The positioning performance with the LVC (Last Visited Cells) report is evaluated and compared with extended reports with signal strength data. The LVC report contains cell identities and time spent in the last cells listened to. This is an off-line data source and the purpose of the positioning is to extract information about users’ whereabouts, which for example can be used to optimize the cellular network or vehicular traffic. The positioning evaluation is done in Matlab with a log-distance model, a fingerprinting algorithm, and a new LVC specific algorithm. A particle filter and a particle smoother is used to process simulated LVC reports and extended reports with different amount of information. The results are compared and evaluated with regard to the positioning accuracy and the information density of the reports.

The aim of the thesis was to design, implement and evaluate the results of automatic tests for the JavaScript Restrictor project, which is being developed as a web browser extension. The tests are divided into three levels - unit, integration, and system. The Unit Tests verify the behavior of individual features, the Integration Tests verify the correct wrapping of browser API endpoints, and the System Tests check that the extension does not suppress the desired functionality of web pages. The System Tests are implemented for parallel execution in a distributed environment which has succeeded in achieving an almost directly proportional reduction in time with respect to the number of the tested nodes. The benefit of this work is detection of previously unknown errors in the JavaScript Restrictor extension and provision of the necessary information that allowed to fix some of the detected bugs.