2018 5th International Workshop on Artificial Intelligence for Requirements Engineering (AIRE)

21-21 Aug. 2018

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  • [Title page i]

    Publication Year: 2018, Page(s): 1
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  • [Title page iii]

    Publication Year: 2018, Page(s): 2
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  • [Copyright notice]

    Publication Year: 2018, Page(s): 3
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  • Table of Contents

    Publication Year: 2018, Page(s):4 - 5
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  • Welcome from the Organizers

    Publication Year: 2018, Page(s): 6
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  • Domain Knowledge Discovery Guided by Software Trace Links

    Publication Year: 2018, Page(s):1 - 7
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (540 KB) | HTML iconHTML

    Software-intensive projects are specified and modeled using domain terminology. Knowledge of the domain terminology is necessary for performing many Software Engineering tasks such as impact analysis, compliance verification, and safety certification. However, discovering domain terminology and reasoning about their interrelationships for highly technical software and system engineering domains is... View full abstract»

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

    Publication Year: 2018, Page(s):8 - 14
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (853 KB) | HTML iconHTML

    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 to... View full abstract»

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  • User Feedback from Tweets vs App Store Reviews: An Exploratory Study of Frequency, Timing and Content

    Publication Year: 2018, Page(s):15 - 21
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (308 KB) | HTML iconHTML

    Context: User feedback on apps is essential for gauging market needs and maintaining a competitive edge in the mobile apps development industry. App Store Reviews have been a primary resource for this feedback, however, recent studies have observed that Twitter is another potentially valuable source for this information. Objective: The objective of this study is to assess user feedback from Twitte... View full abstract»

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  • Extraction of Natural Language Requirements from Breach Reports Using Event Inference

    Publication Year: 2018, Page(s):22 - 28
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (146 KB) | HTML iconHTML

    We address the problem of extracting useful information contained in security and privacy breach reports. A breach report tells a short story describing how a breach happened and the follow-up remedial actions taken by the responsible parties. By predicting sentences that may follow a breach description using natural language processing, our goal is to suggest security and privacy requirements for... View full abstract»

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  • Crowdsourcing Software Development: Silver Bullet or Lead Balloon

    Publication Year: 2018, Page(s):29 - 30
    Cited by:  Papers (1)
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (345 KB) | HTML iconHTML

    Crowdsourcing is emerging as an alternative outsourcing strategy which is gaining increasing attention in the software engineering community. However, crowdsourcing software development involves complex tasks which differ significantly from the micro-tasks that can be found on crowdsourcing platforms such as Amazon Mechanical Turk - the latter are much shorter in duration, and typically very simpl... View full abstract»

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  • Identification of Cross-Domain Ambiguity with Language Models

    Publication Year: 2018, Page(s):31 - 38
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (282 KB) | HTML iconHTML

    During requirements elicitation, different stakeholders with diverse backgrounds and skills need to effectively communicate to reach a shared understanding of the problem at hand. Linguistic ambiguity due to terminological discrepancies may occur between stakeholders that belong to different technical domains. If not properly addressed, ambiguity can create frustration and distrust during requirem... View full abstract»

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  • Validating Goal Models via Bayesian Networks

    Publication Year: 2018, Page(s):39 - 46
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (319 KB) | HTML iconHTML

    Goal models are an example of requirement modeling language that has been applied to support the runtime monitoring and diagnosis of software systems and to steer self-adaptive systems. When creating a goal model, requirement engineers make assumptions concerning how the goals relate to each other and when they should be considered as satisfied. In dynamic environments, however, the assumptions ma... View full abstract»

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  • Crowd-Informed Goal Models

    Publication Year: 2018, Page(s):47 - 53
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (236 KB) | HTML iconHTML

    A topic of recent interest is how to apply crowdsourced information toward producing better software requirements. A research question that has received little attention so far is how to leverage crowdsourced information toward creating better-informed models of requirements. In this paper, we contribute a method following which information in online discussions may be leveraged toward constructin... View full abstract»

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  • Finding Component State Transition Model Elements Using Neural Networks: An Empirical Study

    Publication Year: 2018, Page(s):54 - 61
    Request permission for reuse | Click to expandAbstract | PDF file iconPDF (276 KB) | HTML iconHTML

    Use cases are popular for writing specifications of a system. However, despite their semi-structured nature, it is often time consuming and error-prone to generate component state transition diagrams from use case documents as it is done manually. While attempts to automate model generation from requirements have increased with the advent of deep neural networks (DNNs), there are limited studies i... View full abstract»

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  • Author index

    Publication Year: 2018, Page(s): 63
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