arXiv subjects

Raymond R. Panko

Publications and source records attributed to Raymond R. Panko.

7 recordsLinked to original sources

arXiv2010

The Detection of Human Spreadsheet Errors by Humans versus Inspection (Auditing) Software

Previous spreadsheet inspection experiments have had human subjects look for seeded errors in spreadsheets. In this study, subjects attempted to find errors in human-developed spreadsheets to avoid the potential artifacts created by error seeding. Human subject success rates were compared to the successful rates for error-flagging by spreadsheet static analysis tools (SSATs) applied to the same spreadsheets. The human error detection results were comparable to those of studies using error seeding. However, Excel Error Check and Spreadsheet Professional were almost useless for correctly flagging natural (human) errors in this study.

cs.SE↗

arXiv2008

Revisiting the Panko-Halverson Taxonomy of Spreadsheet Errors

The purpose of this paper is to revisit the Panko-Halverson taxonomy of spreadsheet errors and suggest revisions. There are several reasons for doing so: First, the taxonomy has been widely used. Therefore, it should have scrutiny; Second, the taxonomy has not been widely available in its original form and most users refer to secondary sources. Consequently, they often equate the taxonomy with the simplified extracts used in particular experiments or field studies; Third, perhaps as a consequence, most users use only a fraction of the taxonomy. In particular, they tend not to use the taxonomy's life-cycle dimension; Fourth, the taxonomy has been tested against spreadsheets in experiments and spreadsheets in operational use. It is time to review how it has fared in these tests; Fifth, the taxonomy was based on the types of spreadsheet errors that were known to the authors in the mid-1990s. Subsequent experience has shown that the taxonomy needs to be extended for situations beyond those original experiences; Sixth, the omission category in the taxonomy has proven to be too narrow. Although this paper will focus on the Panko-Halverson taxonomy, this does not mean that that it is the only possible error taxonomy or even the best error taxonomy.

cs.SE↗

arXiv2008

Reducing Overconfidence in Spreadsheet Development

Despite strong evidence of widespread errors, spreadsheet developers rarely subject their spreadsheets to post-development testing to reduce errors. This may be because spreadsheet developers are overconfident in the accuracy of their spreadsheets. This conjecture is plausible because overconfidence is present in a wide variety of human cognitive domains, even among experts. This paper describes two experiments in overconfidence in spreadsheet development. The first is a pilot study to determine the existence of overconfidence. The second tests a manipulation to reduce overconfidence and errors. The manipulation is modestly successful, indicating that overconfidence reduction is a promising avenue to pursue.

cs.HC↗

arXiv2008

Sarbanes-Oxley: What About all the Spreadsheets?

The Sarbanes-Oxley Act of 2002 has finally forced corporations to examine the validity of their spreadsheets. They are beginning to understand the spreadsheet error literature, including what it tells them about the need for comprehensive spreadsheet testing. However, controlling for fraud will require a completely new set of capabilities, and a great deal of new research will be needed to develop fraud control capabilities. This paper discusses the riskiness of spreadsheets, which can now be quantified to a considerable degree. It then discusses how to use control frameworks to reduce the dangers created by spreadsheets. It focuses especially on testing, which appears to be the most crucial element in spreadsheet controls.

cs.SE↗

arXiv2008

Spreadsheet Errors: What We Know. What We Think We Can Do

Fifteen years of research studies have concluded unanimously that spreadsheet errors are both common and non-trivial. Now we must seek ways to reduce spreadsheet errors. Several approaches have been suggested, some of which are promising and others, while appealing because they are easy to do, are not likely to be effective. To date, only one technique, cell-by-cell code inspection, has been demonstrated to be effective. We need to conduct further research to determine the degree to which other techniques can reduce spreadsheet errors.

cs.SE↗

arXiv2008

Thinking is Bad: Implications of Human Error Research for Spreadsheet Research and Practice

In the spreadsheet error community, both academics and practitioners generally have ignored the rich findings produced by a century of human error research. These findings can suggest ways to reduce errors; we can then test these suggestions empirically. In addition, research on human error seems to suggest that several common prescriptions and expectations for reducing errors are likely to be incorrect. Among the key conclusions from human error research are that thinking is bad, that spreadsheets are not the cause of spreadsheet errors, and that reducing errors is extremely difficult.

cs.HC↗

arXiv2007

Recommended Practices for Spreadsheet Testing

This paper presents the authors recommended practices for spreadsheet testing. Documented spreadsheet error rates are unacceptable in corporations today. Although improvements are needed throughout the systems development life cycle, credible improvement programs must include comprehensive testing. Several forms of testing are possible, but logic inspection is recommended for module testing. Logic inspection appears to be feasible for spreadsheet developers to do, and logic inspection appears to be safe and effective.

cs.SE↗