Technical debt reduction using search based automated refactoring

Abstract

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.

A survey of search-based refactoring for software maintenance

“…Mohan, Greer and McMullan (Mohan et al, 2016) adapted the A-CMA tool to investigate different aspects of software quality. They used combinations of metrics to represent three quality factors; abstraction, coupling and inheritance.…”

“…There is the method where problems are first detected in the code and then either refactoring options are generated in order to be applied manually Kessentini et al, 2012;Ouni et al, 2012;Wang et al, 2015;Mkaouer et al, 2016;Griffith et al, 2011) or the problems are addressed automatically (Di Penta, 2005). Koc et al, 2012;Mohan et al, 2016;O'Keeffe & Cinnéide, 2007b;Ghaith & Cinnéide, 2012;Cinnéide et al, 2012;Cinnéide et al, 2016;Veerappa & Harrison, 2013;Fatiregun et al, 2004) or again, using this approach to suggest refactorings to apply (Harman & Tratt, 2007;Seng et al, 2006;. Figure 5 identifies the number of papers that use each type of search technique, with GAs, GP and GEAs again encapsulated as EAs and PSO and ABC encapsulated as SOAs.…”

“…The majority only used one, at 24 papers, although 15 other papers that did use search techniques used more than one. Of these, 12 papers (O' Keeffe & Cinnéide, 2006;O'Keeffe & Cinnéide, 2008a;O'Keeffe & Cinnéide, 2007a;O'Keeffe & Cinnéide, 2008b;Koc et al, 2012;Mohan et al, 2016;Ghaith & Cinnéide, 2012;Mkaouer et al, 2016;Fatiregun et al, 2004) directly compared the different search techniques against each other to speculate on the most applicable. Only one study looked at four separate search techniques.…”

“…A few of the proposed tools were used in multiple papers. The A-CMA tool was proposed by (Koc et al, 2012) and then adapted and used by Mohan, Greer and McMullan (Mohan et al, 2016). The CODe-Imp tool was used in a myriad of studies O'Keeffe and Cinnéide, 2006, O'Keeffe and Cinnéide, 2008a, O'Keeffe and Cinnéide, 2007a, O'Keeffe and Cinnéide, 2008b, O'Keeffe and Cinnéide, 2007b, Ghaith and Cinnéide, 2012, Veerappa and Harrison, 2013.…”

“…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 …”