Applying evolution programming Search Based Software Engineering (SBSE) in selecting the best open source software maintainability metrics

2019 IEEE/ACM 3rd International Workshop on Refactoring (IWoR)

McMullan

2019

This paper describes a multi-objective genetic algorithm used to automate software refactoring. The approach is validated using a set of open source Java programs with a purpose built tool, MultiRefactor. The tool uses a metric function to measure quality in a software system and tests a second objective to measure the amount of code coverage of the applied refactorings by analyzing the code elements they have been applied to. The multi-objective setup will refactor the input program to improve its quality using the quality objective, while also maximizing the code coverage of the refactorings applied to the software. An experiment has been constructed to measure the multi-objective approach against the alternative monoobjective approach that does not use an objective to measure refactoring coverage. The two approaches are tested on six different open source Java programs. The multi-objective approach is found to give significantly better refactoring coverage scores across all inputs in a similar time, while also generating improvements in the quality scores.

Section: Related Workmentioning

confidence: 99%

Maximizing Refactoring Coverage in an Automated Maintenance Approach Using Multi-Objective Optimization

2019 IEEE/ACM 3rd International Workshop on Refactoring (IWoR)

McMullan

2019

“…Furthermore, the parallel program ran substantially faster than the sequential version. Bakar et al (2012a) attempted to outline a set of guidelines to select the best metrics for measuring maintainability in open source software. An EA was used to optimize and rank the set of metrics, which were listed in previous work (Bakar et al, 2012b).…”

Section: Testing Metric Effectiveness With Refactoringmentioning

confidence: 99%

“…Harman and Tratt (2007) tested the Pareto optimal approach to combine software metrics in a search. Vivanco and Pizzi (2004) used a GA to test metrics and choose the most suitable ones to use (Bakar et al (2012a) also proposed a method to do this).…”

Section: Types Of Studymentioning

confidence: 99%

“…Of the papers, there have been a number that have investigated O'Keeffe and Cinnéide, 2006, Mohan et al, 2016, O'Keeffe and Cinnéide, 2007b, Ghaith and Cinnéide, 2012, Veerappa and Harrison, 2013, Vivanco and Pizzi, 2004, Bakar et al, 2012aor discussed Simons et al, 2015 the metrics used in search-based approaches. Many of the programs analyzed in the experiments and case studies conducted have been using Java (or one using C++ Table 7 Open Source Test Programs Used in the Literature (and the Papers They are Used in) GanttProject Cinnéide et al, 2012;Cinnéide et al, 2016;Veerappa & Harrison, 2013;Kessentini et al, 2012;Ouni et al, 2012;Mkaouer et al, 2016;Amal et al, 2014) JHotDraw (Harman & Tratt, 2007;Mohan et al, 2016;Seng et al, 2006;Cinnéide et al, 2012;Cinnéide et al, 2016;Veerappa & Harrison, 2013;Kessentini et al, 2012;Mkaouer et al, 2016;Amal et al, 2014) Xerces-J Kessentini et al, 2012;Ouni et al, 2012;Mkaouer et al, 2016;Amal et al, 2014) JFreeChart (Veerappa & Harrison, 2013;Wang et al, 2015;Mkaouer et al, 2016;Amal et al, 2014) ArgoUML Beaver ( (Harman & Tratt, 2007;Cinnéide et al, 2012;Cinnéide et al, 2016;Veerappa & Harrison, 2013) Azureus JGraphX …”

Section: Metricsmentioning

confidence: 99%

See 1 more Smart Citation

A survey of search-based refactoring for software maintenance

2018

J Softw Eng Res Dev

This survey reviews published materials related to the specific area of Search-Based Software Engineering that concerns software maintenance and, in particular, refactoring. The survey aims to give a comprehensive review of the use of search-based refactoring to maintain software. Fifty different papers have been selected from online databases to analyze and review the use of search-based refactoring in software engineering. The current state of the research is analyzed and patterns in the studies are investigated in order to assess gaps in the area and suggest opportunities for future research. The papers reviewed are tabulated in order to aid researchers in quickly referencing studies. The literature addresses different methods using search-based refactoring for software maintenance, as well as studies that investigate the optimization process and discuss components of the search. There are studies that analyze different software metrics, experiment with multiobjective techniques and propose refactoring tools for use. Analysis of the literature has indicated some opportunities for future research in the area. More experimentation of the techniques in an industrial environment and feedback from software developers is needed to support the approaches. Also, recent work with multi-objective techniques has shown that there are exciting possibilities for future research using these techniques with refactoring. This survey is beneficial as an introduction for any researchers aiming to work in the area of Search-Based Software Engineering with respect to software maintenance and will allow them to gain an understanding of the current landscape of the research and the insights gathered.

“…Among the top encoded genes are method name length metrics, coupling metrics and complexity metrics. Bakar et al (2012) has attempted to develop a metric model for selecting the most suitable metrics to measure maintainability. They analyse the CK metrics suite (Chidamber and Kemerer, 1994).…”

Section: Metricsmentioning

confidence: 99%

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.