Koc, Ugur
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2

SATune : a study-driven auto-tuning approach for configu..:

, In: Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering,
Koc, Ugur ; Mordahl, Austin ; Wei, Shiyi.. - p. 330-342 , 2021
 
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3

An empirical study of real-world variability bugs detected ..:

, In: Proceedings of the 2019 27th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering,
Mordahl, Austin ; Oh, Jeho ; Koc, Ugur.. - p. 50-61 , 2019
 
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4

Localizing configurations in highly-configurable systems:

, In: Proceedings of the 22nd International Systems and Software Product Line Conference - Volume 1,
Gazzillo, Paul ; Koc, Ugur ; Nguyen, ThanhVu. - p. 269-273 , 2018
 
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5

Approaches for computing test‐case‐aware covering arrays:

Koc, Ugur ; Yilmaz, Cemal
Software Testing, Verification and Reliability.  28 (2018)  7 - p. , 2018
 
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Identifying and documenting false positive patterns generat..:

, In: Proceedings of the 4th International Workshop on Software Engineering Research and Industrial Practice,
 
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7

Learning a classifier for false positive error reports emit..:

, In: Proceedings of the 1st ACM SIGPLAN International Workshop on Machine Learning and Programming Languages,
 
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8

iGen: dynamic interaction inference for configurable softwa..:

, In: Proceedings of the 2016 24th ACM SIGSOFT International Symposium on Foundations of Software Engineering,
Nguyen, ThanhVu ; Koc, Ugur ; Cheng, Javran.. - p. 655-665 , 2016
 
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15

amordahl/satune: ASE'21 Revised Artifact:

Ugur Koç ; Austin Mordahl ; Shiyi Wei..
https://github.com/amordahl/satune/tree/v1.3.  , 2021
 
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