People Analytics in Software Development

Singer, Leif; Storey, Margaret-Anne; Filho, Fernando Marques Figueira; Zagalsky, Alexey; Germán, Daniel M.

doi:10.1007/978-3-319-60074-1_6

Cited by 7 publications

(9 citation statements)

References 53 publications

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“…People analytics and the social side of testing. Finally, people analytics [57] has also been explored by the community as a way to engage developers in testing. Pham et al [58] pro-posed an extension to the IDE that shows how much other developers in the team were testing.…”

Section: Developers' Behavioursmentioning

confidence: 99%

How Developers Engineer Test Cases: An Observational Study

Aniche¹,

Zaidman²

2021

Preprint

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One of the main challenges that developers face when testing their systems lies in engineering test cases that are good enough to reveal bugs. And while our body of knowledge on software testing and automated test case generation is already quite significant, in practice, developers are still the ones responsible for engineering test cases manually. Therefore, understanding the developers' thought-and decision-making processes while engineering test cases is a fundamental step in making developers better at testing software. In this paper, we observe 13 developers thinking-aloud while testing different real-world open-source methods, and use these observations to explain how developers engineer test cases. We then challenge and augment our main findings by surveying 72 software developers on their testing practices. We discuss our results from three different angles. First, we propose a general framework that explains how developers reason about testing. Second, we propose and describe in detail the three different overarching strategies that developers apply when testing. Third, we compare and relate our observations with the existing body of knowledge and propose future studies that would advance our knowledge on the topic.

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Section: Developers' Behavioursmentioning

confidence: 99%

How Developers Engineer Test Cases: An Observational Study

Aniche¹,

Zaidman²

2021

Preprint

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“…Integrations between these tools are becoming more prevalent. An increasing amount of information on developers' interactions and behaviors is available in project artifacts, which allows improving cooperative and development processes [17]. However, these concepts have not yet fully established themselves in the domain of Agile process improvement.…”

Section: Discussionmentioning

confidence: 99%

Mining for Process Improvements

Matthies

Dobrigkeit

Hesse

2020

Proceedings of the IEEE/ACM 42nd International Conference on Software Engineering Workshops

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Software Repositories contain knowledge on how software engineering teams work, communicate, and collaborate. It can be used to develop a data-informed view of a team's development process, which in turn can be employed for process improvement initiatives. In modern, Agile development methods, process improvement takes place in Retrospective meetings, in which the last development iteration is discussed. However, previously proposed activities that take place in these meetings often do not rely on project data, instead depending solely on the perceptions of team members. We propose new Retrospective activities, based on mining the software repositories of individual teams, to complement existing approaches with more objective, data-informed process views. CCS CONCEPTS • Software and its engineering → Agile software development.

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“…In short, we could say that PA is an analytical process that helps managers to take better decisions related to their employees. Only Singer et al (2017), link the analyzes with information gathering about how people work together to help them improving in collaborating. We found two general definitions (Leonardi and Contractor, 2018;Gaur et al, 2019) that basically refer to PA as a process that offers information to make better decisions.…”

Section: An Overview Of Human Resource Analytics Conceptualizationmentioning

confidence: 99%

“…One of the features of HR analytics is the use of large amounts of data and increasingly complex models (Singer et al, 2017;Luo et al, 2019). The results of such models are complex to understand and interpret, so tools (or new ways) to make the results and their implications understood by executives become one of the main challenges in the use of analytics (Davenport and Anderson, 2019).…”

Section: Disseminationmentioning

confidence: 99%

Tackling the HR digitalization challenge: key factors and barriers to HR analytics adoption

Fernández¹,

Gallardo-Gallardo

2020

115

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Purpose This paper aims to contribute to the literature on human resources (HR) digitalization, specifically on HR analytics, disentangling the concept of analytics applied to HR and explaining the factors that hinder companies from moving to analytics. Therefore, the central research questions addressed in this study are: what does HR analytics encompass? What impedes the adoption of analytics in HR within organizations? Design/methodology/approach The authors performed a comprehensive literature review on analytics as applied in HR. The authors relied on two of the major multidisciplinary publication databases (i.e. Scopus and WoS). A total of 64 manuscripts from 2010 to 2019 were content analyzed. Findings The results reveal that there is an ongoing confusion on HR analytics conceptualization. Yet, it seems that there is an emerging consensus on what HR analytics encompasses. The authors have identified 14 different barriers for HR analytics adoption grouped into four categories, namely, data and models, software and technology, people and management. Grounding on them the authors propose a set of 14 key factors to help to successfully adopt HR Analytics in companies. Originality/value This paper brings clarity over the conceptualization of HR analytics by offering a comprehensive definition. Additionally, it facilitates business and HR leaders in making informed decisions on adopting and implementing HR analytics. Moreover, it assists HR researchers in positioning their paper more explicitly in current debates and encouraging them to develop some future avenues of research departing from some questions posed.

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People Analytics in Software Development

Cited by 7 publications

References 53 publications

How Developers Engineer Test Cases: An Observational Study

How Developers Engineer Test Cases: An Observational Study

Mining for Process Improvements

Tackling the HR digitalization challenge: key factors and barriers to HR analytics adoption

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