Coding, the analytic task of assigning codes to nonnumeric data, is foundational to writing research. A rich discussion of methodological pluralism has established the foundational importance of systematicity in the task of coding, but less attention has been paid to the equally important commitment to language complexity. Addressing the interplay among a commitment to language complexity, the selection of tools, and the construction of workflow, this article offers a framework of analytic tasks in coding. Three general purpose coding tools are explored: Excel, MAXQDA, and Dedoose. This exploration suggests that how four aspects of analysis should be supported in order to manage language complexity: code restructuring, segmentation in advance of coding, use of a full coding scheme, and retrieval of full context by code. This analysis is intended to help writing researchers choose tools and design workflow to support coding work consistent with our commitment to language in its full complexity.
