Robin Abraham
Microsoft
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ACM Computing Surveys | 2011
Andrew J. Ko; Robin Abraham; Laura Beckwith; Alan F. Blackwell; Margaret M. Burnett; Martin Erwig; Christopher Scaffidi; Joseph Lawrance; Henry Lieberman; Brad A. Myers; Mary Beth Rosson; Gregg Rothermel; Mary Shaw; Susan Wiedenbeck
Most programs today are written not by professional software developers, but by people with expertise in other domains working towards goals for which they need computational support. For example, a teacher might write a grading spreadsheet to save time grading, or an interaction designer might use an interface builder to test some user interface design ideas. Although these end-user programmers may not have the same goals as professional developers, they do face many of the same software engineering challenges, including understanding their requirements, as well as making decisions about design, reuse, integration, testing, and debugging. This article summarizes and classifies research on these activities, defining the area of End-User Software Engineering (EUSE) and related terminology. The article then discusses empirical research about end-user software engineering activities and the technologies designed to support them. The article also addresses several crosscutting issues in the design of EUSE tools, including the roles of risk, reward, and domain complexity, and self-efficacy in the design of EUSE tools and the potential of educating users about software engineering principles.
symposium on visual languages and human-centric computing | 2004
Robin Abraham; Martin Erwig
This paper describes the design and implementation of a unit and header inference system for spreadsheets. The system is based on a formal model of units that we have described in previous work. Since the unit inference depends on information about headers in a spreadsheet, a realistic unit inference system requires a method for automatically determining headers. The present paper describes (1) several spatial-analysis algorithms for header inference, (2) a framework that facilitates the integration of different algorithms, and (3) the implementation of the system. The combined header and unit inference system is fully integrated into Microsoft Excel and can be used to automatically identify various kinds of errors in spreadsheets. Test results show that the system works accurately and reliably
Journal of Visual Languages and Computing | 2007
Robin Abraham; Martin Erwig
Spreadsheets are widely used, and studies have shown that most end-user spreadsheets contain non-trivial errors. Most of the currently available tools that try to mitigate this problem require varying levels of user intervention. This paper presents a system, called UCheck, that detects errors in spreadsheets automatically. UCheck carries out automatic header and unit inference, and reports unit errors to the users. UCheck is based on two static analyses phases that infer header and unit information for all cells in a spreadsheet. We have tested UCheck on a wide variety of spreadsheets and found that it works accurately and reliably. The system was also used in a continuing education course for high school teachers, conducted through Oregon State University, aimed at making the participants aware of the need for quality control in the creation of spreadsheets.
international conference on software engineering | 2007
Robin Abraham; Martin Erwig
We present a spreadsheet debugger targeted at end users. Whenever the computed output of a cell is incorrect, the user can supply an expected value for a cell, which is employed by the system to generate a list of change suggestions for formulas that, when applied, would result in the user-specified output. The change suggestions are ranked using a set of heuristics. In previous work, we had presented the system as a proof of concept. In this paper, we describe a systematic evaluation of the effectiveness of inferred change suggestions and the employed ranking heuristics. Based on the results of the evaluation we have extended both, the change inference process and the ranking of suggestions. An evaluation of the improved system shows that change inference process and the ranking heuristics have both been substantially improved and that the system performs effectively.
IEEE Transactions on Software Engineering | 2009
Robin Abraham; Martin Erwig
Based on 1) research into mutation testing for general-purpose programming languages and 2) spreadsheet errors that have been reported in the literature, we have developed a suite of mutation operators for spreadsheets. We present an evaluation of the mutation adequacy of definition-use adequate test suites generated by a constraint-based automatic test-case generation system we have developed in previous work. The results of the evaluation suggest additional constraints that can be incorporated into the system to target mutation adequacy. In addition to being useful in mutation testing of spreadsheets, the operators can be used in the evaluation of error-detection tools and also for seeding spreadsheets with errors for empirical studies. We describe two case studies where the suite of mutation operators helped us carry out such empirical evaluations. The main contribution of this paper is a suite of mutation operators for spreadsheets that can be used for performing empirical evaluations of spreadsheet tools to indicate ways in which the tools can be improved.
symposium on visual languages and human-centric computing | 2005
Robin Abraham; Martin Erwig
We present a semi-automatic debugger for spreadsheet systems that is specifically targeted at end-user programmers. Users can report expected values for cells that yield incorrect results. The system then generates change suggestions that could correct the error. Users can interactively explore, apply, refine, or reject these change suggestions. The computation of change suggestions is based on a formal inference system that propagates expected values backwards across formulas. The system is fully integrated into Microsoft Excel and can be used to automatically detect and correct various kinds of errors in spreadsheets. Test results show that the system works accurately and reliably.
symposium on visual languages and human-centric computing | 2005
Robin Abraham; Martin Erwig; Steve Kollmansberger; Ethan Seifert
We introduce a visual specification language for spreadsheets that allows the definition of spreadsheet templates. A spreadsheet generator can automatically create Excel spreadsheets from these templates together with customized update operations. It can be shown that spreadsheets created in this way are free from a large class of errors, such as reference, omission, and type errors. We present a formal definition of the visual language for templates and describe the process of generating spreadsheets from templates. In addition, we present an editor for templates and analyze the editor using the cognitive dimensions framework.
Journal of Functional Programming | 2006
Martin Erwig; Robin Abraham; Steve Kollmansberger; Irene Cooperstein
A huge discrepancy between theory and practice exists in one popular application area of functional programming – spreadsheets. Although spreadsheets are the most frequently used (functional) programs, they fall short of the quality level that is expected of functional programs, which is evidenced by the fact that existing spreadsheets contain many errors, some of which have serious impacts. We have developed a template specification language that allows the definition of spreadsheet templates that describe possible spreadsheet evolutions. This language is based on a table calculus that formally captures the process of creating and modifying spreadsheets. We have developed a type system for this calculus that can prevent type, reference, and omission errors from occurring in spreadsheets. On the basis of the table calculus we have developed Gencel, a system for generating reliable spreadsheets. We have implemented a prototype version of Gencel as an extension of Excel.
principles and practice of declarative programming | 2006
Robin Abraham; Martin Erwig
Spreadsheets are the most popular programming systems in use today. Since spreadsheets are visual, first-order functional languages, research into the foundations of spreadsheets is therefore a highly relevant topic for the principles and, in particular, the practice, of declarative programming.Since the error rate in spreadsheets is very high and since those errors have significant impact, methods and tools that can help detect and remove errors from spreadsheets are very much needed. Type systems have traditionally played a strong role in detecting errors in programming languages, and it is therefore reasonable to ask whether type systems could not be helpful in improving the current situation of spreadsheet programming.In this paper we introduce a type system and a type inference algorithm for spreadsheets and demonstrate how this algorithm and the underlying typing concept can identify programming errors in spreadsheets. In addition, we also demonstrate how the type inference algorithm can be employed to infer models, or specifications, for spreadsheets, which can be used to prevent future errors in spreadsheets.
ieee symposium on human centric computing languages and environments | 2003
Robin Abraham
We introduce FoXQ, a visual language that enables end users to query XML We are currently developing a language that brings a lot of the functionality of XQuery within the reach of the end users without getting them embroiled in the intricacies of XQuery syntax. The query interface is form-based and the query model is based on a document metaphor in which the users formulate queries by filling out forms.