Errors in spreadsheets... result in incorrect decisions being made and significant losses incurred.
Beaman, et al (2005)
Spreadsheet errors are still the rule rather than the exception.
Nixon & O'Hara (2010)
Spreadsheet errors... a great, often unrecognised, risk to corporate decision making & financial integrity.
Chadwick (2002)
Untested spreadsheets are riddled with errors.
Miller (2005)
A significant proportion of spreadsheets have severe quality problems.
Ayalew (2007)
Spreadsheets are dangerous to their authors and others.
Durusau & Hunting (2015)
Even obvious, elementary errors in very simple, clearly documented spreadsheets are... difficult to find.
Galletta, et al (1993)
Spreadsheet errors are pervasive, stubborn, ubiquitous and complex.
Irons (2003)
Spreadsheets are commonly used and commonly flawed.
Caulkins, Morrison, & Weidemann (2008)
Despite overwhelming and unanimous evidence... companies have continued to ignore spreadsheet error risks.
Panko (2014)
Spreadsheets are notoriously error-prone.
Cunha, et al (2011)
Never assume a spreadsheet is right, even your own.
Raffensperger (2001)
The untested spreadsheet is as dangerous and untrustworthy as an untested program.
Price (2006)
Your spreadsheets may be disasters in the making.
Caulkins, Morrison, & Weidemann (2006)
It is now widely accepted that errors in spreadsheets are both common and potentially dangerous.
Nixon & O'Hara (2010)
Spreadsheets are alarmingly error-prone to write.
Paine (2001)
Spreadsheets are extraordinarily and unacceptably prone to error.
Dunn (2010)
Spreadsheets... pose a greater threat to your business than almost anything you can imagine.
Howard (2005)
Research on spreadsheet errors is substantial, compelling, and unanimous.
Panko (2015)
The results given by spreadsheets are often just wrong.
Sajaniemi (1998)
Errors in spreadsheets are as ubiquitous as spreadsheets themselves.
Colbenz (2005)
A lot of decisions are being made on the basis of some bad numbers.
Ross (1996)
...few incidents of spreadsheet errors are made public and these are usually not revealed by choice.
Kruck & Sheetz (2001)
94% of the 88 spreadsheets audited in 7 studies have contained errors.
Panko (2008)
Every study, without exception, has found error rates much higher than organizations would wish to tolerate.
Panko (1999)
Spreadsheets contain errors at an alarmingly high rate.
Abraham, et al (2005)
Studies have shown that there is a high incidence of errors in spreadsheets.
Csernoch & Biro (2013)
Spreadsheets are the most popular live programming environments, but they are also notoriously fault-prone.
Hermans & van der Storm (2015)
Every study that has looked for errors has found them... in considerable abundance.
Panko & Halverson (1996)
Spreadsheets have a notoriously high number of faults.
Rust, et al (2006)
Most large spreadsheets have dozens or even hundreds of errors.
Panko & Ordway (2005)
Spreadsheets are more fault-prone than other software.
Kulesz & Ostberg (2013)
1% of all formulas in operational spreadsheets are in error.
Powell, Baker, & Lawson (2009)
It is irrational to expect large error-free spreadsheets.
Panko (2013)
Spreadsheets are easy to use and very hard to check.
Chen & Chan (2000)
Programmers exhibit unwarranted confidence in the correctness of their spreadsheets.
Krishna, et al (2001)
Spreadsheet development must embrace extensive testing in order to be taken seriously as a profession.
Bock (2016)
The quality and reliability of spreadsheets is known to be poor.
Bishop & McDaid (2007)
Most executives do not really check or verify the accuracy or validity of [their] spreadsheets...
Teo & Tan (1999)
60% of large companies feel 'Spreadsheet Hell' describes their reliance on spreadsheets.
Murphy (2007)
Developing an error-free spreadsheet has been a problem since the beginning of end-user computing.
Mireault (2015)
People tend to believe their spreadsheets are more accurate than they really are.
Caulkins, Morrison, & Weidemann (2006)
Despite being staggeringly error prone, spreadsheets are a highly flexible programming environment.
Abreu, et al (2015)
Spreadsheet errors have resulted in huge financial losses.
Abraham & Erwig (2007)
The issue is not whether there is an error but how many errors there are and how serious they are.
Panko (2007)
Spreadsheets can be viewed as a highly flexible programming environment for end users.
Abreu, et al (2015)
Overconfidence is one of the most substantial causes of spreadsheet errors.
Sakal, et al (2015)
Spreadsheet shortcomings can significantly hamper an organization's business operation.
Reschenhofer & Matthes (2015)
Spreadsheets are often hard, if not impossible, to understand.
Mireault & Gresham (2015)
The software that end users are creating... is riddled with errors.
Burnett & Myers (2014)

Spreadsheet bibliography

This is a bibliography of literature about spreadsheet best practice, spreadsheet risk management, spreadsheet errors and testing, and methods for improving the robustness and reliability of spreadsheets.

If you are aware of any relevant items that are missing, then please let us know.

Total items in bibliography:


DetailsCsernoch. Thinking fast and slow in computer problem solving
DetailsFrownfelter-Lohrke. Teaching good Excel design and skills: A three spreadsheet assignment project
DetailsHofer, Hofler, & Wotawa. Combining models for improved fault localization in spreadsheets
DetailsJansen & Hermans. The effect of delocalized plans on spreadsheet comprehension - A controlled experiment
DetailsKulesz, Kafer, & Wagner. Spreadsheet Guardian: An approach for protecting semantic correctness throughout the evolution of spreadsheets
DetailsRoy, Hermans, & van Deursen. Spreadsheet testing in practice
DetailsSchneider, Becker, & Berg. Beyond the mechanics of spreadsheets: Using design instruction to address spreadsheet errors
DetailsSingh, Livshits, & Zorn. Melford: Using neural networks to find spreadsheet errors
DetailsZhang et al. How effectively can spreadsheet anomalies be detected: An empirical study


