NLARE, a natural language processing tool for automatic requirements evaluation

Huertas, Carlos; Juárez‐Ramírez, Reyes

doi:10.1145/2381716.2381786

Cited by 21 publications

(11 citation statements)

References 14 publications

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“…We here want to draw attention to three solutions as we describe them in more detail for a better understanding. These tools are NLARE (Natural Language Automatic Requirement Evaluator) [23,32], RESI [33] and CORDULA (Compensation of Requirements Descriptions Using Linguistic Analysis) [19]. Furthermore, we highlight the discrepancies here.…”

Section: Multiple Inaccuracy Detection and Compensationmentioning

confidence: 97%

“…In literature, the idea of combining different approaches for inaccuracy detection or compensation was investigated. Ambiguity and incompleteness together were covered (e.g., [22][23][24]) as well as ambiguity only (e.g., [25,26]). Furthermore, there are researchers giving an overview over disambiguation methods in the domain of NL software requirements [27,28].…”

Section: Multiple Inaccuracy Detection and Compensationmentioning

confidence: 99%

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Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches

2019

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The vision of On-the-Fly (OTF) Computing is to compose and provide software services ad hoc, based on requirement descriptions in natural language. Since non-technical users write their software requirements themselves and in unrestricted natural language, deficits occur such as inaccuracy and incompleteness. These deficits are usually met by natural language processing methods, which have to face special challenges in OTF Computing because maximum automation is the goal. In this paper, we present current automatic approaches for solving inaccuracies and incompletenesses in natural language requirement descriptions and elaborate open challenges. In particular, we will discuss the necessity of domain-specific resources and show why, despite far-reaching automation, an intelligent and guided integration of end users into the compensation process is required. In this context, we present our idea of a chat bot that integrates users into the compensation process depending on the given circumstances.

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Section: Multiple Inaccuracy Detection and Compensationmentioning

confidence: 97%

Section: Multiple Inaccuracy Detection and Compensationmentioning

confidence: 99%

Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches

2019

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“…lexical ambiguity), there are other approaches that can identify and resolve several deficits in requirements descriptions. Even mixed techniques exist that can detect different forms of ambiguity [8,9] or, for example, ambiguity together with incompleteness [10,11,12]. An overview of existing approaches on disambiguation in the context of NL requirements is given by Husain and Beg [13] as well as Shah and Jinwala [14].…”

Section: Current State Of Researchmentioning

confidence: 99%

“…Huertas and Juarez-Raminez [11,22] introduce NLARE, a combined approach that concentrates on functional requirements and recognizes ambiguity, incompleteness and "atomism". The authors define ambiguity as gradable adjectives.…”

Section: Current State Of Researchmentioning

confidence: 99%

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Flexible Ambiguity Resolution and Incompleteness Detection in Requirements Descriptions via an Indicator-Based Configuration of Text Analysis Pipelines

Bäumer¹,

Geierhos²

2018

Proceedings of the 51st Hawaii International Conference on System Sciences

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Naturallanguage software requirements descriptions enable end users to formulate their wishes and expectations for a future software product without much prior knowledge in requirements engineering. However, these descriptions are susceptible to linguistic inaccuracies such as ambiguities and incompleteness that can harm the development process. There is a number of software solutions that can detect deficits in requirements descriptions and partially solve them, but they are often hard to use and not suitable for end users. For this reason, we develop a software system that helps end-users to create unambiguous and complete requirements descriptions by combining existing expert tools and controlling them using automatic compensation strategies.In order to recognize the necessity of individual compensation methods in the descriptions, we have developed linguistic indicators, which we present in this paper. Based on these indicators, the whole text analysis pipeline is ad-hoc configured and thus adapted to the individual circumstances of a requirements description.

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Improving the Requirement Engineering Process with Speed-Reviews: An Industrial Case Study

Pekar

Felderer

Breu

et al. 2015

Lecture Notes in Business Information Processing

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NLARE, a natural language processing tool for automatic requirements evaluation

Cited by 21 publications

References 14 publications

Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches

Natural Language Processing in OTF Computing: Challenges and the Need for Interactive Approaches

Flexible Ambiguity Resolution and Incompleteness Detection in Requirements Descriptions via an Indicator-Based Configuration of Text Analysis Pipelines

Improving the Requirement Engineering Process with Speed-Reviews: An Industrial Case Study

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