With an eye toward performance, interoperability, or legacy concerns, low-level system software often must parse binary encoded data formats. Few tools are available for this task, especially since the formats involve a mixture of arithmetic and data dependence, beyond what can be handled by typical parser generators. As such, parsers are written by hand in languages like C, with inevitable errors leading to security vulnerabilities.

Web search is a key digital literacy skill that can be particularly challenging for people with dyslexia, a common learning disability that affects reading and spelling skills in about 15% of the English-speaking population. In this paper, we collected and analyzed eye-tracking, search log, and self-report data from 27 participants (14 with dyslexia) to confirm that searchers with dyslexia struggle with all stages of the search process and have markedly different gaze patterns and search behavior that reflect the strategies used and challenges faced. Based on these findings, we discuss design implications to improve the cognitive accessibility of web search.