Spreadsheets are widely used within companies and often form the basis for business decisions. Numerous cases are known where incorrect information in spreadsheets has lead to incorrect decisions. Such cases underline the relevance of research on the professional use of spreadsheets. Recently a new dataset became available for research, containing over 15.000 business spreadsheets that were extracted from the Enron E-mail Archive. With this dataset, we 1) aim to obtain a thorough understanding of the characteristics of spreadsheets used within companies, and 2) compare the characteristics of the Enron spreadsheets with the EUSES corpus which is the existing state of the art set of spreadsheets that is frequently used in spreadsheet studies. Our analysis shows that 1) the majority of spreadsheets are not large in terms of worksheets and formulas, do not have a high degree of coupling, and their formulas are relatively simple; 2) the spreadsheets from the EUSES corpus are, with respect to the measured characteristics, quite similar to the Enron spreadsheets.
Although spreadsheet programs are used for small "scratchpad" applications, they are also used to develop many large applications. In recent years, we have learned a good deal about the errors that people make when they develop spreadsheets. In general, errors seem to occur in a few percent of all cells, meaning that for large spreadsheets, the issue is how many errors there are, not whether an error exists. These error rates, although troubling, are in line with those in programming and other human cognitive domains. In programming, we have learned to follow strict development disciplines to eliminate most errors. Surveys of spreadsheet developers indicate that spreadsheet creation, in contrast, is informal, and few organizations have comprehensive policies for spreadsheet development. Although prescriptive articles have focused on such In recent years several tools and methodologies have been developed to improve the dependability of spreadsheets. However, there has been little evaluation of these dependability devices on spreadsheets in actual use by end users. To assist in the process of evaluating these methodologies, we have assembled a corpus of spreadsheets from a variety of sources. We have ensured that these spreadsheets are suitable for evaluating dependability devices in Microsoft Excel (the most commonly used commercial spreadsheet environment) and have measured a variety of feature of these spreadsheets to aid researchers in selecting subsets of the corpus appropriate to their needs. Legacy spreadsheets are both, an asset, and an enduring problem concerning spreadsheets in business. To make spreadsheets stay alive and remain correct, comprehension of a given spreadsheet is highly important. Visualization techniques should ease the complex and mindblowing challenges of finding structures in a huge set of spreadsheet cells for building an adequate mental model of spreadsheet programs. Since spreadsheet programs are as diverse as the purpose they are serving and as inhomogeneous as their programmers, to find an appropriate representation or visualization technique for every spreadsheet program seems futile. We thus propose different visualization and representation methods that may ease spreadsheet comprehension but should not be applied with all kind of spreadsheet programs. Therefore, this paper proposes to use (complexity) measures as indicators for proper visualization.