RAM usage optimization for automatically generated tests for Autosar RTE

Napretkom automobilske industrije dolazi do povećane potrebe za razvojem i održavanjem programske podrške ugradbenih sustava u automobilu. Ugradbeni računalni sustavi su ograničeni resursima potrebnima za rad, pa tako i radnom memorijom. U ovom radu bilo je potrebno smanjiti potrošnju radne memorije automatski generiranih testova ugradbenog računalnog sustava zasnovanog na Infineon Tricore AURIX mikrokontroleru. Testni programski kod u C programskom jeziku generira se koristeći Python alate nad C programskim kodom. U svrhu optimizacije radne memorije primijenjene su metode inverzije petlje, otpetljavanje petlje, smanjenje veličine varijabli, zamjena globalnih i lokalnih varijabli, poravnavanje memorije, zamjena strukture s unijom i heurističke metode. Osim navedenih metoda, testirane su i razine optimizacije prevoditelja, no one nisu testirane na razvojnom sustavu. Optimizirani programski kod je uspješno prošao testiranja te je korištenjem navedenih metoda ušteđeno do 4,01% radne memorije.With the advancement of the automotive industry, a need to develop and maintain software for in-car embedded systems has risen. Embedded systems are limited with the resources needed to operate, including random access memory. In this paper, it was necessary to reduce the consumption of random access memory of automatically generated tests for embedded computer systems based on Infineon Tricore AURIX microcontroller. The test program code in the programming language C was generated using the Python tools on the C programming code. The techniques used for reducing the consumption of RAM are loop inversion, loop unrolling, reducing the sizes of the variables, switching global and local variables, memory alignment, replacing structures with unions and heuristic methods. Also, compiler optimization options were used but not tested on the system. The optimized program code successfully apssed all the tests and a total consumption of RAM was reduced by up to 4.01%