DetailsAbreu, Cunha, Fernandes, Martins, Perez, & Saraiva. Combining smells and fault localization in spreadsheets
DetailsBartholomew. A structured approach to the development of solutions in Excel
DetailsBock. A literature review of spreadsheet technology
DetailsCheung, Chen, Liu, & Xu. CUSTODES: Automatic spreadsheet cell clustering and smell detection using strong and weak features
DetailsCooke, Blackwell, & Brown. A graphical trap for unwary users of Excel 2010
DetailsCunha, Fernandes, Martins, Mendes, Pereira, & Saraiva. Evaluating refactorings for spreadsheet models
DetailsDou et al. Detecting table clones and smells in spreadsheets
DetailsDou et al. VEnron: A versioned spreadsheet corpus and related evolution analysis
DetailsDou et al. CACheck: Detecting and repairing cell arrays in spreadsheets
DetailsHermans, Jansen, Roy, Aivaloglou, Swidan, & Hoepelman. Spreadsheets are code: An overview of software engineering approaches applied to spreadsheets
DetailsJannach & Schmitz. Model-based diagnosis of spreadsheet programs: A constraint-based debugging approach
DetailsJansen & Hermans. The effect of delocalized plans on the maintainability of spreadsheets
DetailsKankuzi & Sajaniemia. A mental model perspective for tool development and paradigm shift in spreadsheets
DetailsOlusegun. Accountants' perceptions of the use of Excel spreadsheet in financial reporting
DetailsPereira, Saraiva, Cunha, & Fernandes. User-friendly spreadsheet querying: An empirical study
DetailsReschenhofer, Waltl, Gjorgievska, & Matthes. A semantic meta model of spreadsheets
DetailsReschenhofer, Waltl, Shumaiev, & Matthes. A conceptual model for measuring the complexity of spreadsheets
DetailsSakal, Rakovic, & Tumbas. Taxonomies of spreadsheet errors as content of spreadsheet related courses
DetailsSakal, Rakovic, & Vukovic. End user software engineering
DetailsSchmitz & Jannach. Finding errors in the Enron spreadsheet corpus


DetailsAbreu, Ausserlechner, Hofer, & Wotawa. Testing for distinguishing repair candidates in spreadsheets – the Mussco approach
DetailsAbreu, Hofer, Perez, & Wotawa. Using constraints to diagnose faulty spreadsheets
DetailsAivaloglou, Hoepelman, & Hermans. A grammar for spreadsheet formulas evaluated on two large datasets
DetailsAntunes, Correa, & Barros. Automatic spreadsheet generation from conceptual models
DetailsBiro & Csernoch. The mathability of spreadsheet tools
DetailsCsernoch & Biro. Problem solving in Sprego
DetailsCsernoch & Biro. Sprego programming
DetailsCunha, Fernandes, Mendes, & Saraiva. Spreadsheet engineering
DetailsDurusau & Hunting. Spreadsheets - 90+ million end user programmers with no comment tracking or version control
DetailsGetzner. Improvements for spectrum-based fault localization in spreadsheets
DetailsGrossman & Burd. Towards reusable spreadsheet code: Experiments to create and interchange encapsulated Excel modules
DetailsHermans, Aivaloglou, & Jansen. Detecting problematic lookup functions in spreadsheets
DetailsHermans & Murphy-Hill. Enron's spreadsheets and related emails: A dataset and analysis
DetailsHermans, Pinzger, & van Deursen. Detecting and refactoring code smells in spreadsheet formulas
DetailsHermans & van der Storm. Copy-paste tracking: Fixing spreadsheets without breaking them
DetailsHoepelman. Tool-assisted spreadsheet refactoring and parsing spreadsheet formulas
DetailsHofer, Perez, Abreu, & Wotawa. On the empirical evaluation of similarity coefficients for spreadsheets fault localization
DetailsHofer & Wotawa. Fault localization in the light of faulty user input
DetailsJansen. Enron versus EUSES: A comparison of two spreadsheet corpora
DetailsJansen & Hermans. Code smells in spreadsheet formulas revisited on an industrial dataset
DetailsKankuzi. Deficiencies in spreadsheets: A mental model perspective
DetailsKoch. Smells and units: An overview of selected static analysis methods for spreadsheets
DetailsKohlhase, Kohlhase, & Guseva. Context in spreadsheet comprehension
DetailsKulesz, Toth, & Beck. Live inspection of spreadsheets
DetailsLeon, Przasnyski, & Seal. Introducing a taxonomy for classifying qualitative spreadsheet errors
DetailsMeservy & Romney. How to debug Excel spreadsheets
DetailsMiller. The spreadsheet paradigm: A basis for powerful and accessible programming
DetailsMireault. Developing a repeating model using the structured spreadsheet modelling and implementation methodology
DetailsMireault. Structured spreadsheet modeling and implementation
DetailsMireault & Gresham. Governance and structured spreadsheets: Your spreadsheets don't need to be black boxes
DetailsPanko. What we don't know about spreadsheet errors today: The facts, why we don't believe them, and what we need to do
DetailsRakovic, Sakal, Tumbas, Matkovic, & Pavlicevic. Improvement of spreadsheet skills in business-oriented university courses
DetailsReschenhofer & Matthes. A framework for the identification of spreadsheet usage patterns
DetailsReschenhofer & Matthes. An empirical study on spreadsheet shortcomings from an information systems perspective
DetailsSakal, Rakovic, Matkovic, Tumbas, & Pavlicevic. Reducing spreadsheet users' overconfidence through business oriented university courses
DetailsSchalkwijk, Hermans, van der Ven, & Duits. Auditing spreadsheets: With or without a tool?
DetailsShubbak & Thorne. Development and experimentation of a software tool for identifying high risk spreadsheets for auditing
DetailsToader, Kohlhase, & Kohlhase. Managing knowledge for assessing spreadsheet-based models


