Abstract
Different challenges arise while detecting deficient software source code. Usually a large number of potentially problematic entities are identified when an individual software metric or individual quality aspect is used for the identification of deficient program entities. Additionally, a lot of these entities quite often turn out to be false positives, i.e., the metrics indicate poor quality whereas experienced developers do not consider program entities as problematic. The number of entities identified as potentially deficient does not decrease significantly when the identification of deficient entities is carried out by applying code smell detection rules. Moreover, the intersection of entities identified as allegedly deficient among different code smell detection tools is small, which suggests that the implementation of code smell detection rules are not consistent and uniform. To address these challenges, we present a novel approach for identifying deficient entities that is based on applying the majority function on the combination of software metrics. Program entities are assessed according to selected quality aspects that are evaluated with a set of software metrics and corresponding threshold values derived from benchmark data, considering the statistical distributions of software metrics values. The proposed approach was implemented and validated on projects developed in Java, C++ and C#. The validation of the proposed approach was done with expert judgment, where software developers and architects with multiple years of experiences assessed the quality of the software classes. Using a combination of software metrics as the criteria for the identification of deficient source code, the number of potentially deficient object-oriented program entities proved to be reduced. The results show the correctness of quality ratings determined by the proposed identification approach, and most importantly, confirm the absence of false positive entities.
Highlights
Delivering a high-quality product should be the main goal of every software project
When we evaluate software according to an individual software metric, as presented with
This paper presents a novel approach to the identification of deficient source code using a combination of software metrics and applying the majority function
Summary
Delivering a high-quality product should be the main goal of every software project. The quality of software depends on activities within the software development process [1], part of which is the quality assessment phase, including source code analysis. The presented research study was guided by the following research question: Does the identification approach based on the majority function applied on the combination of software metrics identify a deficient source code in a reliable way? Expert judgment was used in order to validate the proposed approach For this purpose, software developers and software architects with multiple years of experience assessed selected program entities within a performed study. Software developers and software architects with multiple years of experience assessed selected program entities within a performed study Their evaluation was compared to the results, obtained by the proposed novel approach for the identification of deficient source code based on a combination of software metrics using a majority function.
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