Analysis and improvement of business process models using spreadsheets

Software in general is thoroughly analyzed before it is released to its users. Business processes often are not - at least not as thoroughly as it could be - before they are released to their users, e.g., employees or software agents. This paper ascribes this practice to the lack of suitable instruments for business process analysts, who design the processes, and aims to provide them with the necessary instruments to allow them to also analyze their processes. We use the spreadsheet paradigm to represent business process analysis tasks, such as writing metrics and assertions, running performance analysis and verification tasks, and reporting on the outcomes, and implement a spreadsheet-based tool for business process analysis. The results of two independent user studies demonstrate the viability of the approach

Automated model-based spreadsheet debugging

Spreadsheets are interactive data organization and calculation programs that are developed in spreadsheet environments like Microsoft Excel or LibreOffice Calc. They are probably the most successful example of end-user developed software and are utilized in almost all branches and at all levels of companies. Although spreadsheets often support important decision making processes, they are, like all software, prone to error. In several cases, faults in spreadsheets have caused severe losses of money. Spreadsheet developers are usually not educated in the practices of software development. As they are thus not familiar with quality control methods like systematic testing or debugging, they have to be supported by the spreadsheet environment itself to search for faults in their calculations in order to ensure the correctness and a better overall quality of the developed spreadsheets. This thesis by publication introduces several approaches to locate faults in spreadsheets. The presented approaches are based on the principles of Model-Based Diagnosis (MBD), which is a technique to find the possible reasons why a system does not behave as expected. Several new algorithmic enhancements of the general MBD approach are combined in this thesis to allow spreadsheet users to debug their spreadsheets and to efficiently find the reason of the observed unexpected output values. In order to assure a seamless integration into the environment that is well-known to the spreadsheet developers, the presented approaches are implemented as an extension for Microsoft Excel. The first part of the thesis outlines the different algorithmic approaches that are introduced in this thesis and summarizes the improvements that were achieved over the general MBD approach. In the second part, the appendix, a selection of the author's publications are presented. These publications comprise (a) a survey of the research in the area of spreadsheet quality assurance, (b) a work describing how to adapt the general MBD approach to spreadsheets, (c) two new algorithmic improvements of the general technique to speed up the calculation of the possible reasons of an observed fault, (d) a new concept and algorithm to efficiently determine questions that a user can be asked during debugging in order to reduce the number of possible reasons for the observed unexpected output values, and (e) a new method to find faults in a set of spreadsheets and a new corpus of real-world spreadsheets containing faults that can be used to evaluate the proposed debugging approaches

Improving spreadsheet test practices

<p>Current testing practices for spreadsheets are<br>ad hoc in nature: spreadsheet users put 'test<br>formulas' in their spreadsheets to validate out-comes. In this paper we show that this practice<br>is common, by analyzing a large set of spread-sheets from practice to investigate if spread-sheet users are currently testing. In a follow up<br>analysis, we study the test practices found in<br>this set to deeply understand the way in which<br>spreadsheet users test, in lack of formal testing<br>methods. Subsequently, we describe the Ex-pector approach to extract formulas that are<br>already present in a spreadsheet, presenting<br>these formulas to the user and suggesting im-provements, both on the level of individual test<br>formulas as on the spreadsheet as a whole by<br>increasing the coverage of the test formulas. Fi-nally, we oer support to understand why a test<br>formula is breaking. We end the paper with<br>an example underlining the applicability of our<br>approach.</p> <p> </p