Automating Endurance Test for Flash-based Storage Devices in Samsung Electronics

Jinkook Kim, Minseok Jeon, Sejeong Jang, Hakjoo Oh

Abstract: We present ARES, an automated framework for writing endurance tests on flash-based storage devices. Since flash-based storages such as solid-state drives and SD cards have a limited capacity for processing data write requests, it is important for manufacturers to accurately test and specify the maximum amount of data writes that their products are guaranteed to withstand. Unfortunately, however, writing such an endurance test is mostly conducted manually in practice, which is difficult, laborious, and sometimes inaccurate. To address this issue, we present ARES, a learning-based automated approach for generating endurance tests on flash-based storage devices. ARES is built on two ideas. First, we observe that the search space of endurance tests can be effectively reduced by devising abstract relative write patterns. Second, we use a learning algorithm based on genetic programming in order to find worse-case write patterns efficiently. The experimental results demonstrate that ARES is capable of successfully learning highquality write patterns. The performance of the learned write patterns is superior to that of the manual tests designed by human engineers in Samsung Electronics. Especially for 32GB USB, ARES identified a write pattern that is 26% more effective than the manually crafted write pattern that has been used until recently.

External IDs:dblp:conf/icst/KimJJO23