Please use this identifier to cite or link to this item: https://doi.org/10.1109/TSMCA.2008.2001071
Title: On the trend of remaining software defect estimation
Authors: Bai, C.-G.
Cai, K.-Y.
Hu, Q.-P.
Ng, S.-H. 
Keywords: Remaining software defect estimation (RSDE) curve
Software defects
Software reliability
Software testing profile
Issue Date: 2008
Source: Bai, C.-G., Cai, K.-Y., Hu, Q.-P., Ng, S.-H. (2008). On the trend of remaining software defect estimation. IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans 38 (5) : 1129-1142. ScholarBank@NUS Repository. https://doi.org/10.1109/TSMCA.2008.2001071
Abstract: Software defects play a key role in software reliability, and the number of remaining defects is one of most important software reliability indexes. Observing the trend of the number of remaining defects during the testing process can provide very useful information on the software reliability. However, the number of remaining defects is not known and has to be estimated. Therefore, it is important to study the trend of the remaining software defect estimation (RSDE). In this paper, the concept of RSDE curves is proposed. An RSDE curve describes the dynamic behavior of RSDE as software testing proceeds. Generally, RSDE changes over time and displays two typical patterns: 1) single mode and 2) multiple modes. This behavior is due to the different characteristics of the testing process, i.e., testing under a single testing profile or multiple testing profiles with various change points. By studying the trend of the estimated number of remaining software defects, RSDE curves can provide further insights into the software testing process. In particular, in this paper, the Goel-Okumoto model is used to estimate this number on actual software failure data, and some properties of RSDE are derived. In addition, we discuss some theoretical and application issues of the RSDE curves. The concept of the proposed RSDE curves is independent of the selected model. The methods and development discussed in this paper can be applied to any valid estimation model to develop and study its corresponding RSDE curve. Finally, we discuss several possible areas for future research. © 2008 IEEE.
Source Title: IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans
URI: http://scholarbank.nus.edu.sg/handle/10635/63224
ISSN: 10834427
DOI: 10.1109/TSMCA.2008.2001071
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