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Following using and estimating set of refactoring, the risks of impacting the consistency between the source codes as well as the other software artifacts involving the documentation, design models, and test suite is high.
Therefore, it has been suggested for counting the approaches for maintaining the consistency [8]. In addition, the difficulties to merge and integrate following refactoring sometimes encourage the individuals from doing refactoring [14].
The version control systems which they utilize have been sensitive to move and rename refactoring, also making it difficult for developers to understand the code change history following refactoring. It also increases the odds in which the changes are going to collide with the changes of someone else. Therefore, this prevents developers from initiating refactoring efforts [16].
In the case when there are no tests, then one must go from the known scenarios and ensuring all works. Furthermore, in the case when there are no sufficient documentations for the scenarios, refactoring must be achieved. The inherent in addition to technical challenges regarding refactoring indicated via participants, maintain backward compatibility sometimes discouraging them from starting refactoring efforts [13].
Refactoring Decision The developers perform refactoring based on the signs of code, helping to make a decision on the refactoring Fig. Base on the self-reported data, the developers spend approximately 13h. The symptoms of code that help developers initiate refactoring 5. How It is possible to measure a bug value which has never existed, or time which is saved on a later unspecified feature?
How can such value bubble up to the management? Due to the fact that there are no ways for placing the exact value on refactoring practice, it is hard to justify to the management [16]. Literature Review of Refactoring The life-cycle of software is highly dependent on maintenance.
Throughout the maintenance, the code might be altered many times, that might be deteriorating the quality of the code. In the present survey, the objective is the aggregation of the patterns and the information on the researches which are carried out on the refactoring for the maintenance of software and trends which are not discovered earlier.
Furthermore, Applying refactoring of code is definitely a reasonable and efficient activity in facilitating maintenance, and it increases the value of quality attributes for the software, if refactoring activates are used properly at a suitable time [19]. The results also recommend to applying the refactoring activities after a regular change of maintenance activities and the advantages of removing coupling between classes on decreasing the refactoring effort precisely with refactoring of package and giving warning data for potential of refactoring [20].
In , Singh and Kahlon introduce a measure to classify faulty classes which are cohesion, hiding of information and encapsulation.
Then, the researchers propose a statistical method to examine the correlation between these measures and source code smells. Firefox is considered as a case study to prove the approach and the results display high precision in classifying the classes that are faulty and applying refactoring activates on the faulty classes.
These results of refactoring will assist the developer in testing and maintenance phases of software life cycle [21]. So in the same year, Dig introduces a new method to applying refactoring techniques for analyzing and transforming current processes. The method suggests to alter multiple lines of source code and eliminate error-prone because programmers require ensuring parallel processes to increase software performance, maintainability and portability. The research also presents a set of tools which supports many activities of refactoring techniques including increasing scalability and maintainability of parallel processes, making processes thread-harmless and increasing throughput of sequential processes [22].
Sometimes the programmer needs to apply the refactoring multiple times to the source code. So in , Meananeatra proposes a method to recognize a best sequence of refactoring that meets many measures which are maintainability factor, the total number of faults eliminated, the dimension sequence of refactoring, and the total number of changed program components.
Furthermore, the authors estimates that the results tend to decrease cost and time of maintainability, and improve the quality of software. The author adopts Columba project as a case study and the result displays that the occurrence of defect is reduced after many circles of refactoring and increases the factor of maintainability through three variables : frequent of refactoring, frequent of fix and defect density [25]. Case studies are taken to examine the effort model and scheduler of clone code refactoring, results compared with other scheduling approaches and CP-depended model shown outperforms other models [26].
In , Chaparro et al introduce a technique called Refactoring Impact Prediction RIP to study the effect of refactoring processes on the quality metrics of source code. In the same year, Steidl and Eder propose to eliminate maintainability defects, reuse of optimal code and long functions, that require less effort to refactor. The research provides the developers a point to enhance the quality of the software. With a case study for java software, the research calculates and assesses the advantage of recommendation depending on feedback from developers and specifies effect of external factors on the process of maintainability defect elimination in software development [28].
In each circle of the process of refactoring, many operations can be applied to increase maintainability value through sets of MISs. The proposed model is implemented on many of case studies and the results display that the model can increase maintainability factor. Furthermore, the developer can apply many circles of refactoring at the same time [29].
In the same year, Kannangara and Wijayanayake study the effect of refactoring approaches based on multiple measures to increase the quality of software. Ten approaches have been selected and assessed quality through five external factors and five internal factors including index of maintainability. In , Mohan and et al, compare 4 distinct methods of refactoring with the use of automated tool of software refactoring.
The weighted summation values of the metrics have been utilized for forming a variety of the fitness functions driving the process of the search in the direction of specific software quality aspects. The measures are integrated for measuring the abstraction, inheritance, and coupling and a 4th function of fitness has been suggested for measuring the technical debt reduction. Those four functions have been compared to one another with the use of three distinct searches on six distinct programs of open source; four out of the six of the programs have shown a higher enhancement in the function of the technical debt following the process of the search based refactoring.
The results have shown that this function has been beneficial to assess quality enhancement [30]. In the same year, Malhotra and Chug examine the refactoring impacts on the maintainability with the use of 5 proprietary software systems.
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