721 research outputs found
Structured Spreadsheet Modeling and Implementation
Developing an error-free spreadsheet has been a problem since the beginning
of end-user computing. In this paper, we present a methodology that separates
the modeling from the implementation. Using proven techniques from Information
Systems and Software Engineering, we present strict, but simple, rules
governing the implementation from the model. The resulting spreadsheet should
be easier to understand, audit and maintain.Comment: In Proceedings of the 2nd Workshop on Software Engineering Methods in
Spreadsheet
A quality model for spreadsheets
In this paper we present a quality model for spreadsheets, based on the ISO/IEC 9126 standard that defines a generic quality model for software. To each of the software characteristics defined in the ISO/IEC 9126, we associate an equivalent spreadsheet characteristic. Then, we propose a set of spreadsheet specific metrics to assess the quality of a spreadsheet in each of the defined characteristics. In order to obtain the normal distribution of expected values for a spreadsheet in each of the metrics that we propose, we have executed them against all spreadsheets in the large and widely used EUSES spreadsheet corpus. Then, we quantify each characteristic of our quality model after computing the values of our metrics, and we define quality scores for the different ranges of values. Finally, to automate the atribution of a quality score to a given spreadsheet, according to our quality model, we have integrated the computation of the metrics it includes in both a batch and a web-based tool.(undefined
Towards a catalog of spreadsheet smells
Spreadsheets are considered to be the most widely used programming language in the world, and reports have shown that 90% of real-world spreadsheets contain errors. In this work, we try to identify spreadsheet smells, a concept adapted from software, which consists of a surface indication that usually corresponds to a deeper problem. Our smells have been integrated in a tool, and were computed for a large spreadsheet repository. Finally, the analysis of the results we obtained led to the refinement of our initial catalog
Reducing Errors in Excel Models with Component-Based Software Engineering
Model errors are pervasive and can be catastrophic. We can reduce model
errors and time to market by applying Component-Based Software Engineering
(CBSE) concepts to Excel models. CBSE assembles solutions from pre-built,
pre-tested components rather than written from formulas. This is made possible
by the introduction of LAMBDA. LAMBDA is an Excel function that creates
functions from Excel's formulas. CBSE-compliant LAMBDA functions can be reused
in any project just like any Excel function. They also look exactly like
Excel's native functions such as SUM(). This makes it possible for even junior
modelers to leverage CBSE-compliant LAMBDAs to develop models quicker with
fewer errors.Comment: 27 page
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