Putting information foraging theory to work: Community-based design patterns for programming tools

Nabi, Tahmid; Sweeney, Kyle M. D.; Lichlyter, Sam; Piorkowski, David; Scaffidi, Christopher; Burnett, Margaret; Fleming, Scott

doi:10.1109/vlhcc.2016.7739675

Cited by 8 publications

(2 citation statements)

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“…We then switched to the topic of the week, usually introducing the underlying theory for about thirty minutes. For the lecture on basic strategies of code navigation, for instance, we introduced the students to both typical strategies (top-down comprehension, bottom-up comprehension, systematic comprehension, opportunistic comprehension, per [13]) as well as information foraging theory [16,32] to explain why different situations may call for a different approach.…”

Section: Basic Structure Of Each Lecturementioning

confidence: 99%

“…More recently, too, several studies have used fMRI techniques to study the cognitive processes of programmers at work (e.g., [18], [22], [25]). Information foraging theory, perhaps the most well-known distillation of the aforementioned observations, essentially likens the search for information in the source code to an animal's hunt for its prey -both try to optimize the energy expended versus the expected payoff [16,32].…”

Section: Introductionmentioning

confidence: 99%

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Reading to Write Code: An Experience Report of a Reverse Engineering and Modeling Course

Ryan

Soria

Dreef

et al. 2022

2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering Education and Training (ICSE-SEET)

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A substantial portion of any software engineer's job is reading code. Despite the criticality of this skill in a budding software engineer, reading code-and more specifically, techniques on how to read code when integrating oneself into a large existing software project-is often neglected in the typical software engineering education. As part of a new professional Master of Software Engineering at the University of California, Irvine, we designed and delivered a "reading to write code" course from the ground up. Titled Reverse Engineering and Modeling, the course introduces students to techniques they can use to become familiar with a large code base, so they are able to make meaningful contributions. In this paper, we briefly introduce the Master program and its underlying philosophy, articulate the course's learning outcomes, present the design of the course, and provide a detailed reflection on our experiences in terms of what went well, what did not go well, what we do not know yet, and what our next steps are in preparing for the forthcoming incarnation of the course in Spring 2022. In so doing, we hope to provide a baseline together with lessons learned for others who may be interested in instituting a similar course at their institution.

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Section: Basic Structure Of Each Lecturementioning

confidence: 99%