Size and cohesion metrics as indicators of the long method bad smell: An empirical study

Abstract

Source code bad smells are usually resolved through the application of well-defined solutions, i.e., refactorings. In the literature, software metrics are used as indicators of the existence and prioritization of resolving bad smells. In this paper, we focus on the long method smell (i.e. one of the most frequent and persistent bad smells) that can be resolved by the extract method refactoring. Until now, the identification of long methods or extract method opportunities has been performed based on cohesion, size or complexity metrics. However, the empirical validation of these metrics has exhibited relatively low accuracy with regard to their capacity to indicate the existence of long methods or extract method opportunities. Thus, we empirically explore the ability of size and cohesion metrics to predict the existence and the refactoring urgency of long method occurrences, through a case study on java open-source methods. The results of the study suggest that one size and four cohesion metrics are capable of characterizing the need and urgency for resolving the long method bad smell, with a higher accuracy compared to the previous studies. The obtained results are discussed by providing possible interpretations and implications to practitioners and researchers.