A Study on Architectural Smells Prediction

Architectural smells can be detrimental to the system maintainability, evolvability and represent a source of architectural debt. Thus, it is very important to be able to understand how they evolved in the past and to predict their future evolution. In this paper, we evaluate if the existence of architectural smells in the past versions of a project can be used to predict their presence in the future. We analyzed four Java projects in 295 Github releases and we applied for the prediction four different supervised learning models in a repeated cross-validation setting. We found that historical architectural smell information can be used to predict the presence of architectural smells in the future. Hence, practitioners should carefully monitor the evolution of architectural smells and take preventative actions to avoid introducing them and stave off their progressive growth.</p

Understanding the Correlation between Code Smells And Software Bugs

https://deepblue.lib.umich.edu/bitstream/2027.42/147342/1/CodeSmellsBugs.pd

An Empirical Study of the Correlation between Code Smells And Software Bugs

Bug predictions helps software quality assurance team to determine the effort required to test the software application. Anti-patterns and code smells can greatly influence the quality of the code. Refactoring can be a solution to remove the negative impact of these anti-patterns. In this paper, we explored the influence of code smells on the code and severity of bugs reported on multiple versions of the projects such as BIRT, Aspect J and SWT. We evaluated the correlation between the different code smells and severity of the bugs reported on these classes. This can help the quality assurance specialists and project managers assess the testing effort required based on the code smells detected. This can prove beneficial to the developers to restructure or refactor before deploying the code in the test environment. On the other hand, the testing team can concentrate on the bug prediction models, testing plan and assess the number of resources needed to perform testing. The empirical validation of our work found a strong correlation between several types of code smells and software bugs based on three large open source projects.Master of ScienceSoftware Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttps://deepblue.lib.umich.edu/bitstream/2027.42/147432/1/Dec 19- Thesis Report_GANESAN GAYATHRI_4pm_FontsEmbedded.pdfDescription of Dec 19- Thesis Report_GANESAN GAYATHRI_4pm_FontsEmbedded.pdf : Thesi

Do code review practices impact design quality? a case study of the qt, vtk, and itk projects

Abstract-Code review is the process of having other team members examine changes to a software system in order to evaluate its technical content and quality. A lightweight variant of this practice, often referred to as Modern Code Review (MCR), is widely adopted by software organizations today. Previous studies have established a relation between the practice of code review and the occurrence of post-release bugs. While the prior work studies the impact of code review practices on software release quality, it is still unclear what impact code review practices have on software design quality. Therefore, using the occurrence of 7 different types of anti-patterns (i.e., poor solutions to design and implementation problems) as a proxy for software design quality, we set out to investigate the relationship between code review practices and software design quality. Through a case study of the Qt, VTK and ITK open source projects, we find that software components with low review coverage or low review participation are often more prone to the occurrence of anti-patterns than those components with more active code review practices

EARMO: An Energy-Aware Refactoring Approach for Mobile Apps

The energy consumption of mobile apps is a trending topic and researchers are actively investigating the role of coding practices on energy consumption. Recent studies suggest that design choices can conflict with energy consumption. Therefore, it is important to take into account energy consumption when evolving the design of a mobile app. In this paper, we analyze the impact of eight type of anti-patterns on a testbed of 20 android apps extracted from F-Droid. We propose EARMO, a novel anti-pattern correction approach that accounts for energy consumption when refactoring mobile anti-patterns. We evaluate EARMO using three multiobjective search-based algorithms. The obtained results show that EARMO can generate refactoring recommendations in less than a minute, and remove a median of 84% of anti-patterns. Moreover, EARMO extended the battery life of a mobile phone by up to 29 minutes when running in isolation a refactored multimedia app with default settings (no WiFi, no location services, and minimum screen brightness). Finally, we conducted a qualitative study with developers of our studied apps, to assess the refactoring recommendations made by EARMO. Developers found 68% of refactorings suggested by EARMO to be very relevant.This work has been supported by the Natural Sciences and Engineering Research Council of Canada (NSERC) and Consejo Nacional de Ciencia y Tecnología, México (CONACyT)