2,602 research outputs found

    Source Code Protection for Applications Written in Microsoft Excel and Google Spreadsheet

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    Spreadsheets are used to develop application software that is distributed to users. Unfortunately, the users often have the ability to change the programming statements (“source code”) of the spreadsheet application. This causes a host of problems. By critically examining the suitability of spreadsheet computer programming languages for application development, six “application development features” are identified, with source code protection being the most important. We investigate the status of these features and discuss how they might be implemented in the dominant Microsoft Excel spreadsheet and in the new Google Spreadsheet. Although Google Spreadsheet currently provides no source code control, its web-centric delivery model offers technical advantages for future provision of a rich set of features. Excel has a number of tools that can be combined to provide “pretty good protection” of source code, but weak passwords reduce its robustness. User access to Excel source code must be considered a programmer choice rather than an attribute of the spreadsheet

    Accuracy in Spreadsheet Modelling Systems

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    Accuracy in spreadsheet modelling systems can be reduced due to difficulties with the inputs, the model itself, or the spreadsheet implementation of the model. When the true outputs from the system are unknowable, accuracy is evaluated subjectively. Less than perfect accuracy can be acceptable depending on the purpose of the model, problems with inputs, or resource constraints. Users build modelling systems iteratively, and choose to allocate limited resources to the inputs, the model, the spreadsheet implementation, and to employing the system for business analysis. When making these choices, users can suffer from expectation bias and diagnosis bias. Existing research results tend to focus on errors in the spreadsheet implementation. Because industry has tolerance for system inaccuracy, errors in spreadsheet implementations may not be a serious concern. Spreadsheet productivity may be of more interest

    Spreadsheets Grow Up: Three Spreadsheet Engineering Methodologies for Large Financial Planning Models

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    Many large financial planning models are written in a spreadsheet programming language (usually Microsoft Excel) and deployed as a spreadsheet application. Three groups, FAST Alliance, Operis Group, and BPM Analytics (under the name “Spreadsheet Standards Review Board”) have independently promulgated standardized processes for efficiently building such models. These spreadsheet engineering methodologies provide detailed guidance on design, construction process, and quality control. We summarize and compare these methodologies. They share many design practices, and standardized, mechanistic procedures to construct spreadsheets. We learned that a written book or standards document is by itself insufficient to understand a methodology. These methodologies represent a professionalization of spreadsheet programming, and can provide a means to debug a spreadsheet that contains errors. We find credible the assertion that these spreadsheet engineering methodologies provide enhanced productivity, accuracy and maintainability for large financial planning models

    A Paradigm for Spreadsheet Engineering Methodologies

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    Spreadsheet engineering methodologies are diverse and sometimes contradictory. It is difficult for spreadsheet developers to identify a spreadsheet engineering methodology that is appropriate for their class of spreadsheet, with its unique combination of goals, type of problem, and available time and resources. There is a lack of well-organized, proven methodologies with known costs and benefits for well-defined spreadsheet classes. It is difficult to compare and critically evaluate methodologies. We present a paradigm for organizing and interpreting spreadsheet engineering recommendations. It systematically addresses the myriad choices made when developing a spreadsheet, and explicitly considers resource constraints and other development parameters. This paradigm provides a framework for evaluation, comparison, and selection of methodologies, and a list of essential elements for developers or codifiers of new methodologies. This paradigm identifies gaps in our knowledge that merit further research

    Research Strategy and Scoping Survey on Spreadsheet Practices

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    We propose a research strategy for creating and deploying prescriptive recommendations for spreadsheet practice. Empirical data on usage can be used to create a taxonomy of spreadsheet classes. Within each class, existing practices and ideal practices can he combined into proposed best practices for deployment. As a first step we propose a scoping survey to gather non-anecdotal data on spreadsheet usage. The scoping survey will interview people who develop spreadsheets. We will investigate the determinants of spreadsheet importance, identify current industry practices, and document existing standards for creation and use of spreadsheets. The survey will provide insight into user attributes, spreadsheet importance, and current practices. Results will be valuable in themselves, and will guide future empirical research

    The Lookup Technique to Replace Nested-IF Formulas in Spreadsheet Programming

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    Spreadsheet programmers often implement contingent logic using a nested-IF formula even though this technique is difficult to test and audit and is believed to be risky. We interpret the programming of contingent logic in spreadsheets in the context of traditional computer programming. We investigate the “lookup technique” as an alternative to nested-IF formulas, describe its benefits for testing and auditing, and define its limitations. The lookup technique employs four distinct principles: 1) make logical tests visible; 2) make outcomes visible; 3) make logical structure visible; and 4) replace a multi-function nested-IF formula with a single-function lookup formula. It can be used only for certain simple contingent logic. We describe how the principles can be applied in more complex situations, and suggest avenues for further research

    When a Feller Needs a Friend

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    https://digitalcommons.library.umaine.edu/mmb-vp/2984/thumbnail.jp

    In Memoriam: Paul R. Rice

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