Modeling user story completion of an agile software process

Houston, Dan; Buettner, Douglas J.

doi:10.1145/2486046.2486063

Cited by 4 publications

(4 citation statements)

References 30 publications

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“…Usually, all the user stories and functional requirements are documented or expressed in natural language. Natural language processing (NLP) techniques are used to analyze these criteria, allowing for linguistic analysis and providing automated support [17]. Elallaoui also describes that Natural Language Processing (NLP) and Software Engineering (SE) are considered subfields of computer science.…”

Section: Related Workmentioning

confidence: 99%

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A Comparison of Transforming the User Stories and Functional Requirements into UML Use Case Diagram

Molla,

Ahmad,

Wan Kadir

2024

Int J Innov Comp

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Software development life cycle is a continuous process for every developer community, including establishing the user requirements and system design until software maintenance. The system design phase contains the transformation of all-natural language requirements into models. The Unified Modelling Language (UML) use case model is regarded as one of the most helpful diagrams for a software developer to understand the higher version of the software blueprint. It’s very useful to reflects the business requirements for any proposed software system. Manual analysis requires significant time and effort, highlighting the need for automated assistance. This study aims to enhance the machine learning techniques that have been utilized to transform user stories and functional requirements into a UML use case diagram. This research also investigate the use of an automated Natural Language Processing (NLP) tool and framework for mapping use case diagram elements from user stories and functional requirements written in natural languages. The proposed approach using a NLP based machine learning framework called BERT to predict and extract actors, use cases, and the relationship between actors and use cases. This approach has been applicable for both user stories and functional requirements. A dataset has been pre-processed in order to train this model and collected from various sources like Kaggle, software projects. There are 11 user stories and 11 functional requirements were selected to test the proposed solution. The data set from benchmark repositories. The extracted results during the whole NLP process are then mapped into actors, use cases, and relationships. This study was evaluated using both accuracy and precision values for performance measures. By applying NLP technologies, this research offers complete support for extracting elements and generating a use case diagram and revealed the 88% accuracy and 88% precision.

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Section: Related Workmentioning

confidence: 99%

“…They also discussed the compatibility issues between user stories and use cases. Another author addressed the model transformation from Computational Independent Model (CIM) model into a Platform Independent Model (PIM), where the CIM model is specified by the Use case diagram [17].…”

Section: Related Workmentioning

confidence: 99%

A Comparison of Transforming the User Stories and Functional Requirements into UML Use Case Diagram

Molla,

Ahmad,

Wan Kadir

2024

Int J Innov Comp

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“…Additionally, we searched for simulation studies in the main conference (ICSSP 3 ) and journal (SPIP, 4 including its new title JSEP), applying the same criteria from the qSLR. We found seven other simulation studies(Al-Emran et al 2010;Birkhölzer et al 2010;Houston and Lieu 2010;Bai et al 2012;Paikari et al 2012;Concas et al 2013;Houston and Buettner 2013) in these venues.…”

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confidence: 90%

“…For instance, in Fig. 5, the report made by (Houston and Buettner 2013) has a comprehensive description of the simulation model (SG8, SG9 and SG10) and also a good amount of information regarding the experimental design (from SG12 to SG17). The authors report what seems to be a case study supported by a discrete-event simulation model to investigate sources of variation in deliveries and how to improve delivery quality of an agile software project, where both the customer and the contractor had become concerned with the lack of predictability in contractor deliveries, in the Aerospace Corporation.…”

Section: Analysis Against the Technical Literaturementioning

confidence: 99%

Experimentation with dynamic simulation models in software engineering: planning and reporting guidelines

França

Travassos

2015

Empir Software Eng

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Simulation-based studies (SBS) have become an interesting investigation approach for Software Engineering (SE). However, the reports on experiments with dynamic simulation models found in the technical literature lack relevant information, hampering the full understanding of the procedures and results reported, as well as their replicability. Apart from the limitations on the length in conferences and journal papers, some of the relevant information seems to be missing due to methodological issues not considered when conducting such studies. This is the case of missing research questions and goals, lack of evidence regarding the dynamic simulation model validity, poorly designed simulation experiments, amongst others. Based on findings from a previous quasi-systematic literature review, we propose a set of reporting guidelines for SBS with dynamic models in the context of SE aiming at providing guidance on which information the report should contain. Furthermore, these guidelines were evolved to support SBS planning by identifying potential threats to simulation study validity and in making recommendations to avoid them, through qualitative analysis and external evaluation. Finally, we conducted different evaluations regarding both the reporting and planning guidelines, apart from using them to support the planning of a SBS as regards software evolution. A set of 33 reporting and planning guidelines for different stages of the simulation lifecycle and focused on the experimentation with dynamic simulation models have been put together. The first assessments point to a comprehensive set of guidelines, supporting a comprehensive preparation and review of the plans and reports from the studies, apart from the planning of a SBS focused on software evolution, potentially reducing the threats to the experimentation with the validity of dynamic simulation models. The 33 guidelines cannot be understood as separate groups for reporting and planning as they overlap in many aspects. The Empir Software Eng main goal is to use the guidelines to support the planning of a simulation-based study with dynamic models so that experimenters may identify potential threats to validity and produce relevant information for a complete simulation experiment report in advance. Despite their initial contribution to increase the validity of SBS, the reporting and planning of simulationbased experiments with dynamic models still has to be discussed and improved in SE. Therefore, additional assessments of this set of guidelines are needed to strengthen the confidence in their completeness and usefulness.

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Metrics for software process simulation modeling

Liu,

Zhang,

Dong

et al. 2024

J Software Evolu Process

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Software process simulation (SPS) has become an effective tool for software process management and improvement. However, its adoption in industry is less than what the research community expected due to the burden of measurement cost and the high demand for domain knowledge. The difficulty of extracting appropriate metrics with real data from process enactment is one of the great challenges. We aim to provide evidence‐based support of the process metrics for software process (simulation) modeling. A systematic literature review was performed by extending our previous review series to draw a comprehensive understanding of the metrics for process modeling following our proposed ontology of metrics in SPS. We identify 131 process modeling studies that collectively involve 1975 raw metrics and classified them into 21 categories using the coding technique. We found product and process external metrics are not used frequently in SPS modeling while resource external metrics are widely used. We analyze the causal relationships between metrics. We find that the models exhibit significant diversity, as no pairwise relationship between metrics accounts for more than 10% SPS models. We identify 17 data issues may encounter in measurement and 10 coping strategies. The results of this study provide process modelers with an evidence‐based reference of the identification and the use of metrics in SPS modeling and further contribute to the development of the body of knowledge on software metrics in the context of process modeling. Furthermore, this study is not limited to process simulation but can be extended to software process modeling, in general. Taking simulation metrics as standards and references can further motivate and guide software developers to improve the collection, governance, and application of process data in practice.

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Modeling user story completion of an agile software process

Cited by 4 publications

References 30 publications

A Comparison of Transforming the User Stories and Functional Requirements into UML Use Case Diagram

A Comparison of Transforming the User Stories and Functional Requirements into UML Use Case Diagram

Experimentation with dynamic simulation models in software engineering: planning and reporting guidelines

Metrics for software process simulation modeling

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