Software Engineering Data Collection for Field Studies

Singer, Janice; Sim, Susan Elliott; Lethbridge, Timothy C.

doi:10.1007/978-1-84800-044-5_1

Cited by 88 publications

(65 citation statements)

References 17 publications

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“…We utilized the survey approach and employed a webbased questionnaire because of the following main advantages [17], [48], [54], [62]: 1) They allow us to understand the views of many individuals that work in different companies or industries in a unified way 2) They support data collection for many variables in a short time 3) They offer unified data collection framed by survey questions 4) They bring the potential of collecting a larger number of responses than with interviews 5) When compared to interviewing practitioners in our industry network, a wider and more heterogeneous sample can be reached by advertising the survey in different industry-oriented forums Prior work delivers limited understanding of how SECIA is handled in practice. The available theories around SECIA are either partial for some phenomena or inexistent for other phenomena.…”

Section: Methodsmentioning

confidence: 99%

An Industrial Survey of Safety Evidence Change Impact Analysis Practice

Vara

Borg

Wnuk

et al. 2016

IIEEE Trans. Software Eng.

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Abstract-Context. In many application domains, critical systems must comply with safety standards. This involves gathering safety evidence in the form of artefacts such as safety analyses, system specifications, and testing results. These artefacts can evolve during a system's lifecycle, creating a need for change impact analysis to guarantee that system safety and compliance are not jeopardised. Objective. We aim to provide new insights into how safety evidence change impact analysis is addressed in practice. The knowledge about this activity is limited despite the extensive research that has been conducted on change impact analysis and on safety evidence management. Method. We conducted an industrial survey on the circumstances under which safety evidence change impact analysis is addressed, the tool support used, and the challenges faced. Results. We obtained 97 valid responses representing 16 application domains, 28 countries, and 47 safety standards. The respondents had most often performed safety evidence change impact analysis during system development, from system specifications, and fully manually. No commercial change impact analysis tool was reported as used for all artefact types and insufficient tool support was the most frequent challenge. Conclusion. The results suggest that the different artefact types used as safety evidence co-evolve. In addition, the evolution of safety cases should probably be better managed, the level of automation in safety evidence change impact analysis is low, and the state of the practice can benefit from over 20 improvement areas.

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Section: Methodsmentioning

confidence: 99%

An Industrial Survey of Safety Evidence Change Impact Analysis Practice

Vara

Borg

Wnuk

et al. 2016

IIEEE Trans. Software Eng.

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“…As expected, some organizations replied that they were misrepresented in the registers and did not develop software, some organizations had restructured or ceased operations, etc. The return rate of the survey was 13%, which is comparable to most software engineering surveys, although [37] claims to have found a consistent response rate as low as 5%.…”

Section: Participant Sources and Survey Designmentioning

confidence: 56%

Current state and potential of variability management practices in software-intensive SMEs: Results from a regional industrial survey

Thörn¹

2010

Information and Software Technology

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“…In (Singer et al 2008), a range of qualitative research methods for use in empirical studies is described; these provided guidance in designing a protocol that sought to minimize the risk of influencing the environment with our presence. Thus, we designed a methodology, in which the first author collected information through participant observation as described by Taylor and Bogdan (1984) as ''research that involves social interaction between the researcher and informants in the milieu of the latter, during which data are systematically and unobtrusively collected.''…”

Section: Methodsmentioning

confidence: 99%

Identifying patients at risk of deterioration in the Joint Emergency Department

Schmidt

Wiil

2015

Cogn Tech Work

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In recent years, Danish hospitals have merged their emergency facilities into Joint Emergency Departments. This poses new collaborative challenges across traditionally separated specialized departments, which now have to collaborate in a shared environment. Despite established protocols and patient monitoring regimes, as many as 31 % of non-critical patients deteriorate with potentially severe consequences. To understand why this may be, we conduct a field study with the aim of investigating what factors external to patients relate to the clinicians' ability to notice adverse events. We look at the case through the lenses of common information spaces. In particular, we apply Bossen's seven-parameter framework to discover new dimensions of how Emergency Departments and individual clinicians identify and respond to unforeseen events, and how they handle the associated cognitive challenges. We complement these findings with a review of a novel taxonomy for patient monitoring. Our contribution is the identification of four improvement areas for patient monitoring platforms in terms of support for the identification of patient deterioration.

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Software Engineering Data Collection for Field Studies

Cited by 88 publications

References 17 publications

An Industrial Survey of Safety Evidence Change Impact Analysis Practice

An Industrial Survey of Safety Evidence Change Impact Analysis Practice

Current state and potential of variability management practices in software-intensive SMEs: Results from a regional industrial survey

Identifying patients at risk of deterioration in the Joint Emergency Department

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