A data-driven risk measurement model of software developer turnover

Ma, Zifei; Li, Ruiyin; Li, Tong; Zhu, Rui; Jiang, Rong; Yang, Juan; Tang, Mingjing; Zheng, Ming

doi:10.1007/s00500-019-04540-z

Cited by 9 publications

(3 citation statements)

References 30 publications

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“…2017 ; Ma et al. 2020 ). For example, community smells can predict if and which developers stop contributing to a project (Huang et al.…”

Section: Related Workmentioning

confidence: 99%

Locating community smells in software development processes using higher-order network centralities

Gote,

Perri,

Zingg

et al. 2023

Soc. Netw. Anal. Min.

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Community smells are negative patterns in software development teams’ interactions that impede their ability to successfully create software. Examples are team members working in isolation, lack of communication and collaboration across departments or sub-teams, or areas of the codebase where only a few team members can work on. Current approaches aim to detect community smells by analysing static network representations of software teams’ interaction structures. In doing so, they are insufficient to locate community smells within development processes. Extending beyond the capabilities of traditional social network analysis, we show that higher-order network models provide a robust means of revealing such hidden patterns and complex relationships. To this end, we develop a set of centrality measures based on the higher-order network model and show their effectiveness in predicting influential nodes using five empirical datasets. We then employ these measures for a comprehensive analysis of a product team at the German IT security company genua GmbH, showcasing our method’s success in identifying and locating community smells. Specifically, we uncover critical community smells in two areas of the team’s development process. Semi-structured interviews with five team members validate our findings: while the team was aware of one community smell and employed measures to address it, it was not aware of the second. This highlights the potential of our approach as a robust tool for identifying and addressing community smells in software development teams. More generally, our work contributes to the social network analysis field with a powerful set of higher-order network centralities that effectively capture community dynamics and indirect relationships.

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“…2017 ; Ma et al. 2020 ). For example, community smells can predict if and which developers stop contributing to a project (Huang et al.…”

Section: Related Workmentioning

confidence: 99%

Locating community smells in software development processes using higher-order network centralities

Gote,

Perri,

Zingg

et al. 2023

Soc. Netw. Anal. Min.

View full text Add to dashboard Cite

show abstract

“…Lack of documentation denotes that the previous knowledge (such as design decisions and their rationales) is not available or documented (such as undocumented design decisions and assumptions), which hinders the subsequent architecture enhancements and modifications (e.g., [S57] and [S66]). Besides, developer turnover 43 aggravates AEr by losing knowledge about system requirements and architectural decisions (e.g., [S50]).…”

Section: Lack Of Communication Between Stakeholders [S12][s25][s34][s47]mentioning

confidence: 99%

Understanding software architecture erosion: A systematic mapping study

Liang

Soliman

et al. 2022

J Software Evolu Process

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Architecture erosion (AEr) can adversely affect software development and has received significant attention in the last decade. However, there is an absence of a comprehensive understanding of the state of research about the reasons and consequences of AEr, and the countermeasures to address AEr. This work aims at systematically investigating, identifying, and analyzing the reasons, consequences, and ways of detecting and handling AEr. With 73 studies included, the main results are as follows: (1) AEr manifests not only through architectural violations and structural issues but also causing problems in software quality and during software evolution; (2) non-technical reasons that cause AEr should receive the same attention as technical reasons, and practitioners should raise awareness of the grave consequences of AEr, thereby taking actions to tackle AEr-related issues; (3) a spectrum of approaches, tools, and measures has been proposed and employed to detect and tackle AEr; and (4) three categories of difficulties and five categories of lessons learned on tackling AEr were identified. The results can provide researchers a comprehensive understanding of AEr and help practitioners handle AEr and improve the sustainability of their architecture. More empirical studies are required to investigate the practices of detecting and addressing AEr in industrial settings.

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“…Lack of documentation denotes that the previous knowledge (such as design decisions and their rationales) is not available or documented (such as undocumented design decisions and assumptions), which hinders the subsequent architecture enhancements and modifications (e.g., [S57], [S66]). Besides, developer turnover [43] aggravates AEr by losing knowledge about system requirements and architectural decisions (e.g., [S50]).…”

Section: Immobilitymentioning

confidence: 99%

Understanding Software Architecture Erosion: A Systematic Mapping Study

Li,

Liang,

Soliman

et al. 2021

Preprint

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Architecture Erosion (AEr) can adversely affect software development and has received significant attention in the last decade. However, there is an absence of a comprehensive understanding of the state of research about the reasons and consequences of AEr, and the countermeasures to address AEr. This work aims at systematically investigating, identifying, and analyzing the reasons, consequences, and ways of detecting and handling AEr. With 73 studies

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A data-driven risk measurement model of software developer turnover

Cited by 9 publications

References 30 publications

Locating community smells in software development processes using higher-order network centralities

Locating community smells in software development processes using higher-order network centralities

Understanding software architecture erosion: A systematic mapping study

Understanding Software Architecture Erosion: A Systematic Mapping Study

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