Works (6)

Updated: April 5th, 2024 08:04

2017 journal article

Identifying the implied: Findings from three differentiated replications on the use of security requirements templates

EMPIRICAL SOFTWARE ENGINEERING, 22(4), 2127–2178.

By: M. Riaz n, J. King n, J. Slankas n, L. Williams n, F. Massacci*, C. Quesada-Lopez*, M. Jenkins*

author keywords: Security requirements; Controlled experiment; Replication; Requirements engineering; Templates; Patterns; Automation
TL;DR: Qualitative findings indicate that participants may be able to differentiate between relevant and extraneous templates suggestions and be more inclined to fill in the templates with additional support, supporting the findings of the original study. (via Semantic Scholar)
Sources: Web Of Science, NC State University Libraries, ORCID
Added: August 6, 2018

2015 article

FUSE: A Reproducible, Extendable, Internet-scale Corpus of Spreadsheets

12TH WORKING CONFERENCE ON MINING SOFTWARE REPOSITORIES (MSR 2015), pp. 486–489.

By: T. Barik n, K. Lubick n, J. Smith n, J. Slankas n & E. Murphy-Hill n

TL;DR: A corpus, called Fuse, containing 2,127,284 URLs that return spreadsheets (and their HTTP server responses), and 249,376 unique spreadsheets, contained within a public web archive of over 26.83 billion pages is described. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (Web of Science)
Source: Web Of Science
Added: August 6, 2018

2014 conference paper

Hidden in plain sight: Automatically identifying security requirements from natural language artifacts

2014 ieee 22nd international requirements engineering conference (re), 183–192.

By: M. Riaz n, J. King n, J. Slankas n & L. Williams n

TL;DR: A tool-assisted process that automatically identifies security-relevant sentences in natural language requirements artifacts and classifies them according to the security objectives, either explicitly stated or implied by the sentences. (via Semantic Scholar)
Sources: NC State University Libraries, NC State University Libraries, ORCID
Added: August 6, 2018

2013 article

Access Control Policy Extraction from Unconstrained Natural Language Text

2013 ASE/IEEE INTERNATIONAL CONFERENCE ON SOCIAL COMPUTING (SOCIALCOM), pp. 435–440.

By: J. Slankas n & L. Williams n

author keywords: access control; documentation; machine learning; natural language processing; relation extraction; security
TL;DR: This research proposes a machine-learning based process to parse existing, unaltered natural language documents, such as requirement or technical specifications to extract the relevant subjects, actions, and resources for an access control policy. (via Semantic Scholar)
UN Sustainable Development Goal Categories
4. Quality Education (OpenAlex)
Source: Web Of Science
Added: August 6, 2018

2013 conference paper

Automated extraction of non-functional requirements in available documentation

2013 1st International Workshop on Natural Language Analysis in Software Engineering (NaturaLiSE), 9–16.

By: J. Slankas n & L. Williams n

TL;DR: To aid analysts in more effectively extracting relevant non-functional requirements in available unconstrained natural language documents through automated natural language processing, this research examines which document types contain NFRs categorized to 14 NFR categories. (via Semantic Scholar)
Source: NC State University Libraries
Added: August 6, 2018

2013 conference paper

Implementing database access control policy from unconstrained natural language text

Proceedings of the 35th International Conference on software engineering (ICSE 2013), 1357–1360.

By: J. Slankas n

TL;DR: The goal of this research is to improve security and compliance by ensuring access controls rules explicitly and implicitly defined within unconstrained natural language texts are appropriately enforced within a system's relational database. (via Semantic Scholar)
Source: NC State University Libraries
Added: August 6, 2018

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