iMER: Iterative process of entity relationship and business process model extraction from the requirements

Javed, Muhammad Awais; Lin, Yuqing

doi:10.1016/j.infsof.2021.106558

Cited by 7 publications

(8 citation statements)

References 21 publications

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“…The state of art approaches [13], [14] that are based on the same tool inputs as our approach, namely acceptance criteria, and user stories, focus mainly on test case generation. In [18] the BPMN generation was performed from textual requirements, as for the user stories, the approach just generates the BPMN operations. Moreover, they do not use acceptance criteria with user stories.…”

Section: Discussionmentioning

confidence: 99%

“…The use of NLP was essential to analyze the specifications. In [18] iterative approach of models extraction from the requirements (iMER) is developed to automatically generate the entity relationships model and business process model from text requirements and user stories. Their approach is made iterative in order to extract the component of each model.…”

Section: Methods 21 Related Workmentioning

confidence: 99%

“…13, No. 1, February 2023: 809-822 810 [18]. In [17], the UML activity diagram is generated automatically from natural language requirements.…”

Section: Introductionmentioning

confidence: 99%

“…The limitation of this work is that some controls like decision nodes and forks are not automated. In [18], the business process model is built automatically from unrestricted requirements, but by manipulating the agile requirements, the authors have only managed to generate the operations of the model, and their model is still incomplete. Moreover, they only process the user stories without taking into account the acceptance criteria.…”

Section: Introductionmentioning

confidence: 99%

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Automatic generation of business process models from user stories

Nasiri

Adadi

Lahmer

2023

IJECE

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In this paper, we propose an automated approach to extract business process models from requirements, which are presented as user stories. In agile software development, the user story is a simple description of the functionality of the software. It is presented from the user's point of view and is written in natural language. Acceptance criteria are a list of specifications on how a new software feature is expected to operate. Our approach analyzes a set of acceptance criteria accompanying the user story, in order, first, to automatically generate the components of the business model, and then to produce the business model as an activity diagram which is a unified modeling language (UML) behavioral diagram. We start with the use of natural language processing (NLP) techniques to extract the elements necessary to define the rules for retrieving artifacts from the business model. These rules are then developed in Prolog language and imported into Python code. The proposed approach was evaluated on a set of use cases using different performance measures. The results indicate that our method is capable of generating correct and accurate process models.

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Section: Discussionmentioning

confidence: 99%

Section: Methods 21 Related Workmentioning

confidence: 99%

“…13, No. 1, February 2023: 809-822 810 [18]. In [17], the UML activity diagram is generated automatically from natural language requirements.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Automatic generation of business process models from user stories

Nasiri

Adadi

Lahmer

2023

IJECE

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“…Manually extracting conceptual models is a time-consuming, error-prone task. The use of automated transformation aids in the preservation of requirement traceability [1]. One of the most difficult aspects of developing an automated ERM is the lack of complete natural language rules for mapping natural language requirements into an ERM [2].…”

Section: Introductionmentioning

confidence: 99%

Novel rules for extracting the entities of entity relationship models

Omar¹,

Alsheky²,

Faiz³

2021

JOPAS

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Extracting entities from natural language text to design conceptual models of the entity relationships is not trivial and novice designers and students can find it especially difficult. Researchers have suggested linguistic rules/guidelines for extracting entities from natural language text. Unfortunately, while these guidelines are often correct they can, also, be invalid. There is no rule that is true at all times. This paper suggests novel rules based on the machine learning classifiers, the RIPPER, the PART and the decision trees. Performance comparison was made between the linguistic and the machine learning rules. The results shows that there was a dramatic improvement when machine learning rules were used.

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Usefulness of open domain model for identifying missing software requirements concepts

Zhao,

Zhang,

Lian

2023

Softw Pract Exp

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SummaryDetecting missing requirements during software development is crucial to avoid unexpected consequences. However, this task is challenging due to limited domain knowledge of requirements analysts and the dynamic nature of software requirements. Previous studies have shown that requirement‐oriented domain models can help identify omissions in requirements, but they are often incomplete for many domains. Meanwhile, domain models constructed from other artifacts are available online. This raises the question: Can these domain models be useful in identifying missing functional information in requirement specifications? To address this question, we conducted a study to measure the overlap between entities in domain models and requirements. We analyzed the occurrence of overlapped entities, considering four distribution characteristics: the type of entities in the domain model, the distribution of mapped entities in the domain model, the family belonging of the mapped entities in the domain model, and the distribution of mapped entities in the requirements. Based on our findings, we proposed recommendations for missing requirements. Additionally, we performed experiments, including the use of the proposed metric “ancestors of the highest level with the most mapped entities” (AHME). The results showed significant improvements with gains of 146% and 223% in the two domains, highlighting the benefits of these distribution characteristics.

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iMER: Iterative process of entity relationship and business process model extraction from the requirements

Cited by 7 publications

References 21 publications

Automatic generation of business process models from user stories

Automatic generation of business process models from user stories

Novel rules for extracting the entities of entity relationship models

Usefulness of open domain model for identifying missing software requirements concepts

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