A multi-objective approach for Entity Refactoring Set Selection Problem

Chisăliţă-Creţu, Camelia

doi:10.1109/icadiwt.2009.5273850

Cited by 2 publications

(1 citation statement)

References 3 publications

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“…Section 5 states the Multi-Objective Refactoring Set Selection Problem as a particular refactoring selection problem. A more restraint problem definition for the case when a single refactoring is searched is discussed too, as Multi-Objective Single Refactoring Selection Problem in (Chisȃliţȃ-Creţu & Vescan, 2009), (Chisȃliţȃ-Creţu & Vescan, 2009). Specific conflicting objectives are studied in order to identify the optimal set of refactorings.…”

Section: Part 3 Electrical Engineering and Applicationsmentioning

confidence: 99%

Advances in Computer Science and Engineering

Sarbazi-Azad¹,

Parhami²,

Miremadi³

et al. 2009

Communications in Computer and Information Science

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Dr. Matthias Schmidt was born in 1978 in Germany. He studied industrial engineering and economics in Hanover. After his work as a project engineer he finished his doctoral thesis in the field of assembly logistics and received his doctor's decree from the Faculty of Mechanical Engineering of the Leibniz University Hannover. Dr. Schmidt is the author of several international articles and book chapters. He has lectureships in the areas of company management and lean production. Currently, he is the Head of Research and Industry at the Institute of Production Systems and Logistics of the Leibniz University Hannover. He coordinates research activities in the areas factory planning, logistics, production management, lean production and ergonomics as well as industrial consulting projects in the same areas.

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Section: Part 3 Electrical Engineering and Applicationsmentioning

confidence: 99%

Advances in Computer Science and Engineering

Sarbazi-Azad¹,

Parhami²,

Miremadi³

et al. 2009

Communications in Computer and Information Science

View full text Add to dashboard Cite

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Evolution of legacy system comprehensibility through automated refactoring

Griffith

Wahl

Izurieta

2011

Proceedings of the International Workshop on Machine Learning Technologies in Software Engineering

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Software engineering is a continually evolving discipline, wherein researchers and members of industry are working towards defining and refining what are known as "best practices." Best practices are the set of known correct engineering techniques that lead to quality software.When a software artifact is produced, it becomes temporally locked into a single instantiation of these best practices at a given point in time. If such software is not maintained in such a way as to keep it current with the evolution of practice, then there is a good chance that subsequent engineers may not understand the design choices made. There are known techniques, called refactorings, which allow for structural changes to software without altering the outward appearance and behavior, thus maintaining the intent of the original design. Unfortunately, refactoring requires an engineer to both understand the techniques to be applied and the code to which they are applied to. This is not always feasible.We have developed an automated system utilizing Evolutionary Algorithms to manipulate refactorings correctly without requiring an underlying understanding of the software. This then allows for sustained levels of quality of evolving software systems. The understandability, maintainability, and reusability of the software regenerate as best practices evolve.

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A multi-objective approach for Entity Refactoring Set Selection Problem

Cited by 2 publications

References 3 publications

Advances in Computer Science and Engineering

Advances in Computer Science and Engineering

Evolution of legacy system comprehensibility through automated refactoring

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