A social network based study of software team dynamics

Datta, Subhajit; Kaulgud, Vikrant; Sharma, Vibhu Saujanya; Kumar, Naveen

doi:10.1145/1730874.1730883

Cited by 17 publications

(17 citation statements)

References 17 publications

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“…5) Team Analysis: PIVoT also analyzes the project data from a "team" perspective. In our field studies [6], we found that even in small teams of about 30 developers, project managers are not fully aware of the team structure and nature of contributions from developers -parts of the code contributed, amount contributed, type of contribution (fresh code, modification to old code etc.). It has been shown in various other studies [7], [8], [9] as well that the team organization and structure has important bearing on the project metrics and outcomes.…”

Section: ) Quality Of Component Testing Effort (Qcte)mentioning

confidence: 84%

PIVoT: Project insights and Visualization Toolkit

Sharma¹,

Kaulgud²

2012

2012 3rd International Workshop on Emerging Trends in Software Metrics (WETSoM)

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An in-process view into a software development project's health is critical for its success. However, in services organizations, a typical software development team employs a heterogeneous set of tools based on client requirements through the different phases of the software project. The use of disparate tools with non-compatible outputs makes it very difficult to extract one coherent picture of the project's health and status. Existing project management tools either work at the process layer and rely on manually entered information, or are activity centric, without a holistic view. In this paper, we present PIVoT, a metric-based framework for automated, non-invasive, and in-process data collection and analysis in heterogeneous software project environments, that provides rich, multi-dimensional insights into the project's health and trajectory. Here, we introduce the different analyses, insights and metrics, and discuss their usage in typical software projects.

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Section: ) Quality Of Component Testing Effort (Qcte)mentioning

confidence: 84%

PIVoT: Project insights and Visualization Toolkit

Sharma¹,

Kaulgud²

2012

2012 3rd International Workshop on Emerging Trends in Software Metrics (WETSoM)

Self Cite

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“…The MS-Vista binaries was used also in addition to an open source project (i.e., the Eclipse) in the work [9]. Two PSs did not provide information about the used industrial data [20,16]. The projects Eclipse, Firefox, and Apache were used the most in the PSs with frequencies 7, 6, and 4 times, respectively.…”

Section: Data Results and Interpretation (Feature C)mentioning

confidence: 99%

On Using Network Science in Mining Developers Collaboration in Software Engineering: A Systematic Literature Review

Abufouda¹,

Abukwaik²

2017

IJDKP

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Abstract.Background: Network science is the set of mathematical frameworks, models, and measures that are used to understand a complex system modeled as a network composed of nodes and edges. The nodes of a network represent entities and the edges represent relationships between these entities. Network science has been used in many research works for mining human interaction during different phases of software engineering (SE). Objective: The goal of this study is to identify, review, and analyze the published research works that used network analysis as a tool for understanding the human collaboration on different levels of software development. This study and its findings are expected to be of benefit for software engineering practitioners and researchers who are mining software repositories using tools from network science field. Method: We conducted a systematic literature review, in which we analyzed a number of selected papers from different digital libraries based on inclusion and exclusion criteria. Results: We identified 35 primary studies (PSs) from four digital libraries, then we extracted data from each PS according to a predefined data extraction sheet. The results of our data analysis showed that not all of the constructed networks used in the PSs were valid as the edges of these networks did not reflect a real relationship between the entities of the network. Additionally, the used measures in the PSs were in many cases not suitable for the used networks. Also, the reported analysis results by the PSs were not, in most cases, validated using any statistical model. Finally, many of the PSs did not provide lessons or guidelines for software practitioners that can improve the software engineering practices. Conclusion: Although employing network analysis in mining developers' collaboration showed some satisfactory results in some of the PSs, the application of network analysis needs to be conducted more carefully. That is said, the constructed network should be representative and meaningful, the used measure needs to be suitable for the context, and the validation of the results should be considered. More and above, we state some research gaps, in which network science can be applied, with some pointers to recent advances that can be used to mine collaboration networks.

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“…In turn, these modifications are associated (or not) with planned or desired social changes. In several studies on software development, SNA was used to generate insights into the structure, communication, and performance of teams, for example, to identify the relation between the social structure and performance of traditional software teams or to determine central individuals in a bug tracker system . Other examples of its use are to study the role of communication among the persons involved in the success and quality of software integration and to examine the influence of the social structure of the persons involved in a software process improvement initiative .…”

Section: Research Approachmentioning

confidence: 99%

“…42 Global centrality addresses the inadequacy of centrality by considering the distance from a particular node to all others in the graph, instead of just its neighbors. 47 Global centrality helps to determine power, influence, and control of the information and communication of employees. 66…”

Section: Nodes Centralitymentioning

confidence: 99%

Analysis of the changes in communication and social interactions during the transformation of a traditional team into an agile team

Espinosa-Curiel

Rodríguez-Jacobo

Vázquez-Alfaro

et al. 2018

J Software Evolu Process

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Traditional software teams that implement agile methodologies frequently experience difficulty working efficiently as agile teams. While agile methodologies support and promote social activities and behaviors, the understanding of the social phenomena and challenges that arise during the transformation of traditional teams into agile teams is limited. We conducted an extensive 10‐month case study in a software enterprise to analyze the changes in the communication and social interactions of employees during the transformation process, and to delineate the social challenges that arise during this process. Using social interaction registers, we collected data on the communication and social interactions of employees, first when they worked as a traditional team and then as an agile team. Then, we processed the data using social network analysis methods to identify the differences between these 2 types of teams and to create graphs of communication and social interaction networks. We identified that the transformation process influences formal, informal, oral, and written communication and increases conjunctive and disjunctive social interactions. Further, from the results of interviews conducted with all the enterprise members, we identified 5 social challenges to transforming a traditional team into an agile one. The results of this research suggest that the transformation process requires broad changes in the relationships and interactions among employees.

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A social network based study of software team dynamics

Cited by 17 publications

References 17 publications

PIVoT: Project insights and Visualization Toolkit

PIVoT: Project insights and Visualization Toolkit

On Using Network Science in Mining Developers Collaboration in Software Engineering: A Systematic Literature Review

Analysis of the changes in communication and social interactions during the transformation of a traditional team into an agile team

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