Candida albicans is the most medically significant fungal pathogen of humans, causing severe systemic disease with a high mortality rate in those with compromised immune function. Fully understanding the organism requires learning how it changes during the process of evolution in the laboratory and the clinic. This has been hindered by the lack of tools to easily observe what is happening across the scale of the entire genome. My work develops a series of tools to examine the structure and changes in the C. albicans genome at increasingly fine levels of resolution. I developed a reliable flow cytometry protocol to analyze the genome size of C. albicans strains, and developed software tools to translate the resulting raw data into simple numerical ploidy estimates. This allowed the discovery of the previously unknown haploid state of the C. albicans life cycle. I developed a single microarray design to assess copy number variations and loss of heterozygosity across the genome with one experiment, as well as a software tool to convert the raw array data into simple- to-interpret graphical cartoons that convey the biologically meaningful interpretations of the data. This allowed the observation of the progressive loss of genetic information through the central lineage of laboratory strains of C. albicans. I extended the array analysis software to process raw data from the ever-improving sequencing technologies which are becoming more and more available to researchers, then developed a web-interface to make it publically accessible. Using these tools has allowed the detailed analysis of the evolution of drug resistance in a patient and revealed the diversity of genomes to be found in laboratory and clinical isolates. Together, these studies represent an improvement in the ability to understand C. albicans, as well as the potential to improve our understanding of other organisms.