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Invariant-based Program Repair. (arXiv:2312.16652v1 [cs.SE])

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This paper describes a formal general-purpose automated program repair (APR)
framework based on the concept of program invariants. In the presented repair
framework, the execution traces of a defected program are dynamically analyzed
to infer specifications $\varphi_{correct}$ and $\varphi_{violated}$, where
$\varphi_{correct}$ represents the set of likely invariants (good patterns)
required for a run to be successful and $\varphi_{violated}$ represents the set
of likely suspicious invariants (bad patterns) that result in the bug in the
defected program. These specifications are then refined using rigorous program
analysis techniques, which are also used to drive the repair process towards
feasible patches and assess the correctness of generated patches.We demonstrate
the usefulness of leveraging invariants in APR by developing an invariant-based
repair system for performance bugs. The initial analysis shows the
effectiveness of invariant-based APR in handling performance bugs by producing
patches that ensure program's efficiency increase without adversely impacting
its functionality.

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