The success of metaheuristic optimization methods has led to the development of a large variety of algorithm paradigms. However, no algorithm clearly dominates all its competitors on all problems. Instead, the underlying variety of landscapes of ...

Multi-objective optimization problems involve several conflicting objectives that have to be optimized simultaneously. Generating a complete Pareto-optimal front (POF) can be computationally expensive or even infeasible, and for that reason there has ...

The evaluation of the performance of an IT system is a fundamental operation in its benchmarking and optimization. However, despite the general consensus on the importance of this task, little guidance is usually provided to practitioners who need to ...

Limited precision floating point computer implementations of large polynomial arithmetic expressions are nonlinear and dissipative. They are not reversible (irreversible, lack conservation), lose information, and so are robust to perturbations (anti-...

In this paper, we present AI Programmer, a machine learning (ML) system that can automatically generate full software programs, while requiring only minimal human guidance. At its core, AI Programmer uses a genetic algorithm (GA), coupled with a tightly ...

Genetic Improvement (GI) can be used to give better quality software and to create new functionality.

We show that GI can evolve the PowerPC open source GNU C runtime library square root function into cube root, binary logarithm log2 and reciprocal ...

Autonomous Driving Systems (ADSs) are complex critical systems that must be thoroughly tested. Still, assessing the strength of tests for ADSs is an open and complex problem. Weight Coverage is a test criterion targeting ADSs which are based on a ...

Assertion oracles are executable boolean expressions placed inside a software program that verify the correctness of test executions. A perfect assertion oracle passes (returns true) for all correct executions and fails (returns false) for all incorrect ...

In Search-based Software Engineering (SBSE), researchers and practitioners (SBSE users) using multi-objective search algorithms (MOSAs) often select commonly used MOSAs to solve their search problems. Such a selection is usually not justified, and the ...

Routing plays a fundamental role in network applications, but it is especially challenging in Delay Tolerant Networks (DTNs). These are a kind of mobile ad hoc networks made of e.g. (possibly, unmanned) vehicles and humans where, despite a lack of ...

Recent studies show that program synthesis with GE produces code that has different structure compared to human-generated code, e.g., loops and conditions are hardly used. In this article, we extract knowledge from human-generated code to guide ...

Automatic programming, the task of generating computer programs compliant with a specification without a human developer, is usually tackled either via genetic programming methods based on mutation and recombination of programs, or via neural language ...

Genetic programming (GP) based symbolic regression is a stochastic, high-variance algorithm. Its sensitivity to changes in training data is a drawback for practical applications.

In this work, we analyze empirically the variance of GP models on the ...

This poster paper presents 2 recommendations for algorithm developers as best practices in the context of engineering design. Genetic algorithms are well suited for multi-objective optimisation problems which are common in engineering. However, the use ...