This study examines the role of LaTeX macro engineering in facilitating domain-specific knowledge formalization within Computer Science research. While LaTeX is widely adopted for technical documentation, limited empirical research has investigated its impact on the structural maturity of scholarly outputs. This paper conceptualizes and operationalizes a Technical Body of Knowledge (TBK) Index to quantitatively measure documentation rigor through indicators such as structural depth, formal notation intensity, cross-referencing density, algorithmic clarity, and bibliographic coherence.Using primary data collected from 120 Computer Science researchers, the study employs an Ordinary Least Squares (OLS) econometric model to analyse the relationship between LaTeX proficiency, macro usage frequency, research experience, and TBK maturity. The results indicate that LaTeX proficiency is the strongest predictor of TBK (β = 0.483), followed by macro usage frequency (β = 0.024), while research experience exhibits a comparatively modest effect. The model explains 62.9% of the variation in the TBK Index (R² = 0.629), demonstrating substantial explanatory power. The findings suggest that domain-specific macro creation functions as a knowledge abstraction mechanism, reinforcing semantic consistency and structured encoding practices. The study advances the understanding of LaTeX as a computational documentation architecture and proposes a Knowledge Formalization Framework integrating macro engineering into research training programs. The results have implications for curriculum design, research methodology instruction, and scholarly documentation standards in Computer Science academia.
Prashanth M C (Thu,) studied this question.