An Empirical Study of End-User Behaviour in Spreadsheet Error Detection & Correction

Very little is known about the process by which end-user developers detect and correct spreadsheet errors. Any research pertaining to the development of spreadsheet testing methodologies or auditing tools would benefit from information on how end-users perform the debugging process in practice. Thirteen industry-based professionals and thirty-four accounting & finance students took part in a current ongoing experiment designed to record and analyse end-user behaviour in spreadsheet error detection and correction. Professionals significantly outperformed students in correcting certain error types. Time-based cell activity analysis showed that a strong correlation exists between the percentage of cells inspected and the number of errors corrected. The cell activity data was gathered through a purpose written VBA Excel plug-in that records the time and detail of all cell selection and cell change actions of individuals.Comment: 12 Pages, 3 Figure

An Insight into Spreadsheet User Behaviour through an Analysis of EuSpRIG Website Statistics

The European Spreadsheet Risks Interest Group (EuSpRIG) has maintained a website almost since its inception in 2000. We present here longitudinal and cross-sectional statistics from the website log in order to shed some light upon end-user activity in the EuSpRIG domain.Comment: 10 Pages, 5 Tables, 2 Colour Figures, ISBN 978-0-9566256-9-

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.Comment: 12 pages including reference

A Toolkit for Scalable Spreadsheet Visualization

This paper presents a toolkit for spreadsheet visualization based on logical areas, semantic classes and data modules. Logical areas, semantic classes and data modules are abstract representations of spreadsheet programs that are meant to reduce the auditing and comprehension effort, especially for large and regular spreadsheets. The toolkit is integrated as a plug-in in the Gnumeric spreadsheet system for Linux. It can process large, industry scale spreadsheet programs in reasonable time and is tightly integrated with its host spreadsheet system. Users can generate hierarchical and graph-based representations of their spreadsheets. This allows them to spot conceptual similarities in different regions of the spreadsheet, that would otherwise not fit on a screen. As it is assumed that the learning effort for effective use of such a tool should be kept low, we aim for intuitive handling of most of the tool's functions.Comment: 12 Page

Towards a Spreadsheet Engineering

In this paper, we report some on-going focused research, but are further keen to set it in the context of a proposed bigger picture, as follows. There is a certain depressing pattern about the attitude of industry to spreadsheet error research and a certain pattern about conferences highlighting these issues. Is it not high time to move on from measuring spreadsheet errors to developing an armoury of disciplines and controls? In short, we propose the need to rigorously lay the foundations of a spreadsheet engineering discipline. Clearly, multiple research teams would be required to tackle such a big task. This suggests the need for both national and international collaborative research, since any given group can only address a small segment of the whole. There are already a small number of examples of such on-going international collaborative research. Having established the need for a directed research effort, the rest of the paper then attempts to act as an exemplar in demonstrating and applying this focus. With regard to one such of research, in a recent paper, Panko (2005) stated that: "...group development and testing appear to be promising areas to pursue". Of particular interest to us are some gaps in the published research record on techniques to reduce errors. We further report on the topics: techniques for cross-checking, time constraints effects, and some aspects of developer perception.Comment: 12 Pages, One Figur

Applying the CobiT Control Framework to Spreadsheet Developments

One of the problems reported by researchers and auditors in the field of spreadsheet risks is that of getting and keeping managements attention to the problem. Since 1996, the Information Systems Audit & Control Foundation and the IT Governance Institute have published CobiT which brings mainstream IT control issues into the corporate governance arena. This paper illustrates how spreadsheet risk and control issues can be mapped onto the CobiT framework and thus brought to managers attention in a familiar format.Comment: 6 Page

Establishing and Measuring Standard Spreadsheet Practices for End-Users

This paper offers a brief review of cognitive verbs typically used in the literature to describe standard spreadsheet practices. The verbs identified are then categorised in terms of Bloom's Taxonomy of Hierarchical Levels, and then rated and arranged to distinguish some of their qualities and characteristics. Some measurement items are then evaluated to see how well computerised test question items validate or reinforce training or certification. The paper considers how establishing standard practices in spreadsheet training and certification can help reduce some of the risks associated with spreadsheets, and help promote productivity.Comment: 15 Pages, 5 Tables, 9 Colour Figure

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.Comment: 14 Pages, 4 Figure

Using Layout Information for Spreadsheet Visualization

This paper extends a spreadsheet visualization technique by using layout information. The original approach identifies logically or semantically related cells by relying exclusively on the content of cells for identifying semantic classes. A disadvantage of semantic classes is that users have to supply parameters which describe the possible shapes of these blocks. The correct parametrization requires a certain degree of experience and is thus not suitable for untrained users. To avoid this constraint, the approach reported in this paper uses row/column-labels as well as common format information for locating areas with common, recurring semantics. Heuristics are provided to distinguish between cell groups with intended common semantics and cell groups related in an ad-hoc manner.Comment: 13 pages, 3 colour figure

Error Estimation in Large Spreadsheets using Bayesian Statistics

Spreadsheets are ubiquitous in business with the financial sector particularly heavily reliant on the technology. It is known that the level of spreadsheet error can be high and that it is often necessary to review spreadsheets based on a structured methodology which includes a cell by cell examination of the spreadsheet. This paper outlines the early research that has been carried out into the use of Bayesian Statistical methods to estimate the level of error in large spreadsheets during cell be cell examination based on expert knowledge and partial spreadsheet test data. The estimate can aid in the decision as to the quality of the spreadsheet and the necessity to conduct further testing or not.Comment: 12 Pages, 5 Colour Figure