Resolving team selection in agile development using NSGA-II algorithm

Arunachalam, Abhinaya; Nagarajan, Nandhini Priya; Mohan, Vanathi; Reddy, Monica; Arumugam, Chamundeswari

doi:10.1007/s40012-016-0105-0

Cited by 7 publications

(5 citation statements)

References 4 publications

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“…The literature offers various solutions for software team formation, involving the utilization of different attributes. Some approaches focus on soft skills [24,40] and hard skills [4,6] attributes. Singh Jat et al [30] elected team members based on performance estimates, in addition to technical and social factors, while Latorre and Suárez [34] developed a Socio-technical framework.…”

Section: Team Formation Approachesmentioning

confidence: 99%

Preliminary Results of Mapping Capabilities for Agile Software Team Formation

Cunha,

Santos,

Perkusich

et al. 2023

Anais Do III Workshop Brasileiro De Engenharia De Software Inteligente (ISE 2023)

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Context: Team formation is critical in agile software development, directly affecting project effectiveness and performance. Ensuring teams possess the necessary capabilities is vital for success. However, the specific capabilities used in practice for team composition remain unclear. Aims: Our objective is to understand the evolution, relevance, and practical application of capabilities used in agile team formation and gain real-world insights. Method: We conducted a comparative analysis, contrasting the software engineers’ capabilities identified in a prior review with those used in agile team formation based on recent studies. To gain insights into real-world practices, we interviewed a key practitioner from a software organization through a semi-structured interview. Results: The study highlights the most impactful capabilities for agile team formation, providing valuable guidance for practitioners and researchers to enhance software engineering practices. Conclusions: This research advances the understanding of essential attributes for successful agile team formation and offers valuable implications on underlying aspects and challenges faced in the practical application of these capabilities.

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Section: Team Formation Approachesmentioning

confidence: 99%

Preliminary Results of Mapping Capabilities for Agile Software Team Formation

Cunha,

Santos,

Perkusich

et al. 2023

Anais Do III Workshop Brasileiro De Engenharia De Software Inteligente (ISE 2023)

View full text Add to dashboard Cite

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“…For instance, Costa et al [30] proposed an automated approach to form multiple teams in Scrum projects using a single-objective GA. stylianou and Andreou [31] presented a multi-objective GA to optimize the project's schedule and assigning the most experienced developers to tasks. Arunachalam et al [32] used GA to form teams with based average team's cost and productivity. Other studies using GA to form teams can be found in [33], [34].…”

Section: Related Workmentioning

confidence: 99%

A Genetic Algorithm-Based Approach to Support Forming Multiple Scrum Project Teams

Costa

Ramos

Perkusich³

et al. 2022

IEEE Access

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Forming effective teams is an essential but challenging task, especially for organizations that carry out multiple projects simultaneously, a problem known as the Multiple Team Formation (MTF) problem. The literature presents several solutions for the MTF problem, mostly modeling it as a search problem. However, the existing solutions are not suitable for Scrum projects. We addressed this gap by developing an approach composed of two main steps. First, we designed a Structured Task Model to support creating developers' profiles given their performance on past Scrum projects. Then, given a set of target projects' technology requirements and the available developers' profiles, we developed a Genetic Algorithm to form the teams for a set of target projects. We evaluated the proposed approach by comparing the teams formed by our approach with the ones formed by project managers from one organization. Our approach achieved 85% of precision when compared with the teams provided by the project managers who worked on the same target projects. We also recorded an acceptance rate of up to 75%. The significant value of precision achieved suggests that our approach can provide teams close to the project managers' expectations. In addition, our Structured Task Model offers a promising way to build technical profiles semi-automatically for Scrum developers.

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“…Software team formation approaches have focused on the use of soft skills [16,21] and hard skills [4,5] attributes. Other studies consider personality [15] and social interactions [19].…”

Section: Team Formation Approachesmentioning

confidence: 99%

“…For the Data Source, we used the project management system in the organization under study. However, we emphasize that the data source can be any other project management system such as Git 2 , Clickup 3 , Jira 4 , Trello 5 , and Jenkins 6 .…”

Section: Data Sourcementioning

confidence: 99%

A Data-driven Framework to Support Team Formation in Software Projects

Cunha¹,

Rique²,

Gorgônio³

et al. 2022

Anais Do II Workshop Brasileiro De Engenharia De Software Inteligente (ISE 2022)

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Context Software analytics approaches have supported managers in making informed decisions regarding several software engineering problems. Team formation is a challenging one, being investigated by the research community as new approaches and tools have been proposed. However, the existing studies do not appropriately address the aspects and procedures to be adopted in the development of tools to meet most scenarios, besides not providing a concrete solution useful from a practical perspective. Aims This study provides a framework to support the development of solutions that can help managers form software teams. Method We interviewed a key practitioner from a software organization and analyzed the collected data to understand how the team formation problem is currently handled, identifying underlying aspects and challenges faced by the organization. Results We presented an overview of the proposed framework and the results of a preliminary evaluation performed by integrating a prototype into an enterprise system. Conclusions Our results provide a concrete solution for the team formation problem that can be integrated not only into a project management tool, but also into software analytics tools.

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Resolving team selection in agile development using NSGA-II algorithm

Cited by 7 publications

References 4 publications

Preliminary Results of Mapping Capabilities for Agile Software Team Formation

Preliminary Results of Mapping Capabilities for Agile Software Team Formation

A Genetic Algorithm-Based Approach to Support Forming Multiple Scrum Project Teams

A Data-driven Framework to Support Team Formation in Software Projects

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