DetailsAurigemma & Panko. Evaluating the effectiveness of static analysis programs versus manual inspection in the detection of natural spreadsheet errors
DetailsBarowy, Gochev, & Berger. CheckCell: Data debugging for spreadsheets
DetailsBurnett & Myers. Future of end-user software engineering: Beyond the silos
DetailsCunha, Erwig, Mendes, & Saraiva. Model inference for spreadsheets
DetailsCunha, Fernandes, Mendes, Pereira, & Saraiva. MDSheet - Model-driven spreadsheets
DetailsDou, Cheung, & Wei. Is spreadsheet ambiguity harmful? Detecting and repairing spreadsheet smells due to ambiguous computation
DetailsDzuranin & Slater. Business risks all identified? If you're using a spreadsheet, think again
DetailsGetzner. Survey of fault localization techniques for spreadsheets
DetailsHofer, Abreu, Perez, & Wotawa. Generation of relevant spreadsheet repair candidates
DetailsHofer, Jannach, Schmitz, Shchekotykhin, & Wotawa. Tool-supported fault localization in spreadsheets: Limitations of current research practice
DetailsHofer & Wotawa. Why does my spreadsheet compute wrong values?
DetailsJannach, Schmitz, Hofer, & Wotawa. Avoiding, finding and fixing spreadsheet errors: A survey of automated approaches for spreadsheet QA
DetailsJansen & Hermans. Using a visual language to create better spreadsheets
DetailsKulesz. A spreadsheet cell-meaning model for testing
DetailsKulesz, Scheurich, & Beck. Integrating anomaly diagnosis techniques into spreadsheet environments
DetailsLeitao & Roast. Developing visualisations for spreadsheet formulae: Towards increasing the accessibility of science, technology, engineering and maths subjects
DetailsMartins & Pereira. Refactoring smelly spreadsheet models
DetailsMinter & Correia. The governance of risk arising from the use of spreadsheets in organisations
DetailsPaige, Kolovos, & Matragkas. Spreadsheets are models too
DetailsPanko. Are we overconfident in our understanding of overconfidence?
DetailsPanko. Improving methodology in spreadsheet error research
DetailsPoon, Kuo, Liu, & Chen. How can non-technical end users effectively test their spreadsheets?
DetailsRakovic, Sakal, & Pavlicevic. Spreadsheets - How it started
DetailsRoy & Hermans. Dependence tracing techniques for spreadsheets: An investigation
DetailsSakal, Rakovic, Matkovic, Tumbas, & Pavlicevic. Spreadsheets as a source of analytical and accounting problems
DetailsSakal, Rakovic, & Pantelic. Errors in user developed applications


DetailsAllen. Spatial modelling techniques in Microsoft Excel
DetailsAusserlechner, et al. The right choice matters! SMT solving substantially improves model-based debugging of spreadsheets
DetailsBirch, et al. Multidisciplinary engineering models: Methodology and case study in spreadsheet analytics
DetailsCsernoch & Biro. Spreadsheet misconceptions, spreadsheet errors
DetailsFrancis, Kolovos, Matragkas, & Paige. Adding spreadsheets to the MDE toolkit
DetailsHawkins, Lemon, & Gibson. Introducing Morphit, a new type of spreadsheet technology
DetailsHermans. Improving spreadsheet test practices
DetailsHermans & Dig. BumbleBee: A transformation environment for spreadsheet formulas
DetailsHofer, et al. On the empirical evaluation of fault localization techniques for spreadsheets
DetailsHofer & Wotawa. Mutation-based spreadsheet debugging
DetailsJannach, Baharloo, & Williamson. Toward an integrated framework for declarative and interactive spreadsheet debugging
DetailsKadijevich. Inappropriate use of spreadsheets in the finance industry
DetailsKankuzi & Sajaniemi. An empirical study of spreadsheet authors' mental models in explaining and debugging tasks
DetailsKohlhase. Human-spreadsheet interaction
DetailsKohlhase & Prodescu. XLSearch: A search engine for spreadsheets
DetailsKohlhase & Toader. Exploration of spreadsheet formulae with Fency
DetailsKulesz & Ostberg. Practical challenges with spreadsheet auditing tools
DetailsMusliu, Slany, & Gartner. Automated test case generation in end-user programming
DetailsO'Beirne. Excel 2013 spreadsheet Inquire
DetailsPanko. The cognitive science of spreadsheet errors: Why thinking is bad
DetailsSilva. Directed evolution of model-driven spreadsheets
DetailsStewart. Self-checking spreadsheets: Recognition of semantics
DetailsThomas. Managing document risk to protect the company's reputation
DetailsThorne, Ball, & Lawson. Reducing error in spreadsheets: Example driven modelling versus traditional programming
DetailsVlootman & Hermans. A maintainability checklist for spreadsheets


DetailsAbreu, Riboira, & Wotawa. Constraint-based debugging of spreadsheets
DetailsAsavametha. Detecting bad smells in spreadsheets
DetailsBadame. Refactoring meets spreadsheet formulas
DetailsBadame & Dig. Refactoring meets spreadsheet formulas
DetailsChan, Goswami, & Kim. An alternative fit through problem representation in cognitive fit theory
DetailsCheng & Rival. An abstract domain to infer types over zones in spreadsheets
DetailsCuff. Design and documentation of real estate spreadsheets - Part 1
DetailsCunha, Fernandes, Martins, Mendes, & Saraiva. SmellSheet Detective: A tool for detecting bad smells in spreadsheets
DetailsCunha, Fernandes, Mendes, & Saraiva. MDSheet: A framework for model-driven spreadsheet engineering
DetailsCunha, Fernandes, Mendes, & Saraiva. Extension and implementation of ClassSheet models
DetailsCunha, Fernandes, Peixoto, & Saraiva. A quality model for spreadsheets
DetailsCunha, Fernandes, Ribeiro, & Saraiva. Towards a catalog of spreadsheet smells
DetailsCunha, Saraiva, & Visser. Model-based programming environments for spreadsheets
DetailsFernandez-Soriano, Marino, & Herranz. A tool for the integration of constraint solving in spreadsheets
DetailsFerreira & Visser. Governance of spreadsheets through spreadsheet change reviews
DetailsGabbay. Controlling critical spreadsheets using ESM (Enterprise Spreadsheet Management) system
DetailsGilbert. Managing spreadsheet risk
DetailsGrigoreanu, Burnett, Wiedenbeck, Cao, Rector, & Kwan. End-user debugging strategies: A sensemaking perspective
DetailsHarutyunyan, Borradaile, Chambers, & Scaffidi. Planted-model evaluation of algorithms for identifying differences between spreadsheets
DetailsHermans. Analyzing and visualizing spreadsheets
DetailsHermans, Pinzger, & van Deursen. Measuring spreadsheet formula understandability
DetailsHermans, Sedee, Pinzger, & van Deursen. Data clone detection and visualization in spreadsheets
DetailsKadijevich. Examining errors in simple spreadsheet modeling from different research perspectives
DetailsKohlhase & Kohlhase. Spreadsheets with a semantic layer
DetailsKulesz & Zitzelsberger. Investigating effects of common spreadsheet design practices on correctness and maintainability
DetailsLiguda. Modeling the structure of spreadsheets
DetailsLuckey, Erwig, & Engels. Systematic evolution of model-based spreadsheet applications
DetailsLueg & Shijia. Improving efficiency in budgeting – an interventionist approach to spreadsheet accuracy testing
DetailsMaditinos, Chatzoudes, & Tsairidis. Spreadsheet error detection: An empirical examination in the context of Greece
DetailsPanko & Port. End user computing: The dark matter (and dark energy) of corporate IT
DetailsSakal & Rakovic. Errors in building and using electronic tables: Financial consequences and minimisation techniques
DetailsStambaugh, Tipgos, Carpenter, & Smith. Using Benford analysis to detect fraud
DetailsThimbleby. Heedless programming: Ignoring detectable error is a widespread hazard
DetailsThorne. The misuse of spreadsheets in the nuclear fuel industry
DetailsWalters & Pergola. Integrating critical spreadsheet competencies into the accounting curriculum


