At the evolution or maintenance stage of software engineering, software developers are required to handle many Software Change Orders (SCOs), which are generally prepared in natural language texts and involve one or more problem domains. The developers will accurately map these orders to corresponding source codes in the software programme and make ordered changes. This mapping requires creation of several search terms and search of them in the programme. Studies show that developers have difficulties in creating accurate and suitable search conditions for changes. In this study, the author proposes a TextRank-based search term recognition method for software change tasks. It enables identification and creation of search terms for software changes by analyzing tasks described in natural languages, to improve the accuracy, average precision, and recall rate of searching.