The Relationship between Traceable Code Patterns and Code Smells

Abstract

Context: It is important to maintain software quality as a software system evolves. Managing code smells in source code contributes towards quality software. While metrics have been used to pinpoint code smells in source code, we present an empirical study on the correlation of code smells with class-level (micro pattern) and methodlevel (nano-pattern) traceable patterns of code. Objective: This study explores the relationship between code smells and class-level and method-level structural code constructs. Method: We extracted micro patterns at the class level and nano-patterns at the method level from three versions of Apache Tomcat and PersonalBlog and Roller from Standford SecuriBench and compared their distributions in code smell versus non-code smell classes and methods.Result: We found that DataM anager, Record and Outline micro patterns are more frequent in classes having code smell compared to non-code smell classes in the applications we analyzed. localReader, localW riter, Switcher, and ArrReader nano-patterns are more frequent in code smell methods compared to the non-code smell methods. Conclusion: We conclude that code smells are correlated with both micro and nano-patterns.

Examining the Relationship of Code and Architectural Smells with Software Vulnerabilities

“…We used the Android Open Source Platform (AOSP) repository in our analysis because Google (the company that maintains AOSP) publishes a list of recently-patched software vulnerabilities in AOSP each month. 9 AOSP also contains a substantial amount of Java code, especially in layers related to the user interface. We chose the base Android platform repository (/platform/frameworks/base/) because it is a large, primarily Java codebase with a high number of security patches and it is central to AOSP.…”

“…4 Many studies have identified code smells as indicators of fault-proneness that directly relate to the system's quality [4]- [6]. Code smells are also related to weak system design, bad implementation methods, micro and nano-patterns which may lead to poor quality [7]- [9]. So, the identification and management of smells is an important part of software quality assurance to build quality software.…”

A Longitudinal Study of Anti Micro Patterns in 113 versions of Tomcat

“…Singer et al [22] presented a catalog of 17 nano-patterns which are categorized into 4 groups. Codabux et al [6], extracted micro patterns and nano-patterns from three versions of Tomcat and other two systems and compared their distributions in code smell versus non-code smell classes and methods, concluding that code smells are correlated with both micro and nano-patterns. Micro patterns have been proven useful also for detecting software vulnerabilities [23,24].…”

Using Naming Patterns for Identifying Architectural Technical Debt

“…Frequently the technical debt, when is inserted, is less visible for decision makers in the software development [5]. The development of techniques for identifying and monitoring incidences of technical debt, is important for making explicit the debt and it could be resolved in due time [3,11,22,24,35,37].…”

“…The technical debt can be inserted by not complying the architectural design, or by not using conventions or standards of programming [35]. Including this as a decision factor inside the software development, requires information about the incidences of technical debt in the software system, where these are located, and their magnitude; such information can be gotten through source code analysis [5].…”