arrow
返回

How Does Refactoring Impact Security When Improving Quality? A Security-Aware Refactoring Approach

delete2020-01-01
delete5
PRE
AI
C
Chaima Abid
M
Marouane Kessentini *
V
Vahid Alizadeh
M
Mouna Dhouadi
R
Rick Kazman
DOI:10.1109/TSE.2020.3005995delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
While state of the art of software refactoring research uses various quality attributes to identify refactoring opportunities and evaluate refactoring recommendations, the impact of refactoring on the security of software systems when improving other quality objectives is under-explored. It is critical to understand how a system is resistant to security risks after refactoring to improve quality metrics. For instance, refactoring is widely used to improve the reusability of code, however such an improvement may increase the attack surface due to the created abstractions. Increasing the spread of security-critical classes in the design to improve modularity may result in reducing the resilience of software systems to attacks. In this paper, we investigated the possible impact of improving different quality attributes (e.g., reusability, extendibility, etc.), from the QMOOD model, effectiveness on a set of 8 security metrics defined in the literature related to the data access. We also studied the impact of different refactorings on these static security metrics. Then, we proposed a multi-objective refactoring recommendation approach to find a balance between quality attributes and security based on the correlation results to guide the search. We evaluated our tool on 30 open source projects. We also collected the practitioner perceptions on the refactorings recommended by our tool in terms of the possible impact on both security and other quality attributes. Our results confirm that developers need to make trade-offs between security and other qualities when refactoring software systems due to the negative correlations between them.
Keyword:
Security
Measurement
Tools
Correlation
Software systems
Computer bugs
Quality
critical code
security metrics
attack surface
refactoring
multi-objective search
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

IEEE Transactions on Software Engineering 封面图
IEEE Transactions on Software Engineering
IF:
5.6
论文数:
2.9K
被引数:
1.1W

机构

U
University of Michigan
学者数:
6.4W
论文数: 5.3W
被引数: 124
U
university of michigan system
学者数:
9.1W
论文数: 8.6W
被引数: 133
引用论文

引用论文

Higgs search by neural networks at LHC
err1994-02-01
err0
errOAAI
errP. Chiappetta; P. Colangelo; P. De Felice; G. Nardulli; G. Pasquariello
err分享
err收藏
On the nature of bladder sensation: The concept of sensory modulation
err2011-06-09
err0
PREAI
errS.G. De Wachter; R. Heeringa; G.A. van Koeveringe; J.I. Gillespie
err分享
err收藏
err分享
err收藏
Sensing aromatic pollutants in water with catalyst-sensitized water-gated transistor
err2020-06-05
err0
errOAAI
errNawal Alghamdi; Zahrah Alqahtani; Changyan Zhou; Naoko Sano; Marco Conte; Martin Grell
err分享
err收藏
err分享
err收藏
Why do we flush gas in gaseous detectors?
err2020-03-01
err0
errOAAI
errS. Procureur; D. Attié; S. Bouteille; D. Calvet; X. Coppolani; B. Gallois; H. Gomez; M. Kebbiri; E. Le Courric; P. Magnier; I. Mandjavidze; N. Sellami; R. Veenhof
err分享
err收藏
学者 查看更多内容