DetailsAdkins. Cognitive skills, domain knowledge, and self-efficacy: Effects on spreadsheet quality
DetailsBaskarada. How spreadsheet applications affect information quality
DetailsBeckwith, Cunha, Fernandes, & Saraiva. An empirical study on end-users productivity using model-based spreadsheets
DetailsCaputi, Chan, & Jayasuriya. How helpful are error management and counterfactual thinking instructions to inexperienced spreadsheet users' training task performance?
DetailsColver. Drivers of the cost of spreadsheet audit
DetailsCorreia & Ferreira. Measuring maintainability of spreadsheets in the wild
DetailsCorreia & Ferreira. Requirements for automated assessment of spreadsheet maintainability
DetailsCorreia & Minter. The role of spreadsheet model design in corporate finance courses
DetailsCoster, Leon, Kalbers, & Abraham. Controls over spreadsheets for financial reporting in practice
DetailsCunha, Visser, Alves, & Saraiva. Type-safe evolution of spreadsheets
DetailsDewey. Error Sentinel: A rule-based spreadsheet program for intelligent data entry, error correction, and curation
DetailsGrossman, Mehrotra, & Sander. Towards evaluating the quality of a spreadsheet: The case of the analytical spreadsheet model
DetailsHermans, Pinzger, & van Deursen. Detecting and visualizing inter-worksheet smells in spreadsheets
DetailsHermans, Pinzger, & van Deursen. Detecting code smells in spreadsheet formulas
DetailsHill & Barnes. End-user computing applications
DetailsKo, et al. The state of the art in end-user software engineering
DetailsKulesz. From good practices to effective policies for preventing errors in spreadsheets
DetailsMadahar. Spreadsheet use for strategic decision-making: An analysis of spreadsheet use and associated risk
DetailsMcDaid, et al. Spreadsheets in financial departments: An automated analysis of 65,000 spreadsheets using the Luminous technology
DetailsMcKeever & McDaid. Effect of range naming conventions on reliability and development time for simple spreadsheet formulas
DetailsMendes. ClassSheet-driven spreadsheet environments
DetailsMoreno & Juhasz. To err or not - consequences of spreadsheet errors and how to avoid them
DetailsNaini. Inferring templates from spreadsheets
DetailsPeixoto. Quality model for spreadsheets
DetailsPrzasnyski, Leon, & Seal. In search of a taxonomy for classifying qualitative spreadsheet errors
DetailsRawat. Analyses of bioenergy systems: Detecting hard-coding errors in spreadsheets, and comparing biofuel cropping systems
DetailsRibeiro. Spreadsheet smells
DetailsVisser. Spreadsheets: Swiss pocket knife or boomerang?
DetailsWiseman, Cairns, & Cox. A taxonomy of number entry error


DetailsAurigemma & Panko. The detection of human spreadsheet errors by humans versus inspection (auditing) software
DetailsBalson. Changing user attitudes to reduce spreadsheet risk
DetailsCampbell. Spreadsheet issues: Pitfalls, best practices, and practical tips
DetailsChambers. Dimension checking tools for spreadsheets
DetailsChambers & Erwig. Reasoning about spreadsheets with labels and dimensions
DetailsChambers & Scaffidi. Struggling to excel: A field study of challenges faced by spreadsheet users
DetailsChan, Caputi, Hilellis, Zhu, & Jayasuriya. Applying an error taxonomy to examine inexperienced spreadsheet users' planning and execution errors
DetailsChilcott, et al. Avoiding and identifying errors in health technology assessment models
DetailsCunha. Model-based spreadsheet engineering
DetailsDunn. Spreadsheets - the good, the bad and the downright ugly
DetailsGalbreth & LeBlanc. Overcoming spreadsheet risk in supply chain modeling
DetailsGesher. The hidden risk
DetailsGrossman & Ozluk. Spreadsheets grow up: Three spreadsheet engineering methodologies for large financial planning models
DetailsHermans, Pinzger, & van Deursen. Automatically extracting class diagrams from spreadsheets
DetailsHermans, Pinzger, & van Deursen. Breviz: Spreadsheet visualization and quality analysis
DetailsJannach & Engler. Toward model-based debugging of spreadsheet programs
DetailsKohlhase & Kohlhase. What we understand is what we get: Assessment in spreadsheets
DetailsLeon, Abraham, & Kalbers. Beyond regulatory compliance for spreadsheet controls: A tutorial to assist practitioners and a call for research
DetailsMcKeever & McDaid. How do range names hinder novice debugging performance?
DetailsO'Beirne. Spreadsheet refactoring
DetailsPanko & Aurigemma. Revising the Panko-Halverson taxonomy of spreadsheet errors
DetailsPeacock. Spreadsheet risk
DetailsRawat, Raman, & Anex. Detecting and categorizing hard-coding errors in Excel spreadsheets using Visual Basic for Applications (VBA)
DetailsRittweger & Langan. Spreadsheet risk management in organisations
DetailsStoller. Spreadsheet users often lack advanced design capabilities
DetailsThimbleby & Cairns. Reducing number entry errors: Solving a widespread, serious problem
DetailsThorne. Defending the future: An MSc module in end user computing risk management


