Abstract
Software test effort estimation has always been an important activity for meeting testing deadlines, relocating resources, and reducing testing cost. However, in practice, estimating test effort is still a major challenge because it is difficult to quantify and collect factors that affect accurate test effort. In this study, we propose a new test effort estimation model by analyzing the relationship between the number of defects collected through defect tracking tools and the source code changes collected through configuration management tools during the software development period. Experiments are performed to validate the proposed model using real industrial software project data. The results indicate that the proposed model achieves high estimation accuracy.
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Acknowledgment
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2017R1C1B5018295).
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Won, J., Seo, YS. (2020). Software Test Effort Estimation Based on Source Code Change History and Defect Information. In: Park, J., Park, DS., Jeong, YS., Pan, Y. (eds) Advances in Computer Science and Ubiquitous Computing. CUTE CSA 2018 2018. Lecture Notes in Electrical Engineering, vol 536. Springer, Singapore. https://doi.org/10.1007/978-981-13-9341-9_38
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DOI: https://doi.org/10.1007/978-981-13-9341-9_38
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