SHF: Medium: Early Reliability Modeling and Prediction of Embedded Software Systems

University Of Southern California, Los Angeles CA

Investigators

Abstract

To build high quality software, it is increasingly important for engineers to reason quantitatively about critical system properties, such as performance and reliability, as early as possible in the design process. Ideally, these properties are assessed before significant time and cost are expended on implementation. However, making useful predictions in early design stages is difficult at best due to the interplay among many relevant factors, such as complex properties of software components, effects of the firmware, and conflicts between desired system attributes. In this project, we focus on design-time evaluation of architectures with respect to one key attribute: reliability. The approach we pursue will enable an engineer to build a multi-faceted, hierarchical model of a system and assess its reliability in an incremental, scalable fashion. Moreover, we particularly focus on the area of embedded systems. Embedded systems present a rich target of opportunity for this work as (1) they demand close interplay of software and execution substrate; (2) they are often unencumbered with legacy concerns, allowing easier introduction and exploration of new techniques such as the one we propose; (3) they often have stringent and complex requirements, yet are seldom approached from a software architectural perspective. An extensive evaluation of our research focuses on two measures of interest: tractability (intended to address scalability issues existing in real, complex systems) and sensitivity (intended to address issues of confidence in our predictions under numerous design-time uncertainties).