Towards understanding programs through wear-based filtering
Abstract
Large software projects often require a programmer to make changes to unfamiliar source code. This paper presents the results of a formative observational study of seven professional programmers who use a conventional development environment to update an unfamiliar implementation of a commonly known video game. We describe several usability problems they experience, including keeping oriented in the program’s source text, maintaining the number and layout of open text documents and relying heavily on textual search for navigation. To reduce the cost of transferring knowledge about the program among developers, we propose the idea of wear-based filtering, a combination of computational wear and social filtering. The development environment collects interaction information, as with computational wear, and uses that information to direct the attention of subsequent users, as with social filtering. We present sketches of new visualizations that use wear-based filtering and demonstrate the feasibility of our approach with data drawn from our study.
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Software engineering researchers have produced tools that help reduce developers' navigation costs.
“These and other findings about developers' foraging and navigations (e.g., [26,31,37,44]) have led software engineering researchers to produce tools that help to reduce developers' navigation costs as they look for the information they need [8,17,18,19,22,30,33,43].”
From Foraging and navigations, fundamentally: developers' predictions of value and cost (2016) · cites this paper as [8]
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- Authors
- DeLine, R., Khella, A., Czerwinski, M., & Robertson, G.
- Affiliations
- Microsoft (United States) (US)
- University of Maryland, College Park (US)
- Venue
- Proceedings of the 2005 ACM symposium on Software visualization
- Publisher
- ACM
- Published
- 2005-05-14
- Pages
- 183-192
- OpenAlex
- W2055821246
- Cited by
- 91
- References
- 31
- Citations by year
- 2026: 3 · 2023: 1 · 2022: 1 · 2020: 4 · 2019: 4 · 2018: 1 · 2017: 8 · 2016: 5 · 2015: 4 · 2014: 9 · 2013: 2 · 2012: 5
- FWCI
- 7.05
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM Symposium on Software Visualization (SoftVis) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Research
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Keywords
- social filtering, program comprehension, knowledge transfer, software visualization, development environment
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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