Master of Science
James H. Andrews
Software testing is a crucial part of the software development process, because it helps developers ensure that the software works correctly and according to stakehold- ers’ requirements and specifications. Faulty or problematic software can cause huge financial losses. Automation of testing tasks can have a positive impact on software development, by reducing costs and minimizing human error. Software testing can be divided into three tasks: choosing test cases, running test cases on the software under test (SUT) and evaluating the test results. To evaluate test results, testers need to examine the output of the SUT to determine if it performed as expected. Programs often store some of their outputs in files known as log files. The task of evaluating test results can be automated by using a log file analyzer. The main goal of this thesis is to design an approach to generate log file analyzers based on a set of state machine specifications. Our analyzers are generated in C++ and are capable of reading log files from disk or shared memory areas. Regular expressions have been incorporated, so that analyzers can be adapted to different logging policies. We analyze the purpose and benefits of this framework and discuss differences with a previous implementation based on Prolog. In particular, we discuss the results of a series of experiments that we performed in order to compare the performance between Prolog–based analyzers and C++ analyzers. Our results show that C++ analyzers are between 8 and 15 times faster than Prolog–based analyzers.
Leal Aulenbacher, Ilse, "Generating Log File Analyzers" (2012). Electronic Thesis and Dissertation Repository. 780.