Corpus ID: 235829850

On the impact of Performance Antipatterns in multi-objective software model refactoring optimization

@article{Cortellessa2021OnTI,
  title={On the impact of Performance Antipatterns in multi-objective software model refactoring optimization},
  author={V. Cortellessa and Daniele Di Pompeo and Vincenzo Stoico and Michele Tucci},
  journal={ArXiv},
  year={2021},
  volume={abs/2107.06127}
}
Software quality estimation is a challenging and time-consuming activity, and models are crucial to face the complexity of such activity on modern software applications. One main challenge is that the improvement of distinctive quality attributes may require contrasting refactoring actions on an application, as for trade-off between performance and reliability. In such cases, multi-objective optimization can provide the designer with a wider view on these trade-offs and, consequently, can lead… Expand

Figures and Tables from this paper

References

SHOWING 1-10 OF 51 REFERENCES
EASIER: An Evolutionary Approach for Multi-objective Software ArchItecturE Refactoring
TLDR
This paper introduces EASIER (Evolutionary Approach for multi-objective Software archItecturE Refactoring), that is an approach for optimizing architecture refactoring based on performance and on the intensity of changes, and focuses on the actionable aspects of architectural optimization. Expand
Analyzing the sensitivity of multi-objective software architecture refactoring to configuration characteristics
TLDR
The results show that the E A S I E R thoroughly automated process for software architecture refactoring allows to identify configuration contexts of the evolutionary algorithm in which multi-objective optimization more effectively finds near-optimal Pareto solutions. Expand
Multi-view refactoring of class and activity diagrams using a multi-objective evolutionary algorithm
TLDR
A novel framework that enables software designers to apply refactoring at the model level using a multi-objective evolutionary algorithm to find a trade-off between improving the quality of class and activity diagrams and the statistical evaluation performed on models extracted from four open-source systems confirms the efficiency. Expand
Automatically improve software architecture models for performance, reliability, and cost using evolutionary algorithms
TLDR
This work proposes an automated approach to search the design space for good solutions by applying a multi-criteria genetic algorithm to software architectures modelled with the Palladio Component Model and can be extended to other quantitative quality criteria of software architectures. Expand
PerOpteryx: automated application of tactics in multi-objective software architecture optimization
TLDR
This work proposes an automated approach guided by architectural tactics to search the design space for good solutions and applies multi-objective evolutionary optimization to software architectures modelled with the Palladio Component Model. Expand
A Hybrid Approach for Multi-attribute QoS Optimisation in Component Based Software Systems
TLDR
This paper proposes a combined use of analytical optimization techniques and evolutionary algorithms to efficiently identify a significant set of design alternatives, from which an architecture that best fits the different quality objectives can be selected, and demonstrates the use of this approach on a simple case study. Expand
An evolutionary multiobjective optimization approach to component-based software architecture design
TLDR
AQOSA (Automated Quality-driven Optimization of Software Architecture) toolkit is introduced, which integrates modeling technologies, performance analysis techniques, and advanced evolutionary multiobjective optimization algorithms to improve non-functional properties of systems in an automated manner. Expand
A survey of many-objective optimisation in search-based software engineering
TLDR
A historical perspective and future lines of research concerning the adoption of many-objective optimisation within SBSE are provided, an emerging area that provides advanced techniques to cope with high-dimensional optimisation problems. Expand
Multi-objective test prioritization via a genetic algorithm
  • M. Ray, D. Mohapatra
  • Engineering, Computer Science
  • Innovations in Systems and Software Engineering
  • 2014
TLDR
A method to estimate the criticality of a component within a system and a genetic algorithm-based technique to select test cases out of a large pool of test cases so that the high-critical components would be tested more completely and rigorously than other less- critical components. Expand
Multi-objective software performance optimisation at the architecture level using randomised search rules
TLDR
A novel approach for performance optimisation at the software architecture level named Multiobjective performance Optimisation based on Randomised search rulEs (MORE) is proposed, which is able to achieve more explicable and higher quality solutions than two state-of-the-art techniques. Expand
...
1
2
3
4
5
...