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Object-Oriented Genetic Improvement for Improved Energy Consumption in Google Guava
TLDR
This work uses metaheuristic search to improve Google’s Guava library, finding a semantically equivalent version of com.google.common.ImmutableMultimap with reduced energy consumption and compares it to an independent exhaustive search at each variation point, finding that the meta heuristic has superior performance.
Genetic Programming + Proof Search = Automatic Improvement
TLDR
An alternative to the traditional mutation operators used, employing deterministic proof search in the sequent calculus to yield semantics-preserving transformations on algebraic data types is described.
Automatic Improvement of Apache Spark Queries using Semantics-preserving Program Reduction
TLDR
Hylas is described, a tool for automatically optimising Spark queries embedded in source code via the application of semantics-preserving transformations, inspired by functional programming techniques of "deforestation", which eliminate intermediate data structures from a computation.
Embedded Dynamic Improvement
TLDR
The useful role that can be played by a subtype of improvement programming, which is embedded at variation points, facilitating the creation of adaptive software that can respond online to changes in its execution environment is discussed.
Genetic Programming $$\varvec{+}$$+ Proof Search $$\varvec{=}$$= Automatic Improvement
TLDR
An alternative to the traditional mutation operators used, employing deterministic proof search in the sequent calculus to yield semantics-preserving transformations on algebraic data types is described.
Repairing and Optimizing Hadoop hashCode Implementations
TLDR
It was established that it produces hashCode functions that are at least as good as the original, broken method as well as those produced by a widely-used alternative method from the ‘Apache Commons’ library.
A Research Agenda for Metaheuristic Standardization
TLDR
The development of standardized, explicit, machine-readable descriptions of metaheuristics will greatly advance scientific progress in the field and promote a higher standard of rigor for both communication and reproducibility of results.
Asymptotic Genetic Improvement Programming via Type Functors and Catamorphisms
TLDR
This work presents a novel semantics-preserving point mutation that operates on algebraic data types (ADTs) and can in principle be applied to most ADTs.
Haiku - a Scala Combinator Toolkit for Semi-automated Composition of Metaheuristics
TLDR
Haiku is described, a combinator tool-kit written in the Scala language, which builds upon previous work to further automate the process of metaheuristics generation by automatically composing the external dependencies of components.
Dependency Injection for Programming by Optimization
TLDR
The structural correspondence between Dependency Injection and context-free grammars yields a new class of evolutionary metaheuristics for automated algorithm configuration, which significantly outperform existing configuration algorithms on many problems of interest.
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