DetailsAbraham, Burnett, & Erwig. Spreadsheet programming
DetailsAbraham & Erwig. Mutation operators for spreadsheets
DetailsAllan. Excel modelling: Transparency, auditing and business use
DetailsBarnes, Tufte, & Christensen. Spreadsheet design: An optimal checklist for accountants
DetailsBekenn & Hooper. Some spreadsheet Poka-Yoke
DetailsBradley & McDaid. Error estimation in large spreadsheets using Bayesian statistics
DetailsButler. The role of spreadsheets in the Allied Irish Bank / Allfirst currency trading fraud
DetailsChambers & Erwig. Automatic detection of dimension errors in spreadsheets
DetailsCognos. Spreadsheet-based planning in today's economy: Why you're up against the wall
DetailsCroll. Spreadsheets and the financial collapse
DetailsCunha, Saraiva, & Visser. Discovery-based edit assistance for spreadsheets
DetailsDeloitte. Spreadsheet management - not what you figured
DetailsDunn. Automated spreadsheet development
DetailsErwig. Software engineering for spreadsheets
DetailsGrigoreanu. Understanding and supporting end-user debugging strategies
DetailsGrossman, Ozluk, & Gustavson. The lookup technique to replace nested-IF formulas in spreadsheet programming
DetailsHihn, Lewicki, & Wilkinson. How spreadsheets get us to Mars and beyond
DetailsHunt. An approach for the automated risk assessment of structural differences between spreadsheets (DiffXL)
DetailsKohlhase & Kohlhase. Compensating the computational bias of spreadsheets with MKM techniques
DetailsLawson, Baker, Powell, & Foster-Johnson. A comparison of spreadsheet users with different levels of experience
DetailsMcKay. Reducing spreadsheet errors
DetailsMcKeever, McDaid, & Bishop. An exploratory analysis of the impact of named ranges on the debugging performance of novice users
DetailsMukherjee. The good, the bad, and the ugly
DetailsO'Beirne. Checks and controls in spreadsheets
DetailsPanko. Two experiments in reducing overconfidence in spreadsheet development
DetailsPowell, Baker, & Lawson. Errors in operational spreadsheets
DetailsPowell, Baker, & Lawson. Impact of errors in operational spreadsheets
DetailsThorne & Ball. A review of spreadsheet error reduction techniques
DetailsTort, Blondel, & Bruillard. From error detection to behaviour observation: First results from screen capture analysis


DetailsAbraham & Erwig. Test-driven goal-directed debugging in spreadsheets
DetailsAccess Analytic. 52 easy ways to prevent spreadsheet problems
DetailsAnastasakis, Olphert, & Wilson. Experiences in using a contingency factor-based validation methodology for spreadsheet DSS
DetailsBaker, Powell, Lawson, & Foster-Johnson. Comparison of characteristics and practices amongst spreadsheet users with different levels of experience
DetailsBekenn & Hooper. Reducing spreadsheet risk with FormulaDataSleuth
DetailsBishop & McDaid. Spreadsheet end-user behaviour analysis
DetailsBurdick. Improving spreadsheet audits in six steps
DetailsCarpenter. No more the humble spreadsheet?
DetailsCaulkins, Morrison, & Weidemann. Do spreadsheet errors lead to bad decisions: Perspectives of executives and senior managers
DetailsChambers & Erwig. Dimension inference in spreadsheets
DetailsCleere. Establishing and measuring standard spreadsheet practices for end-users
DetailsColver. Self-checks in spreadsheets: A survey of current practice
DetailsCroll. In pursuit of spreadsheet excellence
DetailsCummings. Going to the mat with spreadsheet risk
DetailsGoswami, Chan, & Kim. The role of visualization tools in spreadsheet error correction from a cognitive fit perspective
DetailsHayes. Rules for users
DetailsHoag. College student novice spreadsheet reasoning and errors
DetailsHodnigg & Mittermeir. Metrics-based spreadsheet visualization: Support for focused maintenance
DetailsJanvrin. Detecting spreadsheet errors: An education case
DetailsKankuzi. A dynamic graph-based visualization for spreadsheets
DetailsKankuzi & Ayalew. An end-user oriented graph-based visualization for spreadsheets
DetailsKankuzi & Ayalew. An MCL algorithm based technique for comprehending spreadsheets
DetailsKarlsson. Using two heads in practice
DetailsLoraas & Mueller. Bridging the gap between spreadsheet use and control: An instructional case
DetailsO'Beirne. Information and data quality in spreadsheets
DetailsPerry. Automating spreadsheet discovery & risk assessment
DetailsPetti & Cannon. An innovative spreadsheet authoring environment
DetailsPowell, Baker, & Lawson. A critical review of the literature on spreadsheet errors
DetailsPowell, Baker, & Lawson. An auditing protocol for spreadsheet models


DetailsAbraham & Erwig. GoalDebug: A spreadsheet debugger for end users
DetailsAbraham & Erwig. UCheck: A spreadsheet type checker for end users
DetailsAyalew. A user-centered approach for testing spreadsheets
DetailsBaker, Foster-Johnson, Lawson, & Powell. Spreadsheet risk, awareness, and control
DetailsBals, Christ, Engels, & Erwig. ClassSheets - model-based, object-oriented design of spreadsheet applications
DetailsBarned. Model misbehaviour
DetailsBishop & McDaid. An empirical study of end-user behaviour in spreadsheet error detection & correction
DetailsBurnett, Fisher, & Rothermel. A methodology to improve dependability in spreadsheets
DetailsColver. Inclusion analysis
DetailsCompassoft. Five steps to enterprise spreadsheet management and control: A best-practices framework for critical risk reduction
DetailsGrossman, Mehrotra, & Ozluk. Lessons from mission-critical spreadsheets
DetailsHarrison & Howard. A pragmatic approach to the specification of Excel spreadsheets - Part 2
DetailsHarrison & Howard. A pragmatic approach to the testing of Excel spreadsheets - Part 3
DetailsHesse. Electronic spreadsheets: The good, the bad & the ugly
DetailsH.M. Revenue & Customs Audit Service. Methodology for the audit of spreadsheet models
DetailsHoward & Harrison. A pragmatic approach to the validation of Excel spreadsheets - Part 1
DetailsMadahar, Cleary, & Ball. Categorisation of spreadsheet use within organisations, incorporating risk: A progress report
DetailsMcGuire. Best practices for reducing model risk exposure
DetailsMurphy. Spreadsheet hell
DetailsO'Beirne. Facing the facts
DetailsPaine. Fun Boy Three were wrong: It is what you do, not the way that you do it
DetailsPanko. A rant on the lousy use of science in best practice recommendations for spreadsheet development, testing, and inspection
DetailsPanko. Thinking is bad: Implications of human error research for spreadsheet research and practice
DetailsPiquepaille. Fixing spreadsheet errors
DetailsRose. Taking human error out of financial spreadsheets


