Abstract
The application of best-practice software inspection processes for early defect detection requires considerable human effort. Crowdsourcing approaches can support inspection activities (a) by distributing inspection effort among a group of human experts and (b) by increasing inspection control. Thus, the application of crowdsourcing techniques aims at making inspection processes more effective and efficient. In this paper, we present a crowdsourcing-supported model inspection (CSI) process and investigate its defect detection effectiveness and efficiency when inspecting an Extended Entity Relationship (EER) model. The CSI process uses so-called Expected Model Elements (EMEs) to guide CSI inspectors during defect detection. We conducted a controlled experiment on defect detection effectiveness, efficiency, and false positives. While CSI effectiveness and efficiency is lower for CSI inspectors, the number of false positives decreases. However, CSI was found promising for increasing the control of defect detection and supports the inspection of large-scale engineering models.
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Notes
- 1.
Amazon Mechanical Turk: www.mturk.com.
- 2.
CrowdFlower: www.crowdflower.com.
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Winkler, D., Sabou, M., Petrovic, S., Carneiro, G., Kalinowski, M., Biffl, S. (2017). Improving Model Inspection Processes with Crowdsourcing: Findings from a Controlled Experiment. In: Stolfa, J., Stolfa, S., O'Connor, R., Messnarz, R. (eds) Systems, Software and Services Process Improvement. EuroSPI 2017. Communications in Computer and Information Science, vol 748. Springer, Cham. https://doi.org/10.1007/978-3-319-64218-5_10
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DOI: https://doi.org/10.1007/978-3-319-64218-5_10
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