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https://dx.doi.org/10.60882/ci...
Conference object . 2023
Data sources: Datacite
https://dx.doi.org/10.60882/ci...
Conference object . 2023
Data sources: Datacite
https://dx.doi.org/10.60882/ci...
Conference object . 2023
Data sources: Datacite
https://dx.doi.org/10.60882/ci...
Conference object . 2023
Data sources: Datacite
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Debugging inputs

Authors: Lukas Kirschner; Ezekiel O. Soremekun; Andreas Zeller;
Abstract

When a program fails to process an input, it need not be the program code that is at fault. It can also be that the input data is faulty, for instance as result of data corruption. To get the data processed, one then has to debug the input data—that is, (1) identify which parts of the input data prevent processing, and (2) recover as much of the (valuable) input data as possible. In this paper, we present a general-purpose algorithm called ddmax that addresses these problems automatically. Through experiments, ddmax maximizes the subset of the input that can still be processed by the program, thus recovering and repairing as much data as possible; the difference between the original failing input and the “maximized” passing input includes all input fragments that could not be processed. To the best of our knowledge, ddmax is the first approach that fixes faults in the input data without requiring program analysis. In our evaluation, ddmax repaired about 69% of input files and recovered about 78% of data within one minute per input.

Country
Luxembourg
Keywords

: Computer science [C05] [Engineering, computing & technology], repair, program inputs, : Sciences informatiques [C05] [Ingénierie, informatique & technologie], debugging

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    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    13
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Top 10%
Green