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Mining for Gold: How to Predict Service Contract Performance with Optimal Accuracy Based on Ordinal Risk Assessment Data.

, , , , , and . IEEE SCC, page 315-322. IEEE Computer Society, (2014)

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Selecting Small Yet Effective Set of Test Data.. Applied Informatics, page 1013-1019. IASTED/ACTA Press, (2003)A new solution to test generation for Boolean expressions.. CASCON, page 48. IBM, (1995)Modeling execution time of multi-stage N-version fault-tolerant software., , and . COMPSAC, page 505-511. IEEE, (1990)Causal Modeling based Fault Localization in Cloud Systems using Golden Signals., , , , , , , and . CLOUD, page 124-135. IEEE, (2021)Mining for Gold: How to Predict Service Contract Performance with Optimal Accuracy Based on Ordinal Risk Assessment Data., , , , , and . IEEE SCC, page 315-322. IEEE Computer Society, (2014)Decoding Logs for Automatic Metric Identification., , , , , , and . CLOUD, page 336-343. IEEE, (2024)Understanding the role of sentiment analysis in contract risk classification., , , and . NOMS, page 1-6. IEEE, (2014)Localization of Operational Faults in Cloud Applications by Mining Causal Dependencies in Logs Using Golden Signals., , , , , , and . ICSOC Workshops, volume 12632 of Lecture Notes in Computer Science, page 137-149. Springer, (2020)Automated extraction of security policies from natural-language software documents., , , and . SIGSOFT FSE, page 12. ACM, (2012)Automation of Software Test - Report on the Second Interional Workshop AST 2007., , and . ICSE Companion, page 150-151. IEEE Computer Society, (2007)