An Abstract Domain to Infer Types over Zones in Spreadsheets

Cheng, Tie; Rival, Xavier

doi:10.1007/978-3-642-33125-1_9

Cited by 5 publications

(3 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Cheng and Rival propose an abstract domain to infer types of parts (for example, columns) of a spreadsheet (Cheng and Rival 2012). In fact they consider the code to populate a spreadsheet, and not the spreadsheet data as displayed in a spreadsheet environment as we do.…”

Section: Related Workmentioning

confidence: 99%

Model inference for spreadsheets

et al. 2014

View full text Add to dashboard Cite

Many errors in spreadsheet formulas can be avoided if spreadsheets are built automatically from higher-level models that can encode and enforce consistency constraints in the generated spreadsheets. Employing this strategy for legacy spreadsheets is difficult, because the model has to be reverse engineered from an existing spreadsheet and existing data must be transferred into the new model-generated spreadsheet. We have developed and implemented a technique that automatically infers relational schemas from spreadsheets. This technique uses particularities from the spreadsheet realm to create better schemas. We have evaluated this technique in two ways: first, we have demonstrated its applicability by using it on a set of real-world spreadsheets. Second, we have run an empirical study with users. The study has shown that the results produced by our technique are comparable to the ones developed by experts starting from the same (legacy) spreadsheet data. Although relational schemas are very useful to model data, they do not fit spreadsheets well, as they do not allow expressing layout. Thus, we have also introduced a mapping between relational schemas and ClassSheets. A ClassSheet controls further changes to the spreadsheet and safeguards it against a large class of formula errors. The developed tool is a contribution to spread-123 Autom Softw Eng sheet (reverse) engineering, because it fills an important gap and allows a promising design method (ClassSheets) to be applied to a huge collection of legacy spreadsheets with minimal effort.

show abstract

Section: Related Workmentioning

confidence: 99%

Model inference for spreadsheets

et al. 2014

View full text Add to dashboard Cite

show abstract

“…The only contributions found in the literature addressing the analysis of the code of procedures included in spreadsheets are due to Cheng and Rival. These authors propose a static analysis techniques to infer type constraints over spreadsheets cells to avoid type errors and to detect run‐time type unsafe operations .…”

Section: Related Workmentioning

confidence: 99%

EXACT: A tool for comprehending VBA-based Excel spreadsheet applications

Amalfitano

Simone

Fasolino

et al. 2016

J. Softw. Evol. and Proc.

View full text Add to dashboard Cite

Spreadsheet applications are widely adopted by millions of end users from several application domains and provide strategic support to many business, scientific, industrial, and organizational processes. These applications are usually developed by rapid application development processes, exploiting host scripting languages allowing the basic spreadsheets to provide complex functionality, business rules, and user interfaces. Several factors complicate the comprehension of these applications because they are usually developed and maintained by end users without specific software engineering skills, grow over time, are not adequately documented, and do not present explicit separation between data, business logic, and user interface layers. This paper presents a reverse engineering tool intended to support the comprehension of Excel spreadsheet applications developed using the Visual Basic for Application programming language. The tool has been implemented as an add-in that extends the Excel working environment by providing analysis and visualization features. It is able to extract information about the elements composing the analyzed Excel spreadsheet application, the functionality it exposes through its user interface, and the dependencies among its cells. This information is provided by means of interactive views. The validity of the tool has been assessed by a qualitative case study performed with professional end users from an automotive industrial domain.

show abstract

“…Finally, as we are witnessing widespread adoption of software with far-reaching societal impact -i.e., to automate decision-making in fields such as social welfare, criminal justice, and even health care -a number of recent cases have evidenced the importance of ensuring software fairness and non-discrimination 5 as well as data privacy 6 . Going forward, data science software will be subject to more and more legal regulations (e.g., the European General Data Protection Regulation adopted in 2016) as well as administrative audits.…”

Section: Introductionmentioning

confidence: 99%