Related papers: Multi-objective Software Architecture Refactoring …
This article seeks to contribute to a nuanced understanding of the integration of Design Structure Matrix (DSM) and genetic algorithms in the context of Complex Systems modelling described within Model-Based System Engineering approach. By…
Software systems nowadays are complex and difficult to maintain due to continuous changes and bad design choices. To handle the complexity of systems, software products are, in general, decomposed in terms of packages/modules containing…
The continuing process of software systems enlargement in size and complexity becomes system design extremely important for software production. In this way, the role of software architecture is significantly important in software…
Geometric programming problems occur frequently in engineering design and management. In multiobjective optimization, the trade-off information between different objective functions is probably the most important piece of information in a…
In this short note, we discuss a goal-oriented multiobjective optimization problem for system performance assessment. The objective function for such optimization problem, which is usually a composite of different performance indices…
Large language models and AI agents have recently shown promise in automating software performance optimization, but existing approaches predominantly rely on local, syntax-driven code transformations. This limits their ability to reason…
Refactoring is the de-facto practice to optimize software health. While several studies propose refactoring strategies to optimize software design through applying design patterns and removing design defects, little is known about how…
When engineering complex and distributed software and hardware systems (increasingly used in many sectors, such as manufacturing, aerospace, transportation, communication, energy, and health-care), quality has become a big issue, since…
Design erosion is a persistent problem within the software engineering discipline. Software designs tend to deteriorate over time and there is a need for tools and techniques that support software architects when dealing with legacy…
Current autonomic computing systems are ad hoc solutions that are designed and implemented from the scratch. When designing software, in most cases two or more patterns are to be composed to solve a bigger problem. A composite design…
This thesis investigates the use of problem-specific knowledge to enhance a genetic algorithm approach to multiple-choice optimisation problems.It shows that such information can significantly enhance performance, but that the choice of…
We present a multi-objective evolutionary optimization algorithm that uses Gaussian process (GP) regression-based models to select trial solutions in a multi-generation iterative procedure. In each generation, a surrogate model is…
In order to design broadband extreme ultraviolet multilayers with many objectives, the multiobjective genetic algorithm and the multiobjective genetics algorithm with reference direction have been improved and combined used. The certain…
In today's construction industry, poor performance often arises due to various factors related to time, finances, and quality. These factors frequently lead to project delays and resource losses, particularly in terms of financial…
Artificial neural network (NN) architecture design is a nontrivial and time-consuming task that often requires a high level of human expertise. Neural architecture search (NAS) serves to automate the design of NN architectures and has…
From self-assembly and protein folding to combinatorial metamaterials, a key challenge in material design is finding the right combination of interacting building blocks that yield targeted properties. Such structures are fiendishly…
Advances in technologies like artificial intelligence and metaverse have led to a proliferation of software systems in business and everyday life. With this widespread penetration, the carbon emissions of software are rapidly growing as…
The choices of hyperparameters have critical effects on the performance of machine learning models. In this paper, we present a general framework that is able to construct an adaptive optimizer, which automatically adjust the appropriate…
The optimization of dynamic problems is both widespread and difficult. When conducting dynamic optimization, a balance between reinitialization and computational expense has to be found. There are multiple approaches to this. In parallel…
Refactoring is a maintenance activity that aims to improve design quality while preserving the behavior of a system. Several (semi)automated approaches have been proposed to support developers in this maintenance activity, based on the…