Towards Assessing Software Architecture Quality by Exploiting Code Smell Relations

Abstract

We can evaluate software architecture quality using a plethora of metrics proposed in the literature, but interpreting and exploiting in the right way these metrics is not always a simple task. This is true for both fixing the right metric threshold values and determining the actions to be taken to improve the quality of the system. Instead of metrics, we can detect code or architectural anomalies that give us useful hints on the possible architecture degradation. In this paper, we focus our attention on the detection of code smells and in particular on their relations and co-occurrences, with the aim to evaluate tecnical debt in an architectural context. We start from the assumption that certain patterns of code anomalies tend to be better indicators of architectural degradation than simple metrics evaluation.

The Relationship between Traceable Code Patterns and Code Smells

“…In order to avoid these problems, researchers examined ways to detect code smells more accurately by correlating smells with other constructs (including other code smells). Fontana [4] extracted relationships among code smells such as determining whether a code smell contains another code smell or if a smelly method calls another smelly method. The authors exploited these relations to tease out architectural anomalies in a system.…”

“…Step 1: Extract code smells: Next, we used Intooitus inCode 4 to extract the code smells from the source code. inCode follows Marinescu's detection strategies to quantify design problems [11] [13].…”

“…Code smells can also be transitively related to each other [6]. Fontana et al [4] also identified other relations among code smells useful for detecting architectural degradation.…”

On experimenting refactoring tools to remove code smells

“…It would be interesting also to offer not only a preview of the code and refactoring suggestions, but also some views showing possible correlations or co-occurrences among smells, that can be particularly useful during the refactoring process, also to locate the most critical portions of code, as we already started to investigate [2].…”

Semantic-based Architecture Smell Analysis

“…The detection of architecture smells needs to be rigorous and thorough, so it requires intensive human involvement. Even though there are works such as [5] proposed to detect architecture smells, they focus on detecting architecture smells from the source code. However, architecture smells can be rarely identified from the source code.…”