Abstract

In late years, due to the significance of software application, professional testing of software becomes an increasingly important task. Once all detected faults are removed, project managers can begin to determine when to stop testing. Software reliability has important relations with many aspects of software, including the structure, the operational environment, and the amount of testing. Actually, software reliability analysis is a key factor of software quality and can be used for planning and controlling the testing resources during development. Over the past three decades, many software reliability growth models (SRGMs) have been proposed. For most traditional SRGMs, one common assumption is that the fault detection rate is a constant over time. However, the fault detection process in the operational phase is different from that in the testing phase. Thus, in this paper, we use the testing compression factor (TCF) to reflect the fact and describe the possible phenomenon. In addition, sometimes the one-to-one mapping relationship between failures and faults may not be realistic. Therefore, we also incorporate the concept of quantified ratio, not equal to 1, of faults to failures into software reliability growth modeling. We estimate the parameters of the proposed model based on real software failure data set and give a fair comparison with other SRGMs. Finally, we show how to use the proposed model to conduct software release time management

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