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.
Many theories of human debugging rely on complex mental constructs that offer little practical advice to builders of software engineering tools. Although hypotheses are important in debugging, a ...theory of navigation adds more practical value to our understanding of how programmers debug. Therefore, in this paper, we reconsider how people go about debugging in large collections of source code using a modern programming environment. We present an information foraging theory of debugging that treats programmer navigation during debugging as being analogous to a predator following scent to find prey in the wild. The theory proposes that constructs of scent and topology provide enough information to describe and predict programmer navigation during debugging, without reference to mental states such as hypotheses. We investigate the scope of our theory through an empirical study of 10 professional programmers debugging a real-world open source program. We found that the programmers' verbalizations far more often concerned scent-following than hypotheses. To evaluate the predictiveness of our theory, we created an executable model that predicted programmer navigation behavior more accurately than comparable models that did not consider information scent. Finally, we discuss the implications of our results for enhancing software engineering tools.
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.
End-user programmers may not be aware of many software engineering practices that would add greater discipline to their efforts, and even if they are aware of them, these practices may seem too ...costly (in terms of time) to use. Without taking advantage of at least some of these practices, the software these end users create seems likely to continue to be less reliable than it could be. We are working on several ways of lowering both the perceived and actual costs of systematic software engineering practices, and on making their benefits more visible and immediate. Our approach is to leverage the user's cognitive effort through the use of distributed cognition, in which the system and user collaboratively work systematically to reason about the program the end user is creating. This paper demonstrates this concept with a few of our past efforts, and then presents three of our current efforts in this direction.
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. PUBLICATION ABSTRACT
Programmers spend a substantial fraction of their debugging time by navigating through source code, yet little is known about how programmers navigate. With the continuing growth in size and ...complexity of software, this fraction of time is likely to increase, which presents challenges to those seeking both to understand and address the needs of programmers during debugging. Therefore, we investigated the applicability a theory from another domain, namely information foraging theory, to the problem of programmers’ navigation during software maintenance. The goal was to determine the theory’s ability to provide a foundational understanding that could inform future tool builders aiming to support programmer navigation. To perform this investigation, we first defined constructs and propositions for a new variant of information foraging theory for software maintenance. We then operationalized the constructs in different ways and built three executable models to allow for empirical investigation. We developed a simple information-scent-only model of navigation, a more advanced model of programmer navigation, named Programmer Flow by Information Scent (PFIS), which accounts for the topological structure of source code, and PFIS 2, a refinement of PFIS that maintains an up-to-date model of source code on the fly and models information scent even in the absence of explicit information about stated goals. We then used the models in three empirical studies to evaluate the applicability of information foraging theory to this domain. First, we conducted a lab study of 12 IBM programmers working on a bug report and feature request. Second, we conducted an analysis of issues and revisions collected from Sourceforge.net. Finally, we collected programmer navigation behavior, revisions and issues from a field study of programmers working in various groups at IBM. All three models predicted programmers’ navigation behavior, including where programmers allocated their time among patches, where programmers went, or where programmers made changes to fix defects. These results indicate that information foraging theory can predict and explain programmer navigation behavior, and imply that tools based on the principles of information foraging theory will be able to predict subsequent navigation behavior and potentially assist where programmers should go to make changes to fix bugs.
Many researchers have analyzed visual language design using Cognitive Dimensions (CDs), but some have reinterpreted the purpose, vocabulary, and use of CDs, potentially creating confusion. In ...particular, those who have used CDs to convince themselves or others that their language is usable have tended to ignore or downplay the tradeoffs inherent in design, resulting in evaluations that provide few insights. Researchers who do not consider
who,
when, and
how best to analyze a visual language using CDs are likely to miss the most useful opportunities to uncover problems in their visual languages. In this paper, we consider common breakdowns when using CDs in analysis. Then, using three case studies, we demonstrate how the
who,
when, and
how circumstances under which CDs are applied impact the gains that can be expected.
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