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Code cognition models examine how programmers understand program code. The authors survey the current knowledge in this area by comparing six program comprehension models: the Letovsky (1986) model; the Shneiderman and Mayer (1979) model; the Brooks (1983) model; Soloway, Adelson and Ehrlich's (1988) top-down model; Pennington's (1987) bottom-up model; and the integrated metamodel of von Mayrhauser and Vans (1994). While these general models can foster a complete understanding of a piece of code, they may not always apply to specialized tasks that more efficiently employ strategies geared toward partial understanding. We identify open questions, particularly considering the maintenance and evolution of large-scale code. These questions relate to the scalability of existing experimental results with small programs, the validity and credibility of results based on experimental procedures, and the challenges of data availability