This plotting yields a distinctly different perspective than plotting scattered intensity versus linear θ. Where k = 2π/ λ, λ is the wavelength of light, θ is the scattering angle and the scale for plotting should be logarithmic. That is, if the pattern cannot be described, how can one quantitatively describe the scattering pattern and distinguish one pattern from another? Furthermore, if the pattern cannot be described, how can one know the physics responsible for the pattern? However, given a solution or a set of data for scattering, the problem remains what to do with it. Moreover, comprehensive experimental studies of scattering both in the lab and the field have occurred. Nevertheless, remarkable analytical and numerical methods have been developed and computational hardware has allowed for ever increasing speed for large scale calculations. The problem of how spherical particles interact with light was solved long ago on the other hand a solution to describe and understand light scattering and absorption by non-spherical particles can be very challenging. All these particles scatter and absorb light and this light-particle interaction is significant for the energy budget of the atmosphere and the Earth itself. The results indicate that the proposed operators are effective for testing the vulnerabilities, and the mutation-based vulnerability testing process ensures the quality of the applications against these vulnerabilities.The particles that appear in the atmosphere have a variety of shapes that can be simply divided into spheres and non-spheres. Three prototype tools are developed to automatically generate mutants and perform mutation analysis with input test cases and the effectiveness of the proposed operators is evaluated on several open source programs containing known vulnerabilities. We propose distinguishing or killing criteria for mutants that consider varying symptoms of exploitations. The mutants generated by the operators are killed by test cases that expose these vulnerabilities. ![]() The operators mutate source code to inject the vulnerabilities in the library function calls and unsafe implementation language elements. We propose mutation operators to force the generation of adequate test data sets for these vulnerabilities. ![]() In this thesis, we apply the idea of mutation-based adequate testing to perform vulnerability testing of buffer overflows, SQL injections, and format string bugs. We believe that bringing the idea of traditional functional test adequacy to vulnerability testing can help address the issue of test adequacy. Moreover, these approaches do not provide an indication whether a test data set is adequate for vulnerability testing or not. Unfortunately, very few approaches address the issue of testing implementations against vulnerabilities. Many approaches have been proposed to detect these vulnerabilities. Successful exploitations of these vulnerabilities may result in severe consequences such as denial of services, application state corruptions, and information leakage. Despite the rigorous use of various existing testing techniques, many vulnerabilities are discovered after the deployment of software implementations, such as buffer overflows (BOF), SQL injections, and format string bugs (FSB). However, implementations that pass functionality tests are still vulnerable to malicious attacks. Mutation-based testing can be employed to obtain adequate test data sets, and numerous mutation operators have been proposed to date to measure the adequacy of test data sets that reveal functional faults. An adequate test data set consists of test cases that can expose faults in a software implementation. One of the key issues in testing is to obtain a test data set that is able to effectively test an implementation. Testing is an indispensable mechanism for assuring software quality.
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