Abstract: Methods, systems, and articles of manufacture consistent with the present invention provide for asynchronous dynamic deployment of rule engines that are used to determine exposure to failure of computer-based systems. New rule engines are published to a network and received by a wrapper, which encapsulates one or more rule engines. When executed within the wrapper, a rule engine receives subscribed-to input data about a computer-based system and executes a rule that defines a logic for determining exposure to failure of the computer-based system based on the received input data. The rule engine outputs an output data responsive to a determination that there is an exposure to failure.

Abstract: Methods, systems, and articles of manufacture consistent with the present invention provide for managing exposure to failure for computer-based systems. Information about a computer-based system is asynchronously received. An exposure level to failure of the computer-based system is calculated based on the received information. A stability of the computer-based system is determined based on the exposure level. A stability indication is output responsive to the determined stability.

Abstract: A system for creating and editing checks for a knowledge automation engine to use in detecting product issues on products. A knowledge automation engine may evaluate a check against a fact to detect a product issue on a product and provide a client of the product remediation information. A check may contain a product issue description, a rule to evaluate against a fact in order to detect the product issue, and remediation information to help a client address the product issue if the product issue is detected on the product. Product issues may include product installation validation and known product bugs. Facts used by the knowledge automation engine may include product configuration facts. Statistics on check execution results may be accumulated to provide additional information on products through their life cycle.

Abstract: A system for creating and editing checks for a knowledge automation engine to use in detecting product issues on products. A knowledge automation engine may evaluate a check against a fact to detect a product issue on a product and provide a user of the product remediation information. A check may contain a product issue description, a rule to evaluate against a fact in order to detect the product issue, and remediation information to help a user address the product issue if the product issue is detected on the product. Product issues may include product installation validation and known product bugs. Facts used by the knowledge automation engine may include product configuration facts. Checks may be created and edited using a standard interface.

Abstract: A check for a knowledge automation engine to use in detecting product issues on products. A knowledge automation engine may evaluate a check against a fact to detect a product issue on a product and provide a user of the product remediation information. A check may contain a product issue description, a rule to evaluate against a fact in order to detect the product issue, and remediation information to help a user address the product issue if the product issue is detected on the product. Product issues may include product installation validation and known product bugs. Facts used by the knowledge automation engine may include product configuration facts.

Abstract: A system and method for identifying problems with a system configuration may evaluate system configuration information against one or more configuration recommendations or rules. The evaluated system configuration may include various types of software and hardware components which may impact the operations of the computer system. Rules may be any information identifying an issue or describing a recommended configuration for the software or hardware component. A knowledge-based language or a programming language analyzer may be used to specify the rules. In one embodiment, a rules engine may be used as part of the problem detection application to evaluate configuration data against associated rules. A rules engine may be any mechanism used to recognize, interpret and process the configuration data against the rules. The results of the evaluation process may be stored for further analysis.

Abstract: A knowledge automation engine to use in detecting product issues on products. A knowledge automation engine may evaluate a check against a fact to detect a product issue on a product and provide a user of the product remediation information. A check may contain a product issue description, a rule to evaluate against a fact in order to detect the product issue, and remediation information to help a user address the product issue if the product issue is detected on the product. Product issues may include product installation validation and known product bugs. Facts used by the knowledge automation engine may include product configuration facts.

Abstract: Fact collection for a knowledge automation engine to use in detecting product issues on products. A knowledge automation engine may evaluate a check against a fact to detect a product issue on a product and provide a user of the product remediation information. A check may contain a product issue description, a rule to evaluate against a fact in order to detect the product issue, and remediation information to help a user address the product issue if the product issue is detected on the product. Product issues may include product installation validation and known product bugs. Facts used by the knowledge automation engine may include product configuration facts. Static facts may be collected into a fact repository. A fact collector may be used to collect facts not found in the fact repository but needed to execute checks on the knowledge automation engine.

Abstract: A platform independent analysis architecture analyzes memory images for computer programs. The analysis architecture is platform independent in that it is not tied to a particular version of a computer program and is not dependent on the presence or absence of patches. In addition, the analysis architecture is not tied to the hardware architecture on which the analysis architecture runs. The analysis architecture dynamically determines data type definitions for a computer program to account for the hardware architecture on which the computer program runs, the version of the computer program that is running and the presence or absence of patches. As a result, accurate views of data types may be discerned at run time so that the views of the data types may be employed in analyzing memory images such as crash dumps and run time dumps. This analysis architectures greatly assists parties in debugging computer programs as a result.