A Practice-based Research On Computer Science Texts Translation—From The Perspective Of Translation Shift

Currently, technologies of computer science are undergoing never-ending changes and improvements. Big data, as an increasingly more important research direction of this field, is being introduced to China. However, systematic researches into the translation issue of computer science texts are quite limited both in number and quality. Within the framework of the theory of translation shift, the thesis conducts a research on computer science texts on the basis of the translation of the first chapter of Big Data:Principles and Best Practices of Scalable Realtime Data Systems. "Translation shift" means departures from theoretical formal correspondence between source and target language units for the sake of textual equivalence. The theory believes that textual equivalence is of more significance than formal correspondence, which is in line with the basic translating principle-faithfulness of technology texts. The thesis analyzes the syntactic features of computer science texts, the main reasons of level shift and category shift, and the corresponding translation techniques together with cases from Big Data:Principles and Best Practices of Scalable Realtime. Level shift is something which is expressed by grammar in one language and lexis in another, which is given expression to in the translation of tense, plural nouns, subjunctive mood, etc. Category shift, the most frequent shift, includes structure shift, class shift, unit shift, and intra-system shift. As for the syntactic features of computer science texts, the thesis proposes the correspondent translation strategy and techniques from level shift and category shift respectively, which ensures not only the correctness but readability of the target text. Thus, the translation shift theory can effectively guide the translation of computer science texts and the proper use of "shift" strategy helps to avoid translationese and Europeanization in the target text.