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Ko, A.J., Abraham, R., Beckwith, L., Blackwell, A., Burnett, M., Erwig, M., Scaffidi, C., Lawrance, J., Lieberman, H., Myers, B., Rosson, M.B., Rothermel, G., Shaw, M. and Wiedenbeck, S. (2011) The State of the Art in End-User Software Engineering. ACM Computing Surveys, 43, Article No. 21.
https://doi.org/10.1145/1922649.1922658

has been cited by the following article:

• TITLE: Building Custom Spreadsheet Functions with Python: End-User Software Engineering Approach

  AUTHORS: Tamer Bahgat Elserwy, Atef Tayh Nour El-Din Raslan, Tarek Ali, Mervat H. Gheith

  KEYWORDS: End-User Software Engineering, Custom Spreadsheet Functions (CSFs),

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.17 No.5, May 28, 2024

  ABSTRACT: End-user computing empowers non-developers to manage data and applications, enhancing collaboration and efficiency. Spreadsheets, a prime example of end-user programming environments widely used in business for data analysis. However, Excel functionalities have limits compared to dedicated programming languages. This paper addresses this gap by proposing a prototype for integrating Python’s capabilities into Excel through on-premises desktop to build custom spreadsheet functions with Python. This approach overcomes potential latency issues associated with cloud-based solutions. This prototype utilizes Excel-DNA and IronPython. Excel-DNA allows creating custom Python functions that seamlessly integrate with Excel’s calculation engine. IronPython enables the execution of these Python (CSFs) directly within Excel. C# and VSTO add-ins form the core components, facilitating communication between Python and Excel. This approach empowers users with a potentially open-ended set of Python (CSFs) for tasks like mathematical calculations, statistical analysis, and even predictive modeling, all within the familiar Excel interface. This prototype demonstrates smooth integration, allowing users to call Python (CSFs) just like standard Excel functions. This research contributes to enhancing spreadsheet capabilities for end-user programmers by leveraging Python’s power within Excel. Future research could explore expanding data analysis capabilities by expanding the (CSFs) functions for complex calculations, statistical analysis, data manipulation, and even external library integration. The possibility of integrating machine learning models through the (CSFs) functions within the familiar Excel environment.