Applying Metrics to Identify and Monitor Technical Debt Items during Software Evolution

Siebra, Clauirton; Cavalcanti, Antonio; Silva, Fabio Q. B.; Santos, André L. M.; Gouveia, Tatiana B.

doi:10.1109/issrew.2014.59

Cited by 5 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…TD has been established to be closely related to the maintainability quality attribute in [70], [71], [72], [73], especially in distributed software applications. These applications are one of the most important applications currently deployed.…”

Section: The Need For Software Securitymentioning

confidence: 99%

Security risks in the software development lifecycle: A review

Odera¹,

Otieno²,

Ounza³

2023

World J. Adv. Eng. Technol. Sci.

View full text Add to dashboard Cite

Software security is one of the most critical concerns in modern software development, especially in safety-critical systems whose failure can lead to environmental damage, substantial property, or loss of human lives. In addition, flawed applications have been shown to exhibit unpredictable behavior while software products with numerous vulnerabilities present attack vectors that can be exploited by attackers. To address some of these problems, vulnerability prediction has been deployed for early detection of security risks in the software development lifecycle (SDLC). This can potentially facilitate decision making during the SDLC, resulting in the production of more secure software. Prioritizing security during SDLC permits developers and stakeholders to identify and resolve possible security concerns early on in the process. The aim of this paper is therefore to offer some in-depth review of software systems security issues. In addition, the various measures that have been put in place to mitigate security issues during SDLC are discussed.

show abstract

Section: The Need For Software Securitymentioning

confidence: 99%

Security risks in the software development lifecycle: A review

Odera¹,

Otieno²,

Ounza³

2023

World J. Adv. Eng. Technol. Sci.

View full text Add to dashboard Cite

show abstract

“…In a similar manner, coupling metrics, such as the Coupling Between Objects (CBO) or the Coupling Between Methods (CBM), and cohesion metrics, such as the Lack of Cohesion in Methods (LCOM), have been considered by a multitude of researchers for their ability to measure and predict (Eski and Buzluca 2011;Shatnawi and Wei 2008;Zhou et al 2012;Zhou and Leung 2007;Van Koten and Gray 2006;Shatnawi and Wei 2008;Elish and Elish 2009). Therefore, since TD is closely related to the maintainability quality attribute, the aforementioned software metrics are usually being treated as indirect TD indicators or a subset of TD indicators (Kosti et al 2017;Tsoukalas et al 2020;Alves et al 2016;Siebra et al 2014).…”

Section: Selected Indicators 3121 Technical Debtmentioning

confidence: 99%

Technical debt as an indicator of software security risk: a machine learning approach for software development enterprises

Siavvas

Tsoukalas

Janković

et al. 2020

Enterprise Information Systems

View full text Add to dashboard Cite

Vulnerability prediction facilitates the development of secure software, as it enables the identification and mitigation of security risks early enough in the software development lifecycle. Although several factors have been studied for their ability to indicate software security risk, very limited attention has been given to technical debt (TD), despite its potential relevance to software security. To this end, in the present study, we investigate the ability of common TD indicators to indicate security risks in software products, both at project-level and at class-level of granularity. Our findings suggest that TD indicators may potentially act as security indicators as well.

show abstract

Towards an open-source tool for measuring and visualizing the interest of technical debt

Falessi

Reichel

2015

2015 IEEE 7th International Workshop on Managing Technical Debt (MTD)

View full text Add to dashboard Cite

Applying Metrics to Identify and Monitor Technical Debt Items during Software Evolution

Cited by 5 publications

References 7 publications

Security risks in the software development lifecycle: A review

Security risks in the software development lifecycle: A review

Technical debt as an indicator of software security risk: a machine learning approach for software development enterprises

Towards an open-source tool for measuring and visualizing the interest of technical debt

Contact Info

Product

Resources

About