The Legacy of Stefania Gnesi

Beek, Maurice H. ter; Fantechi, Alessandro; Semini, Laura

doi:10.1007/978-3-030-30985-5_1

Cited by 2 publications

(3 citation statements)

References 56 publications

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“…Therefore, these authors suggested a framework with 13 quality points that should be followed to fulfill a good user story. Based on these frameworks, some commercial tools such as AQUSA [14] and QUARS [19] use NLP to analyze user stories and determine some errors in the writing and are capable of detecting problems from the three approaches syntactic, semantic, and pragmatic.…”

Section: Introductionmentioning

confidence: 99%

“…After the framework's creation effort, several authors and developers implemented pricing tools to evaluate the user's story quality [2], such as Quality Analyzer for Requirements Specifications (QUARS) [19], which is considered a pioneer tool for Natural Language Requirement Analysis with a management tool to analyze linguistic defects in it better. Another tool is Automatic Quality User Story Artisan (AQUSA), which analyzes user stories and provides a sample of results and conclusions from their experiments using Natural Language Processing (NLP) techniques [14].…”

Section: Introductionmentioning

confidence: 99%

“…For that reason, it is essential to ensure the quality of these Scrum artifacts. Several authors [12, 19] attempted to propose a framework to evaluate the quality of these sentences; the most recent and popular framework is the QUS framework [12]. The framework has 14 elements for the user stories evaluation.…”

Section: Introductionmentioning

confidence: 99%

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USQA: A User Story Quality Analyzer prototype for supporting software engineering students

Jiménez¹,

Alanis

Beltrán

et al. 2023

Comp Applic In Engineering

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The Standish Group Reports 83.9% of IT Projects fail, and one of the top factors in failed projects is the incomplete requirements or user stories. Therefore, it is essential to teach undergraduate students from computer science degree programs how to create complete user stories. Computer science programs include some subjects or topics involving requirements or user stories collection and writing, such as Requirements Engineering, Software Engineering, Project Management, or Quality Software Assurance. For that reason, we designed a web application called User Story Quality Analyzer (USQA) that uses Natural Language Processing modules to detect errors regarding aspects of usefulness, completeness, and polysemes in the user stories creation. The tool was proved from three perspectives: (1) a reliability test, where 35 user stories developed by experts were tested in the app to prove the prototype's reliability; (2) usability and utility analysis; 48 students interacted with the tool and responded a Satisfaction Usability Scale and an open‐ended question, the students reported a high usability score; (3) finally, error classification, we gathered 159 user stories processed by the system, and we classified the students' common errors considering incompleteness and polysemes. After the evaluations, we concluded that USQA could evaluate the user stories as an expert, which could help the professors/teachers/instructors in their courses by providing feedback to the students when they are writing user stories.

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Section: Introductionmentioning

confidence: 99%