Abstract not found

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.

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.

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. 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.

Although gender differences in a technological world are receiving significant research attention, much of the research and practice has aimed at how society and education can impact the successes and retention of female computer science professionals—but the possibility of gender issues within software has received almost no attention. If gender issues exist with some types of software features, it is possible that accommodating them by changing these features can increase effectiveness, but only if we know what these issues are. In this paper, we empirically investigate gender differences for end users in the context of debugging spreadsheets. Our results uncover significant gender differences in self-efficacy and feature acceptance, with females exhibiting lower self-efficacy and lower feature acceptance. The results also show that these differences can significantly reduce females ’ effectiveness.

Despite years of availability of testing tools, professional software developers still seem to need better support to determine the effectiveness of their tests. Without improvements in this area, inadequate testing of software seems likely to remain a major problem. To address this problem, industry and researchers have proposed systems that visualize “testedness ” for end-user and professional developers. Empirical studies of such systems for end-user programmers have begun to show success at helping end users write more effective tests. Encouraged by this research, we examined the effect that code coverage visualizations have on the effectiveness of test cases that professional software developers write. This paper presents the results of an empirical study conducted using code coverage visualizations found in a commercially available programming environment. Our results reveal how this kind of code coverage visualization impacts test effectiveness, and provide insights into the strategies developers use to test code.

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.

We present an error-detection and-correction approach for spreadsheets that automatically generates questions about input/output pairs and, depending on the feedback given by the user, proposes changes to the spreadsheet that would correct detected errors. This approach combines and integrates previous work on automatic test-case generation and goal-directed debugging. We have implemented this method as an extension to MS Excel. We carried out an evaluation of the system using spreadsheets seeded with faults using mutation operators. The evaluation shows among other things that up to 93 % of the first-order mutants and 98 % of the second-order mutants were detected by the system using the automatically generated test cases. 1.

A post-completion error is a specific form of omission error occurring after some task goal has been accomplished – for example, forgetting to collect your original after photocopying. Using a novel experimental paradigm, this study demonstrates the cognitive robustness of postcompletion error: that it occurs not only in routine procedural tasks but also in problem-solving situations. The effect of a simple static visual cue to mitigate the error was also assessed by testing two different interfaces through which users engaged in problem-solving. The findings suggest that even a simple static cue can reduce the error rate, though not eliminate it.