scholarly journals Comparing Static Analysis and Code Smells as Defect Predictors: An Empirical Study

2021 ◽  
pp. 1-15
Author(s):  
Luigi Lavazza ◽  
Sandro Morasca ◽  
Davide Tosi
Keyword(s):  
Empirical Study ◽  
Static Analysis ◽  
Code Smells

An empirical study on combining diverse static analysis tools for web security vulnerabilities based on development scenarios

Computing ◽  
2018 ◽  
Vol 101 (2) ◽  
pp. 161-185 ◽  
Author(s):  
Paulo Nunes ◽  
Ibéria Medeiros ◽  
José Fonseca ◽  
Nuno Neves ◽  
Miguel Correia ◽  
...  
Keyword(s):  
Empirical Study ◽  
Static Analysis ◽  
Web Security ◽  
Security Vulnerabilities ◽  
Development Scenarios ◽  
Analysis Tools

On the Effectiveness of Concern Metrics to Detect Code Smells: An Empirical Study

2014 ◽  
pp. 656-671 ◽  
Author(s):  
Juliana Padilha ◽  
Juliana Pereira ◽  
Eduardo Figueiredo ◽  
Jussara Almeida ◽  
Alessandro Garcia ◽  
...  
Keyword(s):  
Empirical Study ◽  
Code Smells

scholarly journals Code smells as system-level indicators of maintainability: An empirical study

2013 ◽  
Vol 86 (10) ◽  
pp. 2639-2653 ◽  
Author(s):  
Aiko Yamashita ◽  
Steve Counsell
Keyword(s):  
Empirical Study ◽  
System Level ◽  
Code Smells

scholarly journals Effects of Program Representation on Pointer Analyses — An Empirical Study

2021 ◽  
pp. 240-261
Author(s):  
Jyoti Prakash ◽  
Abhishek Tiwari ◽  
Christian Hammer
Keyword(s):  
Empirical Study ◽  
Static Analysis ◽  
Program Analysis ◽  
Intermediate Representation ◽  
Pointer Analysis ◽  
Class Hierarchy ◽  
Program Representation ◽  
The Impact

AbstractStatic analysis frameworks, such as Soot and Wala, are used by researchers to prototype and compare program analyses. These frameworks vary on heap abstraction, modeling library classes, and underlying intermediate program representation (IR). Often, these variations pose a threat to the validity of the results as the implications of comparing the same analysis implementation in different frameworks are still unexplored. Earlier studies have focused on the precision, soundness, and recall of the algorithms implemented in these frameworks; however, little to no work has been done to evaluate the effects of program representation. In this work, we fill this gap and study the impact of program representation on pointer analysis. Unfortunately, existing metrics are insufficient for such a comparison due to their inability to isolate each aspect of the program representation. Therefore, we define two novel metrics that measure these analyses’ precision after isolating the influence of class-hierarchy and intermediate representation. Our results establish that the minor differences in the class hierarchy and IR do not impact program analysis significantly. Besides, they reveal the sources of unsoundness that aid researchers in developing program analysis.

A large-scale empirical study of code smells in JavaScript projects

2019 ◽  
Vol 27 (3) ◽  
pp. 1271-1314 ◽  
Author(s):  
David Johannes ◽  
Foutse Khomh ◽  
Giuliano Antoniol
Keyword(s):  
Empirical Study ◽  
Large Scale ◽  
Code Smells
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