Detecting terminological ambiguity in user stories: Tool and experimentation

Dalpiaz, Fabiano; Schalk, Ivor van der; Brinkkemper, Sjaak; Aydemir, Fatma Başak; Lucassen, Garm

doi:10.1016/j.infsof.2018.12.007

Cited by 58 publications

(30 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In general, this work offers numerous opportunities for research that combines NLP and information visualization in RE; for another example of such synergy, see our work on terminological ambiguity [6]. In order for automated techniques to become useful for practitioners, the results of automation have to be turned into requirements analytics tools [26] that are built for use by human analysts.…”

Section: Discussion and Future Workmentioning

confidence: 99%

RE-SWOT: From User Feedback to Requirements via Competitor Analysis

Dalpiaz

Parente²

2019

Requirements Engineering: Foundation for Software Quality

Self Cite

View full text Add to dashboard Cite

Context & Motivation] App store reviews are a rich source for analysts to elicit requirements from user feedback, for they describe bugs to be fixed, requested features, and possible improvements. Product development teams need new techniques that help them make real-time decisions based on user feedback. [Question/Problem] Researchers have proposed natural language processing (NLP) techniques for extracting and organizing requirements-relevant knowledge from the reviews for one specific app. However, no attention has been paid to studying whether and how requirements can be identified from competing products. [Principal ideas/results] We propose RE-SWOT, a tool-supported method for eliciting requirements from app store reviews through competitor analysis. RE-SWOT combines NLP algorithms with information visualization techniques. We evaluate the usefulness of RE-SWOT with expert product managers from three mobile app companies.[Contribution] Our preliminary results show that competitor analysis is a promising path for research that has direct impact on the requirements engineering practice in modern app development companies.

show abstract

Section: Discussion and Future Workmentioning

confidence: 99%

RE-SWOT: From User Feedback to Requirements via Competitor Analysis

Dalpiaz

Parente²

2019

Requirements Engineering: Foundation for Software Quality

Self Cite

View full text Add to dashboard Cite

show abstract

“…Some studies were authored/co-authored by the same person, indicating the existence of an active research group in this field. [33] Identify ambiguous user stories [34] Define and measure quality factors from user stories [4], [35] Obtain a security defect reporting form from user stories [36] Indicate duplication between user stories [37] Generate model/artifact Generate a test case from user stories [38]- [43] Generate a class diagram from user stories [44], [45] Generate a sequence diagram from user stories [46] Generate a use case diagram from user stories [47]- [49] Generate a use case scenario from user stories [50] Generate a multi-agent system from user stories [51] Generate a source code from user stories [40] Generate a BPMN diagram from user stories [40] Identify the key abstractions To understand the semantic connection in user stories [52]- [54] Identify topics and summarizing user stories [55], [56] Construct a goal model from a set of user stories. [57] Define ontology for user stories [58] Extract the conceptual model of user stories [59], [60] To find the linguistic structure of user stories [61] Prioritizing and estimation of user story complexity [62], [63] Extracting user stories from text [64]- [66] Trace links between model/NL requirements Tracking the development status of user stories from software artifacts [67] Identify the type of dependency of user stories [68] Traceability user stories and software artifact [69]…”

Section: Fig 4 Authorship Distribution Per Countrymentioning

confidence: 99%

User Stories and Natural Language Processing: A Systematic Literature Review

2021

View full text Add to dashboard Cite

User stories have been widely accepted as artifacts to capture the user requirements in agile software development. They are short pieces of texts in a semi-structured format that express requirements. Natural language processing (NLP) techniques offer a potential advantage in user story applications. Objective: Conduct a systematic literature review to capture the current state-of-the-art of NLP research on user stories. Method: The search strategy is used to obtain relevant papers from SCOPUS, ScienceDirect, IEEE Xplore, ACM Digital Library, SpringerLink, and Google Scholar. Inclusion and exclusion criteria are applied to filter the search results. We also use the forward and backward snowballing techniques to obtain more comprehensive results. Results: The search results identified 718 papers published between January 2009 to December 2020. After applying the inclusion/exclusion criteria and the snowballing technique, we identified 38 primary studies that discuss NLP techniques in user stories. Most studies used NLP techniques to extract aspects of who, what, and why from user stories. The purpose of NLP studies in user stories is broad, ranging from discovering defects, generating software artifacts, identifying the key abstraction of user stories, and tracing links between model and user stories. Conclusion: NLP can help system analysts manage user stories. Implementing NLP in user stories has many opportunities and challenges. Considering the exploration of NLP techniques and rigorous evaluation methods is required to obtain quality research. As with NLP research in general, the ability to understand a sentence's context continues to be a challenge.

show abstract

“…Automatic: Combine scores computed from translations in different languages using BabelNet F. Dalpiaz [24] user stories near-synonyms terms Automatic: calculate the similarity between terms then between their context using Cortical. or [20] which combined various features to recover requirement-to-code links.…”

Section: Homonyms and Synonyms Termsmentioning

confidence: 99%

“…To find word with similar senses, they used a graph-based multilingual joint approach based on the multilingual knowledge base BabelNet [22] with XMeans clustering [23]. F. Dalpiaz [24] try to detect terminological ambiguity in user stories by calculating the similarity between terms then between their context. For this reason, Cortical.io [25] is used, which is considered as a very powerful AI-based tool, with a high processing speed.…”

Section: Homonyms and Synonyms Termsmentioning

confidence: 99%

“…It can be concluded that, there is no single agreed method to extract synonyms from text which is valid for all goals; but we are facing a non-trivial task that differs depending on the objective and context. In the end, despite the divergence in their area of application, the last approach [24] remains the closest to ours, as it extracts nouns automatically from a set of sentences, before calculating the similarity by taking the context into consideration. While our approach deals with textual BR statements having no standard format and uses heuristics to improve the accuracy of identified synonyms.…”

Section: Homonyms and Synonyms Termsmentioning

confidence: 99%

See 1 more Smart Citation

Automated Identification of Semantic Similarity between Concepts of Textual Business Rules

Haj¹,

Balouki²,

Gadi³

2021

IJIES

View full text Add to dashboard Cite

Business Rules (BR) are usually written by different stakeholders, which makes them vulnerable to contain different designations for a same concept. Such problem can be the source of a not well orchestrated behaviors. Whereas identification of synonyms is manual or totally neglected in most approaches dealing with natural language Business Rules. In this paper, we present an automated approach to identify semantic similarity between terms in textual BR using Natural Language Processing and knowledge-based algorithm refined using heuristics. Our method is unique in that it also identifies abbreviations/expansions (as a special case of synonym) which is not possible using a dictionary. Then, results are saved in a standard format (SBVR) for reusability purposes. Our approach was applied on more than 160 BR statements divided on three cases with an accuracy between 69% and 87% which suggests it to be an indispensable enhancement for other methods dealing with textual BR.

show abstract

Detecting terminological ambiguity in user stories: Tool and experimentation

Cited by 58 publications

References 36 publications

RE-SWOT: From User Feedback to Requirements via Competitor Analysis

RE-SWOT: From User Feedback to Requirements via Competitor Analysis

User Stories and Natural Language Processing: A Systematic Literature Review

Automated Identification of Semantic Similarity between Concepts of Textual Business Rules

Contact Info

Product

Resources

About