Extracting goal models from natural language requirement specifications

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A4NBERR8W" target="_blank" >RIV/00216208:11320/25:4NBERR8W - isvavai.cz</a>

Výsledek na webu

<a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183944895&doi=10.1016%2fj.jss.2024.111981&partnerID=40&md5=5220552ecc6625a20d7da191f7df3e0c" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85183944895&doi=10.1016%2fj.jss.2024.111981&partnerID=40&md5=5220552ecc6625a20d7da191f7df3e0c</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jss.2024.111981" target="_blank" >10.1016/j.jss.2024.111981</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Extracting goal models from natural language requirement specifications

Popis výsledku v původním jazyce

Unstructured (or, semi-structured) natural language is mostly used to capture the requirement specifications both for legacy software systems and for modern day software systems. The adoption of a formal approach to the specification of the requirements, using goal models, enables rigorous and formal inspections while analyzing the requirements for satisfiability, consistency, completeness, conflicts and ambiguities. However, such a formal approach is often considered burdening for the analysts’ activity as it requires additional skills, and is therefore, discarded a priori. This works aims to bridge the gap between natural language requirement specifications and efficient goal model analysis techniques. We propose a framework that uses extensive natural language processing techniques to transform a set of unstructured natural language requirement specifications to the corresponding goal model. We combine techniques such as parts-of-speech tagging, dependency parsing, contextual and synonymy vector generation with the FiBER transformer model. An extensive unbiased crowd-sourced evaluation of the proposed framework has been performed, showing an acceptability rate (total and partial combined) of 95%. Time and space analyses of our framework also demonstrate the scalability of the proposed solution. © 2024 The Author(s)

Název v anglickém jazyce

Extracting goal models from natural language requirement specifications

Popis výsledku anglicky

Unstructured (or, semi-structured) natural language is mostly used to capture the requirement specifications both for legacy software systems and for modern day software systems. The adoption of a formal approach to the specification of the requirements, using goal models, enables rigorous and formal inspections while analyzing the requirements for satisfiability, consistency, completeness, conflicts and ambiguities. However, such a formal approach is often considered burdening for the analysts’ activity as it requires additional skills, and is therefore, discarded a priori. This works aims to bridge the gap between natural language requirement specifications and efficient goal model analysis techniques. We propose a framework that uses extensive natural language processing techniques to transform a set of unstructured natural language requirement specifications to the corresponding goal model. We combine techniques such as parts-of-speech tagging, dependency parsing, contextual and synonymy vector generation with the FiBER transformer model. An extensive unbiased crowd-sourced evaluation of the proposed framework has been performed, showing an acceptability rate (total and partial combined) of 95%. Time and space analyses of our framework also demonstrate the scalability of the proposed solution. © 2024 The Author(s)

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Systems and Software

ISSN

0164-1212

e-ISSN

—

Svazek periodika

211

Číslo periodika v rámci svazku

2024

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

21

Strana od-do

2-22

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85183944895