Remote embedded devices test framework on the cloud

• Published in: Software testing, verification & reliability verification & reliability, 2021-11, Vol.31 (7), p.n/a
• Main Authors: Choi, Il‐Seok (Benjamin), Jeong, Chang‐Sung
• Format: Article
• Language: English
• Subjects: Adaptive sampling; cloud computing; Clouds; Component reliability; Electronic devices; Embedded systems; Reliability analysis; Reliability aspects; reliability testing; sample devices; Shipments; Smartphones; test automation; Verification
• ISSN: 0960-0833; 1099-1689
• DOI: 10.1002/stvr.1768

Summary Embedded systems have high coupling and dependency among different hardware and software components in heterogeneous layers, which makes location and issue tracking in their testing difficult. Despite these poor verification conditions, even the most important reliability quality verification among embedded system characteristics is verified with insufficient sample size, typical test cases, and general test strategies, following limitations such as development costs and scheduling. As a result, shipments are highly likely to lead to various reliability quality problems because items have not been verified considering reliability quality characteristics. Hence, to address this gap, this study developed remote embedded device test framework on the cloud (RED‐TFC), which has an innovative reliability test manager component that can automatically perform various tests for the evaluation of reliability and performance of distributed shared devices by utilizing the cloud concept. RED‐TFC offers two key enhancements over existing testing services: (i) the adaptive sample scale for reliability test (ASRT), a feature that identifies the most appropriate sample size for performing functionality and reliability tests of remote verification targets connected to the RED‐TFC server; and (ii) the mass sample reliability test (MSRT), which uses a test case that is specific to reliability, with the sample size obtained by ASRT, to perform verification following the Markov prediction process. This paper analyses two Android smartphone models considered the most generic examples, including many embedded components, and presents a method of detecting a high number of reliability problems in smartphones using the proposed RED‐TFC and its implications.