Scott D. Fleming

Gender pluralism in problem-solving software

Although there has been significant research into gender regarding educational and workplace practices, there has been little awareness of gender differences as they pertain to software tools, such as spreadsheet applications, that try to support end users in problem-solving tasks. Although such software tools are intended to be gender agnostic, we believe that closer examination of this premise is warranted. Therefore, in this paper, we report an end-to-end investigation into gender differences with spreadsheet software. Our results showed gender differences in feature usage, feature-related confidence, and tinkering (playful exploration) with features. Then, drawing implications from these results, we designed and implemented features for our spreadsheet prototype that took the gender differences into account. The results of an evaluation on this prototype showed improvements for both males and females, and also decreased gender differences in some outcome measures, such as confidence. These results are encouraging, but also open new questions for investigation. We also discuss how our results compare to generalization studies performed with a variety of other software platforms and populations.

A Debugging Perspective on End-User Mashup Programming

In recent years, systems have emerged that enable end users to “mash” together existing web services to build new web sites. However, little is known about how well end users succeed at building such mashups, or what they do if they do not succeed at their first attempt. To help fill this gap, we took a fresh look, from a debugging perspective, at the approaches of end users as they attempted to create mashups. Our results reveal the end users’ debugging strategies and strategy barriers, the gender differences between the debugging strategies males and females followed and the features they used, and finally how their debugging successes and difficulties interacted with their design behaviors.

An Information Foraging Theory Perspective on Tools for Debugging, Refactoring, and Reuse Tasks

Theories of human behavior are an important but largely untapped resource for software engineering research. They facilitate understanding of human developers’ needs and activities, and thus can serve as a valuable resource to researchers designing software engineering tools. Furthermore, theories abstract beyond specific methods and tools to fundamental principles that can be applied to new situations. Toward filling this gap, we investigate the applicability and utility of Information Foraging Theory (IFT) for understanding information-intensive software engineering tasks, drawing upon literature in three areas: debugging, refactoring, and reuse. In particular, we focus on software engineering tools that aim to support information-intensive activities, that is, activities in which developers spend time seeking information. Regarding applicability, we consider whether and how the mathematical equations within IFT can be used to explain why certain existing tools have proven empirically successful at helping software engineers. Regarding utility, we applied an IFT perspective to identify recurring design patterns in these successful tools, and consider what opportunities for future research are revealed by our IFT perspective.

Modeling programmer navigation: A head-to-head empirical evaluation of predictive models

Software developers frequently need to perform code maintenance tasks, but doing so requires time-consuming navigation through code. A variety of tools are aimed at easing this navigation by using models to identify places in the code that a developer might want to visit, and then providing shortcuts so that the developer can quickly navigate to those locations. To date, however, only a few of these models have been compared head-to-head to assess their predictive accuracy. In particular, we do not know which models are most accurate overall, which are accurate only in certain circumstances, and whether combining models could enhance accuracy. Therefore, we have conducted an empirical study to evaluate the accuracy of a broad range of models for predicting many different kinds of code navigations in sample maintenance tasks. Overall, we found that models tended to perform best if they took into account how recently a developer has viewed pieces of the code, and if models took into account the spatial proximity of methods within the code. We also found that the accuracy of single-factor models can be improved by combining factors, using a spreading-activation based approach, to produce multi-factor models. Based on these results, we offer concrete guidance about how these models could be used to provide enhanced software development tools that ease the difficulty of navigating through code.

A study of student strategies for the corrective maintenance of concurrent software

Graduates of computer science degree programs are increasingly being asked to maintain large, multi-threaded software systems; however, the maintenance of such systems is typically not well-covered by software engineering texts or curricula. We conducted a think-aloud study with 15 students in a graduate-level computer science class to discover the strategies that students apply, and to what effect, in performing corrective maintenance on concurrent software. We collected think-aloud and action protocols, and annotated the protocols for a number of behavioral attributes and maintenance strategies. We divided the protocols into groups based on the success of the participant in both diagnosing and correcting the failure. We evaluated these groups for statistically significant differences in these attributes and strategies. In this paper, we report a number of interesting observations that came from this study. All participants performed diagnostic executions of the program to aid program comprehension; however, the participants that used this as their predominant strategy for diagnosing the fault were all unsuccessful. Among the participants that successfully diagnosed the fault and displayed high confidence in their diagnosis, we found two commonalities. They all recognized that the fault involved the violation of a concurrent-programming idiom. And, they all constructed detailed behavioral models (similar to UML sequence diagrams) of execution scenarios. We present detailed analyses to explain the attributes that correlated with success or lack of success. Based on these analyses, we make recommendations for improving software engineering curriculums by better training students how to apply these strategies effectively.

