Application Error Prediction System Using Dynamic Execution Sequences
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Solution Overview
Problem
Existing error prediction methods for software applications are inadequate in addressing runtime errors, especially those caused by inconsistencies between interdependent applications and external factors like user load, and fail to consider cascading errors in networked components, leading to inefficiencies in maintenance and increased downtime.
Innovation Solution
A system and method that generate timestamped event logs, model user requests based on arrival time and functionality, create execution sequences of software components, and predict application failures using a holistic approach, analyzing both predicted and actual failures to provide preventive maintenance measures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing error prediction methods are used, then predefined errors during development phase can be predicted, but runtime errors including cascading errors in networked components cannot be effectively predicted
Solution Approach 1:
The system dynamically adapts its error prediction approach by transitioning from static predefined error checking to runtime dynamic analysis. It monitors actual execution sequences, user requests, and component interactions in real-time, allowing the system to detect and predict both predefined and unexpected runtime errors including cascading failures across networked components.
Solution Approach 2:
The error prediction system is designed to handle multiple types of errors universally through a single integrated framework. It can predict predefined errors, runtime errors, cascading errors, and errors caused by external factors like user load simultaneously by analyzing execution sequences and component interdependencies, making the system versatile across different error scenarios.
2Reliability
If a holistic approach analyzing multiple aspects independently and in synergy is implemented, then overall error prediction capability improves, but system complexity increases
Solution Approach 1:
The holistic error prediction system is segmented into independent analysis modules that each handle specific aspects: execution sequence analysis, user request modeling, component status monitoring, and error pattern recognition. Each module operates independently but contributes to the overall prediction, allowing the system to maintain complexity while achieving comprehensive error detection through modular architecture.
3Loss of time
If preventive maintenance measures are implemented by analyzing predicted and actual failures, then downtime is reduced, but management efforts increase
Solution Approach 1:
The system implements self-service by automatically comparing predicted failures with actual failures and generating preventive maintenance measures without requiring extensive manual intervention. The automated analysis of discrepancies between predicted and actual error patterns enables the system to autonomously identify maintenance needs, reducing both downtime and the management effort required for preventive maintenance.
Data Source
AI summary
A system and a method for predicting errors and failure of an application and performing preventive maintenance measures is disclosed. The present invention provides for generating timestamped event logs and extracting data which includes application Id, service Id, user Id, host, error information, resource information, user request data and frequently used execution sequences of associated software components. Further, multiple user requests are modelled based on information extracted from the timestamped event logs and an execution sequence of associated software components is created based on data extracted from timestamped event logs. Further, an execution scheme is generated based on modelled user requests, execution sequence of associated applications and resource status. Yet further, propensity of failure of application is predicted based on the timestamped event logs, user requests, execution sequence of associated applications, resource status and execution scheme of the application by applying a holistic technique.