Overview of the Lambda-* Performance Reasoning Frameworks
CARNEGIE-MELLON UNIV PITTSBURGH PA SOFTWARE ENGINEERING INST
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The Predictable Assembly from Certifiable Code PACC Initiative at the Carnegie Mellon Software Engineering Institute is developing methods and technologies to enable the production of software with predictable behavior by making the application of analytic methods accessible to software engineering practitioners. The use of reasoning frameworks is a means to achieving this goal. A reasoning framework is a packaging of an analysis theory along with other important elements that are needed for its application, such as methods for creating analysis models and evaluating them. Lambda- is a suite of performance reasoning frameworks founded on the principles of Generalized Rate Monotonic Analysis GRMA for predicting the average and worst-case latency of periodic and stochastic tasks in real-time systems. Lambda- can be applied to many different, uniprocessor, real-time systems having a mix of tasks with hard and soft deadlines with periodic and stochastic event interarrivals. Some examples include embedded control systems e.g., avionic, automotive, robotic and multimedia systems e.g., audio mixing. This report provides an overview of the Lambda- performance reasoning frameworks, their current capabilities, and ongoing research. The Lambda- reasoning frameworks have been implemented as a part of the PACC Starter Kit PSK, a development environment that integrates a collection of technologies to enable the development of software with predictable runtime behavior.
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