2020 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC) 2020
DOI: 10.1109/vl/hcc50065.2020.9127254
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Understanding and Inferring Units in Spreadsheets

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Cited by 9 publications
(4 citation statements)
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“…Blackwell's attention investment model of end-user programming posits that the user weighs any effort invested in authoring their program (in our case, the spreadsheet) against the future payoff of that investment [9]. While this has been shown to be the case in the context of error testing [110,112], it has only been speculated to be a factor in the problem of structuring data. We found participants explicitly accounting for the longevity of the spreadsheet and the frequency of its use as part of the decision to invest attention in building structure (Section 5.2.2).…”
Section: Discussion 81 Comparison With Previous Workmentioning
confidence: 99%
“…Blackwell's attention investment model of end-user programming posits that the user weighs any effort invested in authoring their program (in our case, the spreadsheet) against the future payoff of that investment [9]. While this has been shown to be the case in the context of error testing [110,112], it has only been speculated to be a factor in the problem of structuring data. We found participants explicitly accounting for the longevity of the spreadsheet and the frequency of its use as part of the decision to invest attention in building structure (Section 5.2.2).…”
Section: Discussion 81 Comparison With Previous Workmentioning
confidence: 99%
“…Testing methods like WYSIWYT (What You See Is What You Test) integrate white box testing into spreadsheet use [50]. Debugging tools analyse formula dependencies or suggest fixes [14,83]. Other work focuses on developing higher level abstractions to facilitate reuse within spreadsheets, such as lambdas [67], sheet-defined functions [28,41], and grid-based reuse [26].…”
Section: End-user Programmingmentioning
confidence: 99%
“…Examples include data repair tools such as UGuide [19], [20]. The interaction pattern that combines human inputs and automatic inference is also known as mixed-initiative interfaces [21], [22] in the context of graphical user interfaces, and as human-in-the-loop data analytics (HILDA) [22], [23] in the context of data science. However, both of these are general patterns, rather than specific technical frameworks.…”
Section: Semi-automatic Data Wranglingmentioning
confidence: 99%