Automatic detection of nocuous coordination ambiguities in natural language requirements

Yang, Hui; Willis, Alistair; Roeck, Anne De; Nuseibeh, Bashar

doi:10.1145/1858996.1859007

Cited by 49 publications

(38 citation statements)

References 20 publications

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“…Nor is the study of ambiguity confined to the classroom. Active research continues on the use of tools for the detection of ambiguity 17 , the avoidance of ambiguity in major projects 18 , and the clarification of the intended functions of computer programs 15 .…”

Section: The Failure Of Code Descriptionsmentioning

confidence: 99%

The case for open computer programs

Ince

Hatton

Graham-Cumming³

2012

Nature

457

356

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Scientific communication relies on evidence that cannot be entirely included in publications, but the rise of computational science has added a new layer of inaccessibility. Although it is now accepted that data should be made available on request, the current regulations regarding the availability of software are inconsistent. We argue that, with some exceptions, anything less than the release of source programs is intolerable for results that depend on computation. The vagaries of hardware, software and natural language will always ensure that exact reproducibility remains uncertain, but withholding code increases the chances that efforts to reproduce results will fail.T he rise of computational science has led to unprecedented opportunities for scientific advance. Ever more powerful computers enable theories to be investigated that were thought almost intractable a decade ago, robust hardware technologies allow data collection in the most inhospitable environments, more data are collected, and an increasingly rich set of software tools are now available with which to analyse computer-generated data.However, there is the difficulty of reproducibility, by which we mean the reproduction of a scientific paper's central finding, rather than exact replication of each specific numerical result down to several decimal places. We examine the problem of reproducibility (for an early attempt at solving it, see ref. 1) in the context of openly available computer programs, or code. Our view is that we have reached the point that, with some exceptions, anything less than release of actual source code is an indefensible approach for any scientific results that depend on computation, because not releasing such code raises needless, and needlessly confusing, roadblocks to reproducibility.At present, debate rages on the need to release computer programs associated with scientific experiments 2-4 , with policies still ranging from mandatory total release to the release only of natural language descriptions, that is, written descriptions of computer program algorithms. Some journals have already changed their policies on computer program openness; Science, for example, now includes code in the list of items that should be supplied by an author 5 . Other journals promoting code availability include Geoscientific Model Development, which is devoted, at least in part, to model description and code publication, and Biostatistics, which has appointed an editor to assess the reproducibility of the software and data associated with an article 6 .In contrast, less stringent policies are exemplified by statements such as 7 ''Nature does not require authors to make code available, but we do expect a description detailed enough to allow others to write their own code to do similar analysis.'' Although Nature's broader policy states that ''...authors are required to make materials, data and associated protocols promptly available to readers...'', and editors and referees are fully empowered to demand and evaluate any specific code, we belie...

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Section: The Failure Of Code Descriptionsmentioning

confidence: 99%

The case for open computer programs

Ince

Hatton

Graham-Cumming³

2012

Nature

457

356

View full text Add to dashboard Cite

show abstract

“…Ambiguity in requirements sentence is a major problem because it leads to the poor quality of SRS documents (6). Additionally, the software errors increase during requirements phase because of requirements specification are ambiguous and errors in requirements are widespread, harmful and costly such that it can lead to lower quality of SRS documents (7).…”

Section: Motivationmentioning

confidence: 99%

An Analysis of Ambiguity Detection Techniques for Software Requirements Specification (SRS)

Oo¹,

Nordin²,

Ismail³

et al. 2018

IJET

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Ambiguity is the major problem in Software Requirements Specification (SRS) documents because most of the SRS documents are written in natural language and natural language is generally ambiguous. There are various types of techniques that have been used to detect ambiguity in SRS documents. Based on an analysis of the existing work, the ambiguity detection techniques can be categorized into three approaches: (1) manual approach, (2) semi-automatic approach using natural language processing, (3) semi-automatic approach using machine learning. Among them, one of the semi-automatic approaches that uses the Naïve Bayes (NB) text classification technique obtained high accuracy and performed effectively in detecting ambiguities in SRS.

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“…The work in this paper builds on Yang et al [56] which investigates the linguistic factors that contribute to the preference for particular readings, and demonstrates that the distinction between nocuous and innocuous ambiguity can be characterized precisely, and can be implemented in a computational model. The approach builds on previous work applied to requirements documents [9,54,57], which focused on coordination ambiguity shown in example E3 below:…”

Section: E2 Table Data Is Dumped Into a Delimited Text File Which Imentioning

confidence: 99%

Analysing anaphoric ambiguity in natural language requirements

et al. 2011

Self Cite

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Many requirements documents are written in natural language (NL). However, with the flexibility of NL comes the risk of introducing unwanted ambiguities in the requirements and misunderstandings between stakeholders. In this paper, we describe an automated approach to identify potentially nocuous ambiguity, which occurs when text is interpreted differently by different readers. We concentrate on anaphoric ambiguity, which occurs when readers may disagree on how pronouns should be interpreted.We describe a number of heuristics, each of which captures information that may lead a reader to favour a particular interpretation of the text. We use these heuristics to build a classifier, which in turn predicts the degree to which particular interpretations are preferred. We collected multiple human judgements on the interpretation of requirements exhibiting anaphoric ambiguity, and show how the distribution of these judgements can be used to assess whether a particular instance of ambiguity is nocuous. Given a requirements document written in natural language, our approach can identify sentences which contain anaphoric ambiguity, and use the classifier to alert the requirements writer of text that runs the risk of misinterpretation.We report on a series of experiments that we conducted to evaluate the performance of the automated system we developed to support our approach. The results show that the system achieves high recall with a consistent improvement on baseline precision subject to some ambiguity tolerance levels, allowing us to explore and highlight realistic and potentially problematic ambiguities in actual requirements documents.

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Automatic detection of nocuous coordination ambiguities in natural language requirements

Cited by 49 publications

References 20 publications

The case for open computer programs

The case for open computer programs

An Analysis of Ambiguity Detection Techniques for Software Requirements Specification (SRS)

Analysing anaphoric ambiguity in natural language requirements

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