DetailsAbraham & Erwig. AutoTest: A tool for automatic test case generation in spreadsheets
DetailsAbraham & Erwig. Type inference for spreadsheets
DetailsBarker, Harris, & Parkin. Development and testing of spreadsheet applications
DetailsBlayney. An investigation of the incidence and effect of spreadsheet errors caused by the hard coding of input data values into formulas
DetailsBordelon. Safeguarding spreadsheets: Built-in software controls can protect the integrity of important financial data and formulas
DetailsBrath & Peters. Spreadsheet validation and analysis through content visualization
DetailsCarver, Fisher, & Rothermel. An empirical evaluation of a testing and debugging methodology for Excel
DetailsCaulkins, Morrison, & Weidemann. Are spreadsheet errors undermining decision-making in your organization?
DetailsCroll & Butler. Spreadsheets in clinical medicine - A public health warning
DetailsDunn. Spreadsheet controls, without going crazy
DetailsFisher, et al. Integrating automated test generation into WYSIWYT spreadsheet testing methodology
DetailsFisher, et al. Scaling a dataflow testing methodology to the multiparadigm world of commercial spreadsheets
DetailsGrossman. Integrating spreadsheet engineering in a management science course: A hierarchical approach
DetailsHowe & Simkin. Factors affecting the ability to detect spreadsheet errors
DetailsJafry, Sidoroff, & Chi. A computational framework for the near elimination of spreadsheet risk
DetailsKruck. Testing spreadsheet accuracy theory
DetailsLawrance, Abraham, Burnett, & Erwig. Sharing reasoning about faults in spreadsheets: An empirical study
DetailsMicrosoft. Spreadsheet compliance in the 2007 Microsoft Office system
DetailsMurphy. Commercial spreadsheet review
DetailsPanko. Compliance-appropriate spreadsheet testing
DetailsPanko. Facing the problem of spreadsheet errors
DetailsPanko. Recommended practices for spreadsheet testing
DetailsPanko. Spreadsheets and Sarbanes-Oxley: Regulations, risks, and control frameworks
DetailsPrice. Spreadsheet risk - a new direction for HMRC?
DetailsPryor. What's the point of documentation?
DetailsPryor, et al. Actuaries excel: But what about their software?
DetailsPurser & Chadwick. Does an awareness of differing types of spreadsheet errors aid end-users in identifying spreadsheets errors?
DetailsRajalingham, Chadwick, & Knight. An evaluation of a structured spreadsheet development methodology
DetailsRust, Bishop, & McDaid. Investigating the potential of test-driven development for spreadsheet engineering
DetailsRuthruff, Burnett, & Rothermel. Interactive fault localization techniques in a spreadsheet environment
DetailsThorne & Ball. Considering functional spreadsheet operator usage suggests the value of example driven modelling for decision support systems
DetailsVemula, Ball, & Thorne. Towards a spreadsheet engineering
DetailsWeber. Strategies for addressing spreadsheet compliance challenges


DetailsAbraham & Erwig. How to communicate unit error messages in spreadsheets
DetailsAbraham, Erwig, Kollmansberger, & Seifert. Visual specifications of correct spreadsheets
DetailsAndersson, et al. Introducing units in spreadsheets
DetailsBaker, Foster-Johnson, Lawson, & Powell. A survey of MBA spreadsheet users
DetailsBeaman, Waldmann, & Krueger. The impact of training in financial modelling principles on the incidence of spreadsheet error
DetailsBenham & Giullian. Reducing spreadsheet error rates
DetailsBewig. How do you know your spreadsheet is right?
DetailsCaulkins, Morrison, & Weidemann. Spreadsheet errors and decision making: Evidence from field interviews
DetailsClermont. Heuristics for the automatic identification of irregularities in spreadsheets
DetailsCoblenz, Ko, & Myers. Using objects of measurement to detect spreadsheet errors
DetailsCoon. Ensuring spreadsheet accuracy in the Sarbanes-Oxley era
DetailsCroll. The importance and criticality of spreadsheets in the City of London
DetailsEngels & Erwig. ClassSheets: Automatic generation of spreadsheet applications from object-oriented specifications
DetailsErwig, Abraham, Cooperstein, & Kollmansberger. Automatic generation and maintenance of correct spreadsheets
DetailsFisher & Rothermel. The EUSES spreadsheet corpus: A shared resource for supporting experimentation with spreadsheet dependability mechanisms
DetailsGrossman, Mehrotra, & Ozluk. Spreadsheet information systems are essential to business
DetailsHoward. Managing spreadsheets
DetailsLee. Teaching spreadsheet proficiency: Beyond hitting the keys
DetailsMartin. Get spreadsheets under control
DetailsMiller. Only a matter of time before the spreadsheets hit the fan
DetailsMittermeir, Clermont, & Hodnigg. Protecting spreadsheets against fraud
DetailsMurphy. Comparison of spreadsheets with other development tools
DetailsPanko & Ordway. Sarbanes-Oxley: What about all the spreadsheets?
DetailsPhalgune, et al. Garbage in, garbage out? An empirical look at oracle mistakes by end-user programmers
DetailsTakaki. Self-efficacy, confidence, and overconfidence as contributing factors to spreadsheet development errors
DetailsThorne & Ball. Exploring human factors in spreadsheet development


