There has been little research on end-user program development beyond the activity of programming. Devising ways to address additional activities related to end-user program development may be critical, however, because research shows that a large proportion of the programs written by end users contain faults. Toward this end, we have been working on ways to provide formal "software engineering" methodologies to end-user programmers. This paper describes an approach we have developed for supporting assertions in end-user software, focusing on the spreadsheet paradigm. We also report the results of a controlled experiment, with 59 end-user subjects, to investigate the usefulness of this approach. Our results show that the end users were able to use the assertions to reason about their spreadsheets, and that doing so was tied to both greater correctness and greater efficiency.

Spreadsheet language programs, which include commercial spreadsheets, are among the most common form of software in use today. Unlike more "traditional " forms of software however, spreadsheet language programs are created and maintained by end-users with little or no programming experience. As a result, a high percentage of these programs contain errors. Unfortunately, software engineering research has for the most part ignored this problem. We have developed a methodology that is designed to aid end-users in developing, testing, and maintaining spreadsheet language programs. The methodology communicates testing information and information about the impact of cell changes to users in a manner that does not require an understanding of formal testing theory or the behind the scenes mechanisms. This paper presents the results of an empirical study that shows that, during maintenance, end-users using our methodology were more accurate in making changes and did a significantly better job of validating their spreadsheets than end-users without the methodology.

There are many common spreadsheet errors that traditional spreadsheet systems do not help users find. This paper presents a statically-typed spreadsheet language that adds additional information about the objects that the spreadsheet values represent. By annotating values with both units and labels, users denote both the system of measurement in which the values are expressed as well as the properties of the objects to which the values refer. This information is used during computation to detect some invalid computations and allow users to identify properties of

End-user programmers are writing an unprecedented number of programs, due in large part to the significant effort put forth to bring programming power to end users. Unfortunately, this effort has not been supplemented by a comparable effort to increase the correctness of these often faulty programs. To address this need, we have been working towards bringing fault localization techniques to end users. In order to understand how end users are affected by and interact with such techniques, we conducted a think-aloud study, examining the interactive, human-centric ties between end-user debugging and a fault localization technique. Our results provide insights into the contributions such techniques can make to an interactive end-user debugging process. 1.

End-user programmers are writing an unprecedented number of programs, primarily using languages and environments that incorporate a number of interactive and visual programming techniques. To help these users debug these programs, we have developed an entirely visual, interactive approach to fault localization. This paper presents the approach. We also present the results of a think-aloud study that examined the interactive, human-centric issues that arise in end-user debugging using a fault localization strategy. Our results provide insights into the contributions such strategies can make to the end-user debugging process.

Spreadsheets are a common tool in end-user programming. But even while important decisions are based on spreadsheet computations, spreadsheets are poorly documented software and the differences between simple on-shot computations and large, long-living sheets are not well understood. Like other software, production spreadsheets are subject to repeated maintenance cycles. Consequently, as with conventional software, short maintenance cycles and poor documentation tend to decrease their quality. We introduce an approach to help maintainers understand the structure of large spreadsheets as well as to zoom into certain parts of the spreadsheet. To cope with large sheets, our approach features two levels of abstraction: logical areas and semantic classes. These abstractions are based on different degrees of relatedness of cells according to the formulas they contain.

Abstract: One common approach to validating data such as email addresses and phone numbers is to check whether values conform to some desired data format. Unfortunately, users may need to learn a specialized notation such as regular expressions to specify the format, and even after learning the notation, specifying formats may take substantial time. To address these problems, this paper introduces Topei, a system that infers a format from an unlabeled collection of examples (which may contain errors). The generated format is presented as understandable English, so users can review and customize the format. In addition, the format can be used to automatically check data against the format and find outliers that do not match. Topei shows substantially higher precision and recall than an alternate algorithm (Lapis) on test data. Topei’s usefulness is demonstrated by integrating it with spreadsheet, database, and web services systems. 1

Spreadsheet languages, which include commercial spreadsheets and various research systems, have had a substantial impact on end-user computing. Research shows, however, that spreadsheets often contain faults. Thus, in previous work, we presented a methodology that assists spreadsheet users in testing their spreadsheet formulas. Our empirical studies have shown that this methodology can help endusers test spreadsheets more adequately and eciently; however, the process of generating test cases can still represent a signi cant impediment. To address this problem, wehave been investigating how to automate test case generation for spreadsheets in ways that support incremental testing and provide immediate visual feedback. We have utilized two techniques for generating test cases, one involving random selection and one involving a goal-oriented approach. We describe these techniques, and report results of an experiment examining their relative costs and bene ts.

Programmers often omit input validation when inputs can appear in many different formats or when validation criteria cannot be precisely specified. To enable validation in these situations, we present a new technique that puts valid inputs into a consistent format and that identifies “questionable ” inputs which might be valid or invalid, so that these values can be double-checked by a person or a program. Our technique relies on the concept of a “tope”, which is an application-independent abstraction describing how to recognize and transform values in a category of data. We present our definition of topes and describe a development environment that supports the implementation and use of topes. Experiments with web application and spreadsheet data indicate that using our technique improves the accuracy and reusability of validation code and also improves the effectiveness of subsequent data cleaning such as duplicate identification.

A human-centric issue that has not been considered in the design of end-user programming environments is whether gender differences exist that are important to the design of these environments. Ignoring this issue would miss the opportunity of enhancing the effectiveness of end-user programmers by incorporating appropriate mechanisms to support gender-associated differences in decision making, learning, and problem solving. This paper takes a first step toward building a foundation for investigating this issue by surveying gender difference literature from five domains with an eye toward possible implications for end-user programming. We present a taxonomy of this literature, and derive a number of specific issues for each element of the taxonomy (stated as hypotheses). This foundation provides a starting point for organized investigations into issues that may be important for making breakthroughs in the effectiveness of end-user programmers.