Software teams and their knowledge networks in large-scale software development

mite, Darja; Moe, Nils Brede; blis, Aivars; Wohlin, Claes

doi:10.1016/j.infsof.2017.01.003

Cited by 91 publications

(107 citation statements)

References 26 publications

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“…Self-management is a central principle in agile methods, but studies from fields other than software development indicate that selfmanagement can reduce the ability to coordinate across teams effectively (Ingvaldsen and Rolfsen 2012). Also, while the teams need to self-manage, team members need to have an effective knowledge network and collaborate closely with experts outside the team in large-scale agile environments Šmite et al 2017). Having an emerging architecture (Eckstein 2014) could hamper project progress when many teams are working in parallel.…”

Section: Introductionmentioning

confidence: 99%

Exploring software development at the very large-scale: a revelatory case study and research agenda for agile method adaptation

et al. 2017

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Agile development methods were believed to best suit small, co-located teams, but the success in small teams has inspired use in large and very large-scale software development. However, fundamental assumptions of agile development are challenged when applying the methods at a very large scale. An interpretative revelatory case study on one of the largest software development programmes in Norway shows how agile methods were adapted and complemented with practices from traditional methods to handle the scale. The programme ran over four years with 12 colocated development teams and a total of 175 people involved. The case study was conducted retrospectively using group interviews with 24 participants and documents. Findings on key challenging areas are reported: customer involvement, software architecture, and inter-team coordination. The revelatory study also suggests refinements of a research agenda for very large-scale agile development. Empir Software Eng (2018) 23:490-520

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Section: Introductionmentioning

confidence: 99%

Exploring software development at the very large-scale: a revelatory case study and research agenda for agile method adaptation

et al. 2017

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“…Just as the knowledge of individuals interacts with the organisational level, so do the relationships between individuals: work-related relationships and friendships between individuals establish social network structures between teams, which influences team efficiency positively by increasing their ability to acquire and apply resources such as knowledge [62]. Software development teams have 695 been shown to rely on these relationships in particular when solving complex and unfamiliar tasks [63]. The influence of networks is not necessarily tied to tight and frequent collaboration: strong arguments exist for weak ties being critical in ensuring the propagation of knowledge, even if recent research indicates that this depends on the environment and complexity of the information [64,65].…”

Section: Organisational Implicationsmentioning

confidence: 99%

Exploratory testing: Do contextual factors influence software fault identification?

Asplund

2019

Information and Software Technology

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Context: Exploratory Testing (ET) is a manual approach to software testing in which learning, test design and test execution occurs simultaneously. Still a developing topic of interest to academia, although as yet insufficiently investigated, most studies focus on the skills and experience of the individual tester.However, contextual factors such as project processes, test scope and organisational boundaries are also likely to affect the approach.Objective: This study explores contextual differences between teams of testers at a MedTec firm developing safety-critical products to ascertain whether contextual factors can influence the outcomes of ET, and what associated implications can be drawn for test management.Method: A development project was studied in two iterations, each consisting of a quantitative phase testing hypotheses concerning when ET would identify faults in comparison to other testing approaches and a qualitative phase involving interviews.Results: Influence on ET is traced to how the scope of tests focus learning on different types of knowledge and imply an asymmetry in the strength and number of information flows to test teams. Conclusions:While test specialisation can be attractive to software development organisations, results suggest changes to processes and organisational * Corresponding author structures might be required to maintain test efficiency throughout projects: the responsibility for test cases might need to be rotated late in projects, and asymmetries in information flows might require management to actively strengthen the presence and connections of test teams throughout the firm. However, further research is needed to investigate whether these results also hold for non safety-critical faults.

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“…• To developing deep understanding: To employ a variety of methods so as to enrich our understanding of techniques, practices, and phenomena in the software engineering area. Such studies are needed to understand the state of practice, and to analyze and document complex phenomena (see, for example, Smite et al [7]);…”

Section: The Present: Articles In This Special Sectionmentioning

confidence: 99%

Introduction to the EASE 2016 special section: Evidence-based software engineering: Past, present, and future

Beecham

Bowes

Stol

2017

Information and Software Technology

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The International Conference on Evaluation and Assessment in Software Engineering (EASE) had its twentieth anniversary in 2016, with that year's edition hosted in Limerick, Ireland. Founded in 1997, the EASE conference was the first event solely dedicated to encouraging empirical research in software engineering, and its founders have been longtime advocates of evidence-based software engineering (EBSE). In this editorial, we briefly look back at the history of EBSE and the EASE conference. We then introduce the four articles which are revised and extended versions of papers presented at EASE 2016. We conclude by looking at the future of EBSE, and provide some suggestions for conducting and reporting empirical research.

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Software teams and their knowledge networks in large-scale software development

Cited by 91 publications

References 26 publications

Exploring software development at the very large-scale: a revelatory case study and research agenda for agile method adaptation

Exploring software development at the very large-scale: a revelatory case study and research agenda for agile method adaptation

Exploratory testing: Do contextual factors influence software fault identification?

Introduction to the EASE 2016 special section: Evidence-based software engineering: Past, present, and future

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