Detecting Feature Duplication in Natural Language Specifications when Evolving Software Product Lines

Khtira, Amal; Benlarabi, Anissa; Asri, Bouchra El

doi:10.5220/0005459802570262

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…Instead of Jaccard's similarity, other works [19] [13] rely on cosine similarity. And some other defines their own method [30][2][20] [9].…”

Section: Related Workmentioning

confidence: 99%

An Approach to Cluster Scenarios According to Their Similarity Using Natural Language Processing

Delle Ville,

Torres,

Fernández

et al. 2024

Communications in Computer and Information Science

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Scenarios are ideal to capture knowledge in human computer interface software engineering. Requirements engineering is a fundamental part of software development. If errors appear in this stage, it will be expensive to correct them in further stages. The domain experts and the developer team belong to different worlds. This generates a gap in communication between them. Because of it, it is important to use artifacts in natural language to communicate both sides. One simpler approach to specify requirements is Scenarios. They are widely used artifacts that generally describe the dynamics (tasks, activities) to be carried out in some specific situation. Generally, scenarios promote communication and participation from both sides. This can cause some problems. One of these problems is redundancy, that occurs when two stakeholders describe the same situation in different artifacts. This paper proposes an approach to analyze a set of scenarios by grouping them according to their similarity. The similarity is calculated through a series of comparisons of the different attributes of the scenario. This paper also describes a prototype implementing this method. Finally, the paper shows the result of a preliminary evaluation with results about the applicability of the approach.

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“…Instead of Jaccard's similarity, other works [19] [13] rely on cosine similarity. And some other defines their own method [30][2][20] [9].…”

Section: Related Workmentioning

confidence: 99%

An Approach to Cluster Scenarios According to Their Similarity Using Natural Language Processing

Delle Ville,

Torres,

Fernández

et al. 2024

Communications in Computer and Information Science

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show abstract

“…First, we generate the XML source of the feature model using FeatureIDE [24], and then we use some mapping rules to create a variability-based tree structure. As regard specifications, we adopt an approach based on natural language processing by analyzing syntactically and semantically the specification sentences in order to extract the potential variation points and variants [25]. The repository of variants created from the product line general specification must be constantly updated by new evolutions to improve the activity of variant detection.…”

Section: The Deduplication Frameworkmentioning

confidence: 99%

Detecting Feature Duplication in a CRM Product Line

Khtira¹

2020

JSW

Self Cite

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Many defects may arise during software product lines such as inconsistency, incorrectness and ambiguity. In our work, we are interested in a specific defect, which is duplication in features since it has received little attention in literature. In previous work, we proposed a conceptual framework that describes the different processes to follow in order to produce duplication-free feature models. We also implemented a tool support called FDDetector based on this framework with the aim of detecting and correcting duplication introduced in feature models by new product line evolutions. To evaluate this tool, we have adopted a CRM product line as a case study. In this paper, we explain the motivations behind choosing a case study from the CRM field, and we present the results of a test performed on an evolution related to this product line.

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“…If any sentence having some missing information. It will considered as Syntax ambiguty [29]. For example, in line 6 sentence marked as syntax ambiguty due to word "both" and denoted in blue color.…”

Section: Step 1: Read the Nl Srs Document (That Is To Be Tested) Linementioning

confidence: 99%

Algorithm for Automatic Detection of Ambiguities from Software Requirements

2019

IJITEE

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Software Systems are built by the Software engineers and must ensure that software requirement document (SRS) should be specific. Natural Language is the main representation of Software requirement specification document, because it is the most flexible and easiest way for clients or customers to express their software requirements [2]. However being stated in natural language, software requirement specification document may lead to ambiguities [28]. The main goal of presented work to automatically detection of the different types of ambiguities like Lexical, Syntactic, Syntax and Pragmatic. Then an algorithm is proposed to early detection the different types of ambiguities from software requirement document. Part of Speech (POS) technique and regular expression is used to detect each type of ambiguities. An algorithm presented in this paper have two main goals (1) Automatic detection of different types of ambiguities. (2) Count the total number of each types of ambiguities found and evaluate the percentage of ambiguous and non- ambiguous statements detected from software requirement document. The suggested algorithm can absolutely support the analyst in identifying different kinds of ambiguities in Software requirements specification (SRS) document.

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Detecting Feature Duplication in Natural Language Specifications when Evolving Software Product Lines

Cited by 5 publications

References 13 publications

An Approach to Cluster Scenarios According to Their Similarity Using Natural Language Processing

An Approach to Cluster Scenarios According to Their Similarity Using Natural Language Processing

Detecting Feature Duplication in a CRM Product Line

Algorithm for Automatic Detection of Ambiguities from Software Requirements

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