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Competitive Online Clique Clustering.

, , and . CIAC, volume 7878 of Lecture Notes in Computer Science, page 221-233. Springer, (2013)

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Diagnosing Sample Ratio Mismatch in Online Controlled Experiments: A Taxonomy and Rules of Thumb for Practitioners., , , , , , and . KDD, page 2156-2164. ACM, (2019)A/B Integrations: 7 Lessons Learned from Enabling A/B testing as a Product Feature., , , , , and . ICSE-SEIP, page 304-314. IEEE, (2023)Safe velocity: a practical guide to software deployment at scale using controlled rollout., , , and . ICSE (SEIP), page 11-20. IEEE / ACM, (2019)The Benefits of Controlled Experimentation at Scale., , , and . SEAA, page 18-26. IEEE Computer Society, (2017)The Online Controlled Experiment Lifecycle., , , and . IEEE Software, 37 (2): 60-67 (2020)The evolution of continuous experimentation in software product development: from data to a data-driven organization at scale., , , and . ICSE, page 770-780. IEEE / ACM, (2017)Three key checklists and remedies for trustworthy analysis of online controlled experiments at scale., , , , , and . ICSE (SEIP), page 1-10. IEEE / ACM, (2019)Online Controlled Experimentation at Scale: An Empirical Survey on the Current State of A/B Testing., , , and . SEAA, page 68-72. IEEE Computer Society, (2018)Experimentation growth: Evolving trustworthy A/B testing capabilities in online software companies., , , , , and . Journal of Software: Evolution and Process, (2018)Early Value Argumentation and Prediction: An Iterative Approach to Quantifying Feature Value., , and . PROFES, volume 9459 of Lecture Notes in Computer Science, page 16-23. Springer, (2015)