Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Many large scale object-oriented applications suffer from chronic performance problems. The many layers of generalised frameworks and libraries that these applications are typically assembled from leads to seemingly simple tasks requiring many thousands of operations to complete. Addressing these performance problems with traditional profiling tools is difficult because of the scale and complexity of the dynamic behaviour being exhibited. A alth of detailed data is collected but costs are thinly distributed across thousands of methods leaving few easily identifiable performance optimisation opportunities. Hover  believe there are repeated patterns of method calls hidden within the profile data that represent performance critical sections of code.  plan to investigate new approaches to analysing typical performance data sets to identify these repeated patterns. Our initial work shows some promising results - being able to identify, within an application with over 64 thousand unique calling contexts, ten patterns that account for over 50% of the execution time.
['David Maplesden']
I am writing a research paper on a idea Performance analysis of object-oriented software
[{"from": "human", "value": "I am writing a research paper on a idea Performance analysis of object-oriented software"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Many large scale object-oriented applications suffer from chronic performance problems. The many layers of generalised frameworks and libraries that these applications are typically assembled from leads to seemingly simple tasks requiring many thousands of operations to complete. Addressing these performance problems with traditional profiling tools is difficult because of the scale and complexity of the dynamic behaviour being exhibited. A alth of detailed data is collected but costs are thinly distributed across thousands of methods leaving few easily identifiable performance optimisation opportunities. Hover  believe there are repeated patterns of method calls hidden within the profile data that represent performance critical sections of code.  plan to investigate new approaches to analysing typical performance data sets to identify these repeated patterns. Our initial work shows some promising results - being able to identify, within an application with over 64 thousand unique calling contexts, ten patterns that account for over 50% of the execution time."}]