The Software Failure Prediction Based on Fractal

Reliability is one of the most important qualities of software, and failure analysis is an important part of the research of software reliability. Fractals are mathematical or natural objects that are made of parts similar to the whole in certain ways. A fractal has a self-similar structure that occurs at different scales. In this paper the failure data of software are analyzed, the fractals are discovered in the data, and the method of software failure prediction based on fractals is proposed. Analyzing the empirical failure data (three data sets including two of Musa's) validates the validity of the model. It should be noticed that the analyses and research methods in this paper are differ from the conventional methods in the past, and a new idea for the research of the software failure mechanism is presented.

[1]  J. Yorke,et al.  Strange attractors that are not chaotic , 1984 .

[2]  G. B. Finelli,et al.  Real-time software failure characterization , 1990, Fifth Annual Conference on Computer Assurance, Systems Integrity, Software Safety and Process Security..

[3]  Abraham Kandel,et al.  Software-Reliability Modeling: The Case for Deterministic Behavior , 2007, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[4]  William Farr,et al.  Software reliability modeling survey , 1996 .

[5]  Zhang Kai.  Software Defect Fractal Growing and Mechanism Analysis , 2004 .

[6]  Amrit L. Goel,et al.  Software Reliability Models: Assumptions, Limitations, and Applicability , 1985, IEEE Transactions on Software Engineering.

[7]  Richard C. Holt,et al.  Empirical Evidence for SOC Dynamics in Software Evolution , 2007, 2007 IEEE International Conference on Software Maintenance.

[8]  B. Mandelbrot,et al.  Fractals: Form, Chance and Dimension , 1978 .

[9]  Janet R. Dunham.  Experiments in software reliability: Life-critical applications , 1986, IEEE Transactions on Software Engineering.

[10]  Tobias J. Hagge,et al.  Physics , 1929, Nature.

[11]  A. Wolf,et al.  Determining Lyapunov exponents from a time series , 1985 .

[12]  Wang Ji,et al.  High Confidence Software Engineering Technologies , 2003 .

[13]  Michael Friedman,et al.  Software Assessment: Reliability, Safety, Testability , 1995 .

[14]  Elmer E Lewis,et al.  Introduction To Reliability Engineering , 1987 .

[15]  Kai-Yuan Cai,et al.  A critical review on software reliability modeling , 1991 .

[16]  J. A. Stewart,et al.  Nonlinear Time Series Analysis , 2015 .

[17]  Benoit B. Mandelbrot,et al.  Fractal Geometry of Nature , 1984 .

[18]  W D Brooks,et al.  Analysis of Discrete Software Reliability Models. , 1980 .

[19]  Zou Feng.  A Chaotic Model for Software Reliability , 2001 .

[20]  G. B. Finelli,et al.  NASA Software failure characterization experiments , 1991 .