Homeostasis: Design and Implementation of a Self-Stabilizing Compiler
Aman Nougrahiya, V. Krishna Nandivada

TL;DR
This paper introduces Homeostasis, a novel compiler framework that automatically stabilizes program-abstractions after transformations, ensuring correctness and consistency in compiler analyses and optimizations.
Contribution
It presents the design, formalization, and implementation of Homeostasis, enabling automated stabilization of program-abstractions in compilers.
Findings
Homeostasis effectively automates stabilization in compiler workflows.
Implementation in IMOP shows efficiency and ease of use.
Ensures correctness of compiler phases after program transformations.
Abstract
Mainstream compilers perform a multitude of analyses and optimizations on the given input program. Each analysis (such as points-to analysis) may generate a program-abstraction (such as points-to graph). Each optimization is typically composed of multiple alternating phases of inspection of such program-abstractions and transformations of the program. Upon transformation of a program, the program-abstractions generated by various analyses may become inconsistent with the modified program. Consequently, the correctness of the downstream inspection (and consequent transformation) phases cannot be ensured until the relevant program-abstractions are stabilized; that is, the program-abstractions are either invalidated or made consistent with the modified program. In general, the existing compiler frameworks do not perform automated stabilization of the program-abstractions and instead leave…
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Taxonomy
TopicsParallel Computing and Optimization Techniques · Cloud Computing and Resource Management · Software System Performance and Reliability
