Muts, KaterynaKaterynaMuts2023-01-302023-01-302023-01-26http://hdl.handle.net/11420/14664Compiler-based optimizations are efficient techniques to improve a program to be compiled. Function inlining is a well-known compiler-based optimization that substitutes function calls by the body of the function. The data represent the results of multiobjective function inlining for hard real-time systems with code size, energy consumption and worst-case execution time (WCET) as objectives. Since the analyses of energy consumption and WCET are very time-consuming at compile time, search space reduction and predictions based on machine learning techniques were applied to speed up the multiobjective function inlining at compile time.enhttps://creativecommons.org/publicdomain/zero/1.0/Compiler-based optimizationFunction InliningMachine learningSearch space reductionHard real-time systemIngenieurwissenschaftenMultiobjective code compression and function inlining for hard real-time systemsDataset10.15480/336.489010.15480/336.489010.1007/s11241-010-9101-x10.15480/882.4799ResearchData