article · 2010
Software defect detection and process improvement using personal software process data
M. Gopichand, V. Swetha, A. Ananda Rao
Cited by 4Abstract and details only
Abstract
Statistical evidence has shown that programmers perform better when following a defined, repeatable process such as the Personal Software Process (PSP).Anecdotal and qualitative evidence from industry indicates that two programmers working side-by-side at one computer, collaborating on the same design, algorithm, code, or test, perform substantially better than the two working alone i.e. pair programming. Bringing these two ideas together, a new Software Process has been formulated. The Hybrid Personal Software Process (HPSP) is a defined, repeatable process for two programmers working collaboratively. The development time and cost of the product are reduced in HPSP when compared with PSP programming.
Cite this paper
Gopichand, M., Swetha, V., & Rao, A. A. (2010). Software defect detection and process improvement using personal software process data. https://doi.org/10.1109/icccct.2010.5670734
Gopichand, M., et al. “Software defect detection and process improvement using personal software process data.” 2010, pp. 794–99, https://doi.org/10.1109/icccct.2010.5670734.
Gopichand, M., V. Swetha, and A. Ananda Rao. 2010. “Software defect detection and process improvement using personal software process data.” https://doi.org/10.1109/icccct.2010.5670734.
Gopichand, M., Swetha, V. and Rao, A.A. (2010) ‘Software defect detection and process improvement using personal software process data’. Available at: https://doi.org/10.1109/icccct.2010.5670734.
@article{gopichand2010software,
title = {{Software defect detection and process improvement using personal software process data}},
author = {Gopichand, M. and Swetha, V. and Rao, A. Ananda},
pages = {794--799},
year = {2010},
doi = {10.1109/icccct.2010.5670734}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.
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