SEApr 4, 2017

A Conceptual Model for Measuring the Complexity of Spreadsheets

arXiv:1704.01147v16 citations
Originality Synthesis-oriented
AI Analysis

This work addresses the problem of risk assessment in spreadsheets for business processes, but it is incremental as it builds on existing literature without introducing new methods or data.

The paper tackles the lack of a shared understanding of spreadsheet complexity drivers by proposing a conceptual model that integrates all aspects identified in related literature, forming a foundation for structured metric definitions and enhancing reproducibility.

Spreadsheets are widely used in industry, even for critical business processes. This implies the need for proper risk assessment in spreadsheets to evaluate the reliability and validity of the spreadsheet's outcome. As related research has shown, the risk of spreadsheet errors is strongly related to the spreadsheet's complexity. Therefore, spreadsheet researchers proposed various metrics for quantifying different aspects of a spreadsheet in order to assess its complexity. However, until now there is no shared understanding of potential complexity drivers for spreadsheets. The present work addresses this research gap by proposing a conceptual model integrating all aspects which are identified by related literature as potential drivers to spreadsheet complexity. In this sense, this model forms the foundation for a structured definition of complexity metrics, and thus enhances the reproducibility of their results. At the same time, it forms the foundation for identifying further applicable complexity metrics from other scientific domains.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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