Technical debt in general refers to suboptimal decisions the practitioners make during software development that achieve short-term goals at the expense of long-term quality concerns. Architecture technical debt is a subset of technical debt, when software practitioners make wrong or sub-optimal decisions related to the architecture of the software. Identifying such architecture technical debt plays a crucial role in software quality. In the last decade, there were several methods proposed to identify architecture debts in the literature.In this study, we conduct a systematic literature review of methods that identify architecture technical debt by inspecting 28 primary studies published from 2011 to 2020. Based on the outcomes of our review: (1) design rule space and traceability graphs are the dominant techniques; (2) despite the increase of automated techniques in identifying architecture debt, pure manual methods using expert opinion is still popular; (3) majority of the approaches use code/version history to mine archictural technical debt; (4) the field is getting increasingly more attraction in the last five years.