Value Type Segmentation for Memory Efficiency
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Solution Overview
Problem
Current programming languages face performance and memory inefficiencies due to object identity costs, particularly for small objects, which can be mitigated by introducing value types that do not have identity and are stored as flattened representations, passed by value, and optimized for storage and access.
Innovation Solution
Implementing value types in programming languages that are defined by named components, behavior, and access control, without identity headers, allowing for storage as flattened representations and optimized pointer management, including atomic operations and bounds on storage costs, to enhance memory and performance efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If objects include identity headers and are accessed by pointers, then object identity and encapsulation are supported, but memory footprint and access performance deteriorate
Solution Approach 1:
The invention segments types into two categories: reference types that include identity headers and value types that exclude them. This segmentation allows the system to apply identity support only where necessary, reducing memory footprint for types that don't require identity while maintaining it for types that do.
Solution Approach 2:
The invention applies different quality characteristics to different parts of the type system. Value types have the local quality of being headerless and stored in-place, while reference types maintain the traditional object structure with headers. This local differentiation optimizes memory usage for each type based on its specific needs.
2Reliability
If objects include identity headers and are accessed by pointers, then object identity is maintained, but access performance and locality deteriorate
Solution Approach 1:
The invention segments types into reference types with pointers and value types stored in-place. This segmentation enables direct access to value types without pointer dereferencing, improving access performance while maintaining identity support through the hybrid type system.
Solution Approach 2:
The invention uses copying semantics for value types, where values are copied directly to and from the stack or registers rather than being accessed through pointers. This copying approach eliminates pointer indirection and improves access speed while maintaining data integrity.
3Weight of stationary object
If primitive types are used without identity, then memory footprint and access performance improve, but encapsulation and maintainability deteriorate
Solution Approach 1:
The invention makes value types universal by allowing them to have named components, behavior (methods), and access control, making them multi-functional. They can serve both as memory-efficient storage containers and as encapsulated objects with defined interfaces, combining the benefits of primitives and objects.
Solution Approach 2:
The invention changes the parameters of value types to include encapsulation features such as private fields, public accessors, and defined behavior. This parameter change transforms simple data containers into encapsulated objects that maintain both memory efficiency and software design quality.
4Speed
If the number of primitive types is expanded to solve specific problems, then performance for specific cases improves, but language complexity and adaptability to new problems deteriorate
Solution Approach 1:
The invention creates a universal value type mechanism that can be applied to any custom type, eliminating the need to expand the set of primitive types. This universal approach maintains language simplicity while providing performance benefits for all value types through a single coherent framework.
Data Source
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AI summary
In one approach, a method comprises receiving one or more higher-level instructions specifying to assign a value of a particular value type to a particular container of a plurality of containers, wherein the plurality of containers represent a data structure for maintaining one or more variables during execution of a block of code, wherein at least two containers of the plurality of containers are different sizes; generating one or more lower-level instructions that assign the value to the particular container based on applying one or more assignment rules to the one or more higher-level instructions based on the particular value type and executing the one or more lower-level instructions.