An imperfect software debugging model considering log-logistic distribution fault content function

Generalized multi‐release modelling of software reliability growth models from the perspective of two types of imperfect debugging and change point

“…Then, models incorporating both imperfect debugging and error introduction/generation have been put forth in previous studies . Recently, more work on fault detection and correction or imperfect debugging has been proposed by other studies . All these models assume that the rate of fault detection and/or removal stays the same throughout the testing.…”

“…4,[15][16][17] Recently, more work on fault detection and correction or imperfect debugging has been proposed by other studies. [18][19][20][21][22]46,49,52,54 All these models assume that the rate of fault detection and/or removal stays the same throughout the testing. In Kapur et al, 23 models have been proposed based on change point.…”

The sigmoidal growth of operating system security vulnerabilities: An empirical revisit

“…The other example comes from reliability modeling within which the central question is how reliability of software increases over time. As recently surveyed by Wang et al (2014), numerous different S-shaped curves have been used in this equivalently extensive branch of empirical research. If no new faults are assumed to arrive when detected faults are removed, the so-called perfect debugging models are often based on the familiar assumptions: the number of corrected faults is proportional to the existing faults, while the upper asymptote implies a satisfactory level of quality improvements.…”

“…The literature contains an abundant amount of sigmoid functions for S-shaped growth patterns (Höök et al, 2011;López et al, 2004;Massacci and Nguyen, 2014;Meade and Islam, 2006;Wang et al, 2014;Zwietering et al, 1990). A classical example is the famous function that Gompertz (1825) formulated to determine the rate of mortality.…”

“…Akaike's information criterion (AIC), which isfrequently used in the context (Alhazmi and Malaiya, 2008;López et al, 2004;Ohishi et al, 2005;Wang et al, 2014), is as a good alternative for coarse approximate comparisons as any other readily available criterion. 4 The AIC values and F-tests provide a decent comparative toolbox for the initial analysis.…”