The objective of this thesis is to analyse theconnection between test results and field claims of ECUs (electronic controlunits) at Scania in order to improve the acceptance criteria and evaluatesoftware testing strategies. The connection is examined through computation ofdifferent measures of dependencies such as the Pearson’s correlation, Spearman’srank correlation and Kendall’s tau. The correlations are computed from testresults in different ECU projects and considered in a predictive model based onlogistic regression. Numerical results indicate a weak connection between testresults and field claims. This is partly due to insufficient number of ECUprojects and the lack of traceability of field claims and test results. Themain conclusion confirms the present software testing strategy. Continuoussoftware release and testing results in a lower field claim and thus a betterproduct.

The objective of this study is to investigate land-use changes and water quality trends within the headwaters of the Alafia River watershed. Water quality data were obtained from the Environmental Protection Commission of Hillsborough County (EPCHC). Eleven water quality parameters selected for analysis included: temperature (˚C), dissolved oxygen (DO), percent saturation of DO, conductivity, pH, total phosphorous (TP), total nitrogen (TN), ammonium, chlorophyll-a (uncorrected), fecal coliforms, and enterococci. ArcMap® & SWFWMD data were used to map EPCHC sampling stations, calculate contributing watershed size, and determine land-use changes over the course of the sampling period; 17 stations were chosen for this study. The annual average for each of the water quality parameters was calculated along with a Mann-Kendall Trend Analysis in order to determine if any of the observed trends were statistically significant. A non-parametric Kendall’s tau-b correlation and stepwise multiple linear regression tests were conducted in SPSS to determine if any statistically significant relationships between water quality data, land-use and basin size exist. The land-use results showed every basin consisted of some percentage of Low Density Residential, Cropland & Pastureland, Reservoirs, and Streams & Lake Swamps. In addition, no basin comprised of more than 20% wetlands and often it appears urbanization was at the sacrifice of agricultural lands, as opposed to wetlands. The trends in water quality showed eight of the 17 basins had at least one statistically significant trend. Analysis of the data used for this study has shown instances where water quality measurements were in violation of state standards. Changes in water quality can be statistically related to changes in land-use and basin size as both the correlation and the regression showed consistent relationships between several LULC types and water quality parameters: increases in Commercial & Services causes increased nutrients (TP and TN); Cropland & Pastureland causes decreased DO and DO% Saturation; increases in Tree Crops causes a decrease in pH; increasing Other Open Lands Rural causes a decrease in temperature; and increases in Shrub & Brushland cause decreases in conductivity and pH. As these relationships are based on the results from both analyses, it would seem that these relationships are the most reliable, and are key results of the study. These key relationships might be areas that future water resource managers may want to focus on in order to more efficiently improve or regulate water quality within headwater streams.