DetailsAnderson. A comparison of automated and manual spreadsheet error detection
DetailsAntoniu, Steckler, Krishnamurthi, Neuwirth, & Felleisen. Validating the unit correctness of spreadsheet programs
DetailsBewig. Let cell maps and traffic lights guide your spreadsheet inspections
DetailsBregar. Complexity metrics for spreadsheet models
DetailsChan. Spreadsheet visualization effects on error correction
DetailsClermont. A toolkit for scalable spreadsheet visualization
DetailsColver. Spreadsheet good practice: Is there any such thing?
DetailsEmmett & Goldman. Identification of logical errors through Monte Carlo simulation
DetailsGrossman & Ozluk. A paradigm for spreadsheet engineering methodologies
DetailsHorowitz. Spreadsheet overload?
DetailsKlobas & McGill. Spreadsheet knowledge: Measuring what user developers know
DetailsOlphert & Wilson. Validation of decision-aiding spreadsheets: The influence of contingency factors
DetailsPrabhakararao. Strategies and behaviors of end-user programmers with interactive fault localization (Thesis)
DetailsPryor. When, why and how to test spreadsheets
DetailsReinhardt & Pillay. Analysis of spreadsheet errors made by computer literacy students
DetailsRuthruff, Burnett, & Rothermel. The impact of two orthogonal factors in interactive fault localization
DetailsRuthruff, Phalgune, Beckwith, Burnett, & Cook. Rewarding "good" behavior: End-user debugging and rewards
DetailsShaw. Avoiding costly errors in your spreadsheets
DetailsSimkin. Ferret out spreadsheet errors
DetailsThorne, Ball, & Lawson. A novel approach to formulae production and overconfidence measurement to reduce risk in spreadsheet modelling


DetailsAhmad, Antoniu, Goldwater, & Krishnamurthi. A type system for statically detecting spreadsheet errors
DetailsAyalew & Mittermeir. Spreadsheet debugging
DetailsBewig. In Excel, cell names spell speed, safety
DetailsBurnett et al. End-user software engineering with assertions in the spreadsheet paradigm
DetailsCleary, et al. Investigating the use of software agents to reduce the risk of undetected errors in strategic spreadsheet applications
DetailsClermont & Mittermeir. Auditing large spreadsheet programs
DetailsGrossman. Accuracy in spreadsheet modelling systems
DetailsIrons. The wall and the ball: A study of domain referent spreadsheet errors
DetailsKruck, Maher, & Barkhi. Framework for cognitive skill acquisition and spreadsheet training
DetailsNash, Smith, & Adler. Audit and change analysis of spreadsheets
DetailsPanko. Reducing overconfidence in spreadsheet development
DetailsPhan. Validation of electronic spreadsheets for complying with 21 CFR Part 11
DetailsPrabhakararao, Cook, Ruthruff, Main, Durham, & Burnett. Strategies and behaviors of end-user programmers with interactive fault localization
DetailsPryor. Correctness is not enough
DetailsWillemain, Wallace, Fleischmann, Waisel, & Ganaway. Bad numbers: Coping with flawed decision support
DetailsWilson, et al. Harnessing curiosity to increase correctness in end-user programming


DetailsBanks & Monday. Interpretation as a factor in understanding flawed spreadsheets
DetailsBeckwith, Burnett, & Cook. Reasoning about many-to-many requirement relationships in spreadsheets
DetailsBurnett & Erwig. Visually customizing inference rules about apples and oranges
DetailsBurnett, Sheretov, Ren, & Rothermel. Testing homogeneous spreadsheet grids with the "What You See Is What You Test" methodology
DetailsCallahan. Block that spreadsheet error
DetailsChadwick. Stop that subversive spreadsheet!
DetailsChadwick. Training gamble leads to corporate grumble
DetailsClermont, Hanin, & Mittermeir. A spreadsheet auditing tool evaluated in an industrial context
DetailsCroll. A typical model audit approach
DetailsErwig & Burnett. Adding apples and oranges
DetailsFisher, Cao, Rothermel, Cook, & Burnett. Automated test case generation for spreadsheets
DetailsFisher, Jin, Rothermel, & Burnett. Test reuse in the spreadsheet paradigm
DetailsGoo. The effect of negative feedback on confidence calibration and error reduction in spreadsheet development
DetailsGrossman. Spreadsheet engineering: A research framework
DetailsJoseph. The effect of group size on spreadsheet error detection
DetailsMcGill. User-developed applications: Can end users assess quality?
DetailsMittermeir & Clermont. Finding high-level structures in spreadsheet programs
DetailsMorrison, et al. A visual code inspection approach to reduce spreadsheet linking errors
DetailsPryor. Managing the operational risks of user-developed software
DetailsRajalingham. The development of a structured methodology for the construction and integrity control of spreadsheet models
DetailsRajalingham, Chadwick, & Knight. Efficient methods for checking integrity: A structured spreadsheet engineering methodology
DetailsRandolph, Morris, & Lee. A generalised spreadsheet verification methodology


DetailsAyalew. Spreadsheet testing using interval analysis
DetailsBurnett, Ren, Ko, Cook, & Rothermel. Visually testing recursive programs in spreadsheet languages
DetailsChadwick, Knight, & Rajalingham. Quality control in spreadsheets: A visual approach using color codings to reduce errors in formulae
DetailsChadwick & Sue. Teaching spreadsheet development using peer audit and self-audit methods for reducing errors
DetailsEttema, Janssen, & de Swart. Spreadsheet assurance by "control around" is a viable alternative to the traditional approach
DetailsKrishna. Empirical studies of a spreadsheet maintenance experiment
DetailsKrishna, et al. Incorporating incremental validation and impact analysis into spreadsheet maintenance: An empirical study
DetailsKruck & Sheetz. Spreadsheet accuracy theory
DetailsNixon & O'Hara. Spreadsheet auditing software
DetailsO'Donnell. The use of influence diagrams in the design of spreadsheet models: An experimental study
DetailsPaine. Ensuring spreadsheet integrity with Model Master
DetailsPanko & Halverson. An experiment in collaborative development to reduce spreadsheet errors
DetailsRaffensperger. New guidelines for writing spreadsheets
DetailsRothermel, Burnett, Li, Dupuis, & Sheretov. A methodology for testing spreadsheets
DetailsTeo & Lee-Partridge. Effects of error factors and prior incremental practice on spreadsheet error detection: An experimental study
DetailsTukiainen. Comparing two spreadsheet calculation paradigms: An empirical study with novice users


