An Empirical Study About Search-Based Refactoring Using Alternative Multiple and Population-Based Search Techniques

Product-Focused Software Process Improvement

2017

Abstract. In this paper, a new approach is proposed for automated software maintenance. The tool is able to perform 26 different refactorings. It also contains a large selection of metrics to measure the impact of the refactorings on the software and six different search based optimization algorithms to improve the software. This tool contains both mono-objective and multi-objective search techniques for software improvement and is fully automated. The paper describes the various capabilities of the tool, the unique aspects of it, and also presents some research results from experimentation. The individual metrics are tested across five different codebases to deduce the most effective metrics for general quality improvement. It is found that the metrics that relate to more specific elements of the code are more useful for driving change in the search. The mono-objective genetic algorithm is also tested against the multi-objective algorithm to see how comparable the results gained are with three separate objectives. When comparing the best solutions of each individual objective the multi-objective approach generates suitable improvements in quality in less time, allowing for rapid maintenance cycles.

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Section: Multirefactormentioning

confidence: 99%

MultiRefactor: Automated Refactoring to Improve Software Quality

Product-Focused Software Process Improvement

2017

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“…A-CMA is an automated refactoring tool developed by Koc et al (2012) that refactors Java programs using Java bytecode as input. An advantage of this tool over many others is that it has many options for refactoring as well as metrics available and it is highly configurable.…”

Section: Refactoring Toolmentioning

confidence: 99%

“…The random search was used as a benchmark with 5,000 iterations. Steepest ascent hill climbing was chosen for the experiment with 30 restarts at a depth of 5 neighbours (chosen based on published comparisons between different hill climbing parameters (Koc et al, 2012)). The third search used was low temperature simulated annealing (as low temperatures have been found to be more effective by O'Keeffe and Ó Cinnéide (2008)) with 5,000 iterations and with the starting temperature set to 1.5.…”

Section: =0mentioning

confidence: 99%

“…The tool used in this paper, A-CMA (Koc et al, 2012), uses metaheuristic search techniques to measure the code quality and to search for a better solution. It has the advantage of numerous metrics and refactoring abilities to aid with its purpose.…”

Section: Refactoring Toolsmentioning

confidence: 99%

“…As previous work in the area has investigated abstraction (O'Keeffe and Ó Cinnéide, 2003), (Mitchell and Mancoridis, 2002), coupling (Veerappa and Harrison, 2013), (Murgia et al, 2012) and inheritance (O'Keeffe and Ó Cinnéide, 2007), there is some support for the position that these are useful properties to use for a comparative study against an approach for tackling TD. To further the investigation, an experiment has been conducted using the refactoring tool A-CMA (Koc et al, 2012) to assess the effectiveness of three sets of metrics that measure these object oriented properties and compare them against a proposed set of metrics to measure TD. A weighted sum is used to combine the metrics into an overall score to improve.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Technical debt reduction using search based automated refactoring

Journal of Systems and Software

McMullan

2016

Software refactoring has been recognised as a valuable process during software development and is often aimed at repaying technical debt. Technical debt arises when a software product has been built or amended without full care for structure and extensibility. Refactoring is useful to keep technical debt low and if it can be automated there are obvious efficiency benefits. Using a combination of automated refactoring techniques, software metrics and metaheuristic searches, an automated refactoring tool can improve the structure of a software system without affecting its functionality. In this paper, four different refactoring approaches are compared using an automated software refactoring tool. Weighted sums of metrics are used to form different fitness functions that drive the search process towards certain aspects of software quality. Metrics are combined to measure coupling, abstraction and inheritance and a fourth fitness function is proposed to measure reduction in technical debt. The 4 functions are compared against each other using 3 different searches on 6 different open source programs. Four out of the 6 programs show a larger improvement in the technical debt function after the search based refactoring process. The results show that the technical debt function is useful for assessing improvement in quality.

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Automated Multi-objective Refactoring Based on Quality and Code Element Recentness

Communications in Computer and Information Science

2019