The patchworks code editor: toward faster navigation with less code arranging and fewer navigation mistakes

Increasingly, people are faced with navigating large information spaces, and making such navigation efficient is of paramount concern. In this paper, we focus on the problems programmers face in navigating large code bases, and propose a novel code editor, Patchworks, that addresses the problems. In particular, Patchworks leverages two new interface idioms - the patch grid and the ribbon - to help programmers navigate more quickly, make fewer navigation errors, and spend less time arranging their code. To validate Patchworks, we conducted a user study that compared Patchworks to two existing code editors: the traditional file-based editor, Eclipse, and the newer canvas-based editor, Code Bubbles. Our results showed (1) that programmers using Patchworks were able to navigate significantly faster than with Eclipse (and comparably with Code Bubbles), (2) that programmers using Patchworks made significantly fewer navigation errors than with Code Bubbles or Eclipse, and (3) that programmers using Patchworks spent significantly less time arranging their code than with Code Bubbles (and comparably with Eclipse).

Idea Garden: Situated Support for Problem Solving by End-User Programmers

Although there have been many advances in end-user programming environments, recent empirical studies report that programming still remains difficult for end users. We hypothesize that one reason may be lack of effective support for helping end-user programmers problem-solve their own way around barriers they encounter. Therefore, in this paper, we describe the Idea Garden, a concept designed to help end-user programmers generate new ideas and problem-solve when they run into barriers. The Idea Garden has its roots in Minimalist Learning Theory and problem-solving theories. Our proof-of-concept prototype of the Idea Garden concept in the CoScripter end-user programming environment currently targets three barriers reported in end-user programming literature. It does so using an integrated, just-in-time combination of scaffolding for problem-solving strategies, for design patterns, and for programming concepts. Our empirical results showed that this approach helped enduser programmers overcome all three types of barriers our prototype targeted.

From barriers to learning in the idea garden: An empirical study

How can end-user programming environments better help their users overcome programming barriers? We have been investigating an approach called Idea Gardening, which addresses this problem by helping end users to help themselves overcome barriers in the context of “doing”. In this paper, we report on a qualitative empirical study of how effectively an Idea Garden prototype helped end users overcome programming barriers in the CoScripter environment, and the extent to which participants learned after interacting with our features. Our results showed that 9 out of 10 participants who encountered barriers and then used the Idea Garden, overcame their barriers. Further, all 9 went on to demonstrate evidence of having learned the programming concepts, patterns, and strategies relevant to overcoming these barriers.

End-user programmers in trouble: Can the Idea Garden help them to help themselves?

End-user programmers often get stuck because they do not know how to overcome their barriers. We have previously presented an approach called the Idea Garden, which makes minimalist, on-demand problem-solving support available to end-user programmers in trouble. Its goal is to encourage end users to help themselves learn how to overcome programming difficulties as they encounter them. In this paper, we investigate whether the Idea Garden approach helps end-user programmers problem-solve their programs on their own. We ran a statistical experiment with 123 end-user programmers. The experiments results showed that, even when the Idea Garden was no longer available, participants with little knowledge of programming who previously used the Idea Garden were able to produce higher-quality programs than those who had not used the Idea Garden.

An approach to implementing dynamic adaptation in C

This paper describes TRAP/C++, a software tool that enables new adaptable behavior to be added to existing C++ programs in a transparent fashion. In previous investigations, we used an aspect-oriented approach to manually define aspects for adaptation infrastructure, which were woven into the original application code at compile time. In follow-on work, we developed TRAP, a transparent shaping technique for automatically generating adaptation aspects, where TRAP/J is a specific instantiation of TRAP. This paper presents our work into building TRAP/C++, which was intended to be a port of TRAP/J into C++. Designing TRAP/C++ required us to overcome two major hurdles: lack of reflection in C++ and the incompatibility between the management of objects in C++ and the aspect weaving technique used in TRAP/J. We used generative programming methods to produce two tools, TrapGen and TrapCC, that work together to produce the desired TRAP/C++ functionality. Details of the TRAP/C++ architecture and operation are presented, which we illustrate with a description of a case study that adds dynamic auditing capabilities to an existing distributed C++ application.