Avoiding, finding and fixing spreadsheet errors – A survey of automated approaches for spreadsheet QA

Jannach, Dietmar; Schmitz, Thomas; Hofer, Birgit; Wotawa, Franz

doi:10.1016/j.jss.2014.03.058

Cited by 59 publications

(31 citation statements)

References 41 publications

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“…Statistical debugging has been previously extended to spreadsheets and to multi‐agent systems as well. Similar to our work, in both of these approaches, the notion of spectrum is defined per test case and per output.…”

Section: Related Workmentioning

confidence: 99%

“…Similar to our work, in both of these approaches, the notion of spectrum is defined per test case and per output. Specifically, in the spreadsheet fault localization approach, only one test case is used for each spreadsheet, and each execution of that test case for each output amounts to one spectrum . In the multi‐agent system fault localization, the behaviour of each agent at each time step is considered to be a spectrum .…”

Section: Related Workmentioning

confidence: 99%

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Simulink fault localization: an iterative statistical debugging approach

Liu

Lucia

Nejati

et al. 2016

Software Testing Verif & Rel

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Debugging Simulink models presents a significant challenge in the embedded industry. In this work, we propose SimFL, a fault localization approach for Simulink models by combining statistical debugging and dynamic model slicing. Simulink models, being visual and hierarchical, have multiple outputs at different hierarchy levels. Given a set of outputs to observe for localizing faults, we generate test execution slices, for each test case and output, of the Simulink model. In order to further improve fault localization accuracy, we propose iSimFL, an iterative fault localization algorithm. At each iteration, iSimFL increases the set of observable outputs by including outputs at lower hierarchy levels, thus increasing the test oracle cost but offsetting it with significantly more precise fault localization. We utilize a heuristic stopping criterion to avoid unnecessary test oracle extension. We evaluate our work on three industrial Simulink models from Delphi Automotive. Our results show that, on average, SimFL ranks faulty blocks in the top 8.9% in the list of suspicious blocks. Further, we show that iSimFL significantly improves this percentage down to 4.4% by requiring engineers to observe only an average of five additional outputs at lower hierarchy levels on top of high-level model outputs.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Simulink fault localization: an iterative statistical debugging approach

Liu

Lucia

Nejati

et al. 2016

Software Testing Verif & Rel

View full text Add to dashboard Cite

show abstract

“…For these cases, there are several approaches that try to find faults or errors in spreadsheets. Jannach et al presented a survey covering the current techniques in this field [63]. They present an overview of their own method in [64], where they use an interactive approach to help the user to find the faults.…”

Section: Related Workmentioning

confidence: 99%

Embedding, Evolution, and Validation of Model-Driven Spreadsheets

Cunha

Fernandes

Mendes

et al. 2015

IIEEE Trans. Software Eng.

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This paper proposes and validates a model-driven software engineering technique for spreadsheets. The technique that we envision builds on the embedding of spreadsheet models under a widely used spreadsheet system. This means that we enable the creation and evolution of spreadsheet models under a spreadsheet system. More precisely, we embed ClassSheets, a visual language with a syntax similar to the one offered by common spreadsheets, that was created with the aim of specifying spreadsheets. Our embedding allows models and their conforming instances to be developed under the same environment. In practice, this convenient environment enhances evolution steps at the model level while the corresponding instance is automatically co-evolved. Finally, we have designed and conducted an empirical study with human users in order to assess our technique in production environments. The results of this study are promising and suggest that productivity gains are realizable under our model-driven spreadsheet development setting.

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“…Numerous researchers in different subfields of Computer Science and Information Science have developed approaches to support spreadsheet developers during the development and use of their spreadsheets [10]. There are many commercial tools available for end-users, like, for example, Spreadsheet Detective, Excel Auditor, and SLATE.…”

Section: Related Workmentioning

confidence: 99%

A methodology for constructing the calculation model of scientific spreadsheets

Vos¹,

Wielemaker²,

Schreiber³

et al. 2015

Proceedings of the 8th International Conference on Knowledge Capture

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Spreadsheets models are frequently used by scientists to analyze research data. These models are typically described in a paper or a report, which serves as single source of information on the underlying research project. As the calculation workflow in these models is not made explicit, readers are not able to fully understand how the research results are calculated, and trace them back to the underlying spreadsheets. This paper proposes a methodology for semiautomatically deriving the calculation workflow underlying a set of spreadsheets. The starting point of our methodology is the cell dependency graph, representing all spreadsheet cells and connections. We automatically aggregate all cells in the graph that represent instances and duplicates of the same quantities, based on analysis of the formula syntax. Subsequently, we use a set of heuristics, incorporating knowledge on spreadsheet design, computational procedures and domain knowledge, to select those quantities, that are relevant for understanding the calculation workflow. We explain and illustrate our methodology by actually applying it on three sets of spreadsheets from existing research projects in the domains of environmental and life science. Results from these case studies show that our constructed calculation models approximate the ground truth calculation workflows, both in terms of content and size, but are not a perfect match.

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Avoiding, finding and fixing spreadsheet errors – A survey of automated approaches for spreadsheet QA

Cited by 59 publications

References 41 publications

Simulink fault localization: an iterative statistical debugging approach

Simulink fault localization: an iterative statistical debugging approach

Embedding, Evolution, and Validation of Model-Driven Spreadsheets

A methodology for constructing the calculation model of scientific spreadsheets

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