DetailsAyalew, Clermont, & Mittermeir. Detecting errors in spreadsheets
DetailsBurnett, Agrawal, & van Zee. Exception handling in the spreadsheet paradigm
DetailsButler. Risk assessment for spreadsheet developments: Choosing which models to audit
DetailsButler. Is this spreadsheet a tax evader? How H. M. Customs & Excise test spreadsheet applications
DetailsChan, Ying, & Peh. Strategies and visualization tools for enhancing user auditing of spreadsheet models
DetailsEdwards, Finlay, & Wilson. The role of OR specialists in 'do it yourself' spreadsheet development
DetailsFinlay & Wilson. A survey of contingency factors affecting the validation of end-user spreadsheet-based decision support systems
DetailsHawker. Building financial accuracy into spreadsheets
DetailsJanvrin & Morrison. Using a structured design approach to reduce risks in end user spreadsheet development
DetailsPanko. Spreadsheet errors: What we know; what we think we can do
DetailsPanko. Two corpuses of spreadsheet errors
DetailsRajalingham, Chadwick, & Knight. Classification of spreadsheet errors
DetailsRajalingham, Chadwick, Knight, & Edwards. Quality control in spreadsheets: A software engineering-based approach to spreadsheet development
DetailsRothermel, et al. WYSIWYT testing in the spreadsheet paradigm: An empirical evaluation
DetailsTukiainen. Uncovering effects of programming paradigms: Errors in two spreadsheet systems
DetailsYing & Chan. Visual checking of spreadsheets


DetailsBerglas & Hoare. Spreadsheet errors: Risks and techniques
DetailsBurnett & Rothermel. Applying a "What You See Is What You Test" (WYSIWYT) technology to commercial spreadsheet packages: Several scenarios
DetailsBurnett, Sheretov, & Rothermel. Scaling up a "What You See Is What You Test" methodology to spreadsheet grids
DetailsHormann. Getting the oops! out of spreadsheets
DetailsKruck & Maher. Home mortgage analysis for cultivating crucial spreadsheet and model development skills
DetailsPanko. Applying code inspection to spreadsheet testing
DetailsRead & Batson. Spreadsheet modelling best practice
DetailsReichwein, Rothermel, & Burnett. Slicing spreadsheets: An integrated methodology for spreadsheet testing and debugging
DetailsTeo & Tan. Spreadsheet development and 'what-if' analysis - quantitative versus qualitative errors
DetailsWhittaker. Spreadsheet errors and techniques for finding them


DetailsBerglas & Hoare. Spreading the risk: Errors, risks and techniques in spreadsheets
DetailsKruck. Towards a theory of spreadsheet accuracy: An empirical study
DetailsPanko. What we know about spreadsheet errors
DetailsPanko & Sprague. Hitting the wall: Errors in developing and code inspecting a 'simple' spreadsheet model
DetailsRothermel, Li, DuPuis, & Burnett. What You See Is What You Test: A methodology for testing form-based visual programs
DetailsSajaniemi. Modeling spreadsheet audit: A rigorous approach to automatic visualization


DetailsChadwick, Knight, & Clipsham. Information integrity in end-user systems
DetailsCohen. Auditing spreadsheets
DetailsFulford. Designing spreadsheet models: Can you afford to be wrong?
DetailsGalletta, Hartzel, Johnson, Joseph, & Rustagi. Spreadsheet presentation and error detection: An experimental study
DetailsNew Zealand Treasury. Review spreadsheets
DetailsPanko & Halverson. Are two heads better than one? (At reducing errors in spreadsheet modeling)
DetailsRothermel, Li, & Burnett. Testing strategies for form-based visual programs
DetailsTeo & Tan. Quantitative and qualitative errors in spreadsheet development


DetailsChan & Storey. The use of spreadsheets in organizations: Determinants and consequences
DetailsDavis. Tools for spreadsheet auditing
DetailsFreeman. How to make spreadsheets error-proof
DetailsGalletta, Hartzel, Johnson, Joseph, & Rustagi. An experimental study of spreadsheet presentation and error detection
DetailsHall. A risk and control-oriented study of the practices of spreadsheet application developers
DetailsPanko. Hitting the wall: Errors in developing "simple" spreadsheet models
DetailsPanko & Halverson. Spreadsheets on trial: A survey of research on spreadsheet risks
DetailsRoss. Spreadsheet risk: How and why to build a better spreadsheet




DetailsCale. Quality issues for end-user developed software
DetailsChandler & Marriott. Different approaches to the use of spreadsheet models in teaching management accounting
DetailsHendry & Green. Creating, comprehending and explaining spreadsheets: A cognitive interpretation of what users think of the spreadsheet model
DetailsSchultheis & Sumner. The relationship of application risks to application controls: A study of microcomputer-based spreadsheet applications


DetailsCragg & King. Spreadsheet modelling abuse: An opportunity for OR?
DetailsGalletta, et al. An empirical study of spreadsheet error-finding performance
DetailsIsakowitz, Schocken, & Lucas. Toward a logical/physical theory of spreadsheet modeling
DetailsWilde. A WYSIWYC (what you see is what you compute) spreadsheet




DetailsGable, Yap, & Eng. Spreadsheet investment, criticality, and control
DetailsLu, Litecky, & Lu. Application controls for spreadsheet development
DetailsNardi & Miller. Twinkling lights and nested loops: Distributed problem solving and spreadsheet development


DetailsBusbin, Gross, & Dillon. Improving spreadsheet control for sales managers through the use of the systems development life cycle
DetailsCragg & Grant. An analysis of spreadsheet models used for decision support
DetailsEdge & Wilson. Avoiding the hazards of microcomputer spreadsheets
DetailsGhosal & Caster. A disciplined approach to spreadsheet development


DetailsBorthick. Validating spreadsheets: Minimizing the potential for errors
DetailsGoss, Dillon, & Kendrick. Bittersweet spreadsheets: Application development needs control
DetailsHayen & Peters. How to ensure spreadsheet integrity
DetailsMiller. 8 ways to avoid worksheet errors
DetailsRonen, Palley, & Lucas. Spreadsheet analysis and design


DetailsKee. Programming standards for spreadsheet software
DetailsKee & Mason. Preventing errors in spreadsheets


DetailsBrown & Gould. An experimental study of people creating spreadsheets
DetailsDavies & Ikin. Auditing spreadsheets
DetailsFloyd & Pyun. Errors in spreadsheet use
DetailsSimkin. How to validate spreadsheets


DetailsBeitman. Reviewing electronic spreadsheets
DetailsBrown & Gould. How people create spreadsheets
DetailsGulmaraes & Ramanujam. Personal computing trends and problems: An empirical study


DetailsAlavi & Weiss. Managing the risks associated with end-user computing
DetailsBromley. Template design and review: How to prevent spreadsheet disasters
DetailsCreeth. Microcomputer spreadsheets: Their uses and abuses
DetailsHowitt. Avoiding bottom-line disasters
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