PBURC: a patterns-based, unsupervised requirements clustering framework for distributed agile software development

Belsis, Petros; Koutoumanos, Anastasios; Sgouropoulou, Cleo

doi:10.1007/s00766-013-0172-9

Cited by 20 publications

(13 citation statements)

References 17 publications

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“…Software development practices have been growing more and more into an agile development culture that typically focuses efforts on user and customer needs. Agile approaches are efficient for getting solutions into the environment quickly, and it requires fewer formal specifications to execute 29 . However, maintainers, regulators, buyers, and users supporting the full system life cycle may not be involved in this process resulting in their needs becoming lower in priority.…”

Section: Methodsmentioning

confidence: 99%

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

Douglas

Mazzuchi

Sarkani

2020

Systems Engineering

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Complex adaptive systems (CAS) exhibit emergent behaviors caused by the nonlinear actions between individual components within the system and their environment. These emergent behaviors are difficult to predict and measure making it very challenging to initially design from the start. Developing CASs, such as an autonomous swarming unmanned system, is a relevant key task today for solving hard problems with limited resources in a demanding economy. Swarming unmanned systems are valued by their unique capabilities, but how do stakeholders ensure their needs are considered during development? Certain stakeholders have interests that go beyond the initial delivery of the system, yet developers seem to focus efforts on designing autonomous behaviors to satisfy immediate mission needs. To close this gap, we propose a stakeholder focused framework for evaluating CASs over a full system life cycle for swarming unmanned systems. A goal‐oriented requirements engineering modeling methodology, Knowledge Acquisition in AutOmated Specification, is used to map requirements between stakeholder goals and autonomous behaviors. Behaviors are analyzed in an agent‐based simulation using NetLogo for quantifying stakeholder‐driven performance qualities (‐ilities). A case study was performed for a swarm of unmanned surface vessels called wave gliders to evaluate performance over the entire system life cycle.

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Section: Methodsmentioning

confidence: 99%

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

Douglas

Mazzuchi

Sarkani

2020

Systems Engineering

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“…• The unique characteristics belonging to the requirements of the software tend to increase the dimensionality of the relevant datasets, make them sparse and more often lead to ambiguous expressions. The aforeexplained strategy increases the challenges on the standard processing techniques [21]. • ASD is linked to improved decision-making, and the existing theories concentrate on the precise strategies of decision-making in such environments.…”

Section: Challengesmentioning

confidence: 99%

Distributed cat modeling based agile framework for software development

Prakash

Viswanathan

2019

Sādhanā

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Software development is a challenging process that requires in-depth understanding and an effective model such that the developed software inherits good quality and reliability, and attains customer satisfaction towards achieving the goals successfully. The effectiveness of the software is enabled by modifying the operating modules of the software through a model, like agility. In this paper, the catastrophic and distributed computing models are integrated into the software development process. The proposed model is termed as a distributed cat model that is developed with the aim to handle the risk factors engaged in various developing stages of the agile model. The risk factors that affect the communication, planning, release, design, coding and testing modules of the agile modules are deeply learned and executed such that the risk factors are tackled by various modules present in the proposed distributed cat model. The effectiveness of the proposed model is analysed based on the performance metrics such as Index of Integration (IoI) and Usability Goals Achievement Metric (UGAM), for which five products, including the hotel management system, Customer Relationship Management system (CRM), rainfall prediction system, temperature monitoring system and meta-search system, are employed. The analysis is performed using the parameters like mean difference, variance, standard deviation and correlation coefficient. The result proves that the proposed model offers a great positive deviation contributing to high degree of performance in software development.

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“…Inconsistency is analyzed in [17] by proposing the framework of a patterns-based unsupervised requirements clustering (based on k-means algorithm), called PBURC, which makes use of machine-learning methods for requirements validation. This approach aims to overcome data inconsistencies and effectively determine appropriate requirements clusters for optimal definition of software development sprints.…”

Section: A Redundancy and Inconsistency Detectionmentioning

confidence: 99%

Industrial Requirements Classification for Redundancy and Inconsistency Detection in SEMIOS

Mezghani¹,

Kang²,

Sèdes³

2018

2018 IEEE 26th International Requirements Engineering Conference (RE)

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Requirements are usually "hand-written" and suffers from several problems like redundancy and inconsistency. The problems of redundancy and inconsistency between requirements or sets of requirements impact negatively the success of final products. Manually processing these issues requires too much time and it is very costly. The main contribution of this paper is the use of k-means algorithm for a redundancy and inconsistency detection in a new context, which is Requirements Engineering context. Also, we introduce a filtering approach to eliminate "noisy" requirements and a preprocessing step based on the Natural Language Processing (NLP) technique to see the impact of this latter on the k-means results. We use Part-Of-Speech (POS) tagging and noun chunking to detect technical business terms associated to the requirements documents that we analyze. We experiment this approach on real industrial datasets. The results show the efficiency of the k-means clustering algorithm, especially with the filtering and preprocessing steps. Our approach is using the software SEMIOS and will be integrated as a new functionality.

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PBURC: a patterns-based, unsupervised requirements clustering framework for distributed agile software development

Cited by 20 publications

References 17 publications

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

A stakeholder framework for evaluating the ‐ilities of autonomous behaviors in complex adaptive systems

Distributed cat modeling based agile framework for software development

Industrial Requirements Classification for Redundancy and Inconsistency Detection in SEMIOS

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