OMG’s recent standard. We have also developed a prototype tool SR-Elicitor (an Eclipse plugin), which can be used by software engineers to record and automatically transform the natural language software requirements to SBVR software requirements specification. The major contribution of the presented research is to demonstrate the potential of SBVR based approach, implemented in a prototype tool, proposed to improve the process of requirements elicitation and specification

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

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    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

    Generating natural language specifications from UML class diagrams

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    Early phases of software development are known to be problematic, difficult to manage and errors occurring during these phases are expensive to correct. Many systems have been developed to aid the transition from informal Natural Language requirements to semistructured or formal specifications. Furthermore, consistency checking is seen by many software engineers as the solution to reduce the number of errors occurring during the software development life cycle and allow early verification and validation of software systems. However, this is confined to the models developed during analysis and design and fails to include the early Natural Language requirements. This excludes proper user involvement and creates a gap between the original requirements and the updated and modified models and implementations of the system. To improve this process, we propose a system that generates Natural Language specifications from UML class diagrams. We first investigate the variation of the input language used in naming the components of a class diagram based on the study of a large number of examples from the literature and then develop rules for removing ambiguities in the subset of Natural Language used within UML. We use WordNet,a linguistic ontology, to disambiguate the lexical structures of the UML string names and generate semantically sound sentences. Our system is developed in Java and is tested on an independent though academic case study

    Bridging the Gap Between Requirements and Simulink Model Analysis

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    Formal verification and simulation are powerful tools for the verification of requirements against complex systems. Requirements are developed in early stages of the software lifecycle and are typically expressed in natural language. There is a gap between such requirements and their software implementations.We present a framework that bridges this gap by supporting a tight integration and feedback loop between high-level requirements and their analysis against software artifacts. Our framework implements an analysis portal within the fret requirements elicitation tool, thus forming an end-to-end, open-source environment where requirements are written in an intuitive, structured natural language, and are verified automatically against Simulink models

    LadderBot: A requirements self-elicitation system

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    Digital transformation impacts an ever-increasing amount of everyone’s business and private life. It is imperative to incorporate user requirements in the development process to design successful information systems (IS). Hence, requirements elicitation (RE) is increasingly performed by users that are novices at contributing requirements to IS development projects. [Objective] We need to develop RE systems that are capable of assisting a wide audience of users in communicating their needs and requirements. Prominent methods, such as elicitation interviews, are challenging to apply in such a context, as time and location constraints limit potential audiences. [Research Method] We present the prototypical self-elicitation system “LadderBot”. A conversational agent (CA) enables end-users to articulate needs and requirements on the grounds of the laddering method. The CA mimics a human (expert) interviewer’s capability to rephrase questions and provide assistance in the process. An experimental study is proposed to evaluate LadderBot against an established questionnaire-based laddering approach. [Contribution] This work-in-progress introduces the chatbot LadderBot as a tool to guide novice users during requirements self-elicitation using the laddering technique. Furthermore, we present the design of an experimental study and outline the next steps and a vision for the future

    Data-driven agile requirements elicitation through the lenses of situational method engineering

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    Ubiquitous digitalization has led to the continuous generation of large amounts of digital data, both in organizations and in society at large. In the requirements engineering community, there has been a growing interest in considering digital data as new sources for requirements elicitation, in addition to stake-holders. The volume, dynamics, and variety of data makes iterative requirements elicitation increasingly continuous, but also unstructured and complex, which current agile methods are unable to consider and manage in a systematic and efficient manner. There is also the need to support software evolution by enabling a synergy of stakeholder-driven requirements elicitation and management with data-driven approaches. In this study, we propose extension of agile requirements elicitation by applying situational method engineering. The research is grounded on two studies in the business domains of video games and online banking.The work presented in this paper is partially funded by the DOGO4ML Spanish research project, PID2020-117191RB-I00.Peer ReviewedPostprint (author's final draft
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