Information technology � Software measurement � Software quality measurement � Automated source code quality measures

2021 ◽  
Author(s):  
Dalila Amara ◽  
Latifa Ben Arfa Rabai

Software measurement helps to quantify the quality and the effectiveness of software to find areas of improvement and to provide information needed to make appropriate decisions. In the recent studies, software metrics are widely used for quality assessment. These metrics are divided into two categories: syntactic and semantic. A literature review shows that syntactic ones are widely discussed and are generally used to measure software internal attributes like complexity. It also shows a lack of studies that focus on measuring external attributes like using internal ones. This chapter presents a thorough analysis of most quality measurement concepts. Moreover, it makes a comparative study of object-oriented syntactic metrics to identify their effectiveness for quality assessment and in which phase of the development process these metrics may be used. As reliability is an external attribute, it cannot be measured directly. In this chapter, the authors discuss how reliability can be measured using its correlation with syntactic metrics.


2022 ◽  
Vol 31 (2) ◽  
pp. 1-23
Author(s):  
Jevgenija Pantiuchina ◽  
Bin Lin ◽  
Fiorella Zampetti ◽  
Massimiliano Di Penta ◽  
Michele Lanza ◽  
...  

Refactoring operations are behavior-preserving changes aimed at improving source code quality. While refactoring is largely considered a good practice, refactoring proposals in pull requests are often rejected after the code review. Understanding the reasons behind the rejection of refactoring contributions can shed light on how such contributions can be improved, essentially benefiting software quality. This article reports a study in which we manually coded rejection reasons inferred from 330 refactoring-related pull requests from 207 open-source Java projects. We surveyed 267 developers to assess their perceived prevalence of these identified rejection reasons, further complementing the reasons. Our study resulted in a comprehensive taxonomy consisting of 26 refactoring-related rejection reasons and 21 process-related rejection reasons. The taxonomy, accompanied with representative examples and highlighted implications, provides developers with valuable insights on how to ponder and polish their refactoring contributions, and indicates a number of directions researchers can pursue toward better refactoring recommenders.


Author(s):  
Amanda Damasceno Santana ◽  
Eduardo Figueiredo

When a system evolution is not planned, developers can take decisions that degrade the system quality. To cope with this problem, refactoring can be applied to the source code aiming to increase code quality without modifying the software external behavior. To know when to refactor, the concept of bad smells can be used. Bad smells are snippets of source code that suggest the need of refactoring. However, bad smells does not always appear isolated. The aim of this study is to understand the impact of bad smell agglomerations on the software quality by evaluating a large dataset of open source systems. To achieve our goal, we plan to use data mining techniques complemented with correlation analysis of the dataset.


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