This dissertation addresses the use of automatic translation in translation memory systems (CAT), a fast-growing modality of work in today s specialized translation market. An experimental study was conducted with four professional translators specializing in the field of computing. Each professional translated two texts, one about technology marketing and the other, a highly technical document, using different modalities of work. The purpose of the study was to identify any differences resulting from the use of automatic translation, with segment-based post-editing, and the use of automatic translation as sub-segment translation suggestions. The resources of computational linguistics were employed to analyze the translations, considering the following metrics: lexical diversity, lexical density, edit distance, taking into account grammatical sequences, and productivity. For comparative purposes, the experimental study included 100 percent human translations and automatic translations that were not submitted to post-editing. The metrics employed turned out differing results attributable to the modalities of work, and allowed for the comparison of the effects on the different types of texts translated. Finally, the multiple translations of one of the texts were submitted to the evaluation of the readers, to determine their preferences.