Ensuring the Correctness of Regular Expressions: A Review

Zheng, Lixiao; Ma, Shuai; Chen, Zu-Xi; Luo, Xiangyu

doi:10.1007/s11633-021-1301-4

Cited by 8 publications

(4 citation statements)

References 71 publications

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“…Nonetheless, regular expressions have certain drawbacks. As a result, strategies for validating regular expressions [30] or testing their use in applications [31] are being sought to expose potential flaws in regular expressions.…”

Section: Resultsmentioning

confidence: 99%

A web content mining application for detecting relevant pages using Jaccard similarity

Jalal

Jasim

Mahawish

2022

IJECE

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<span lang="EN-US">The tremendous growth in the availability of enormous text data from a variety of sources creates a slew of concerns and obstacles to discovering meaningful information. This advancement of technology in the digital realm has resulted in the dispersion of texts over millions of web sites. Unstructured texts are densely packed with textual information. The discovery of valuable and intriguing relationships in unstructured texts demands more computer processing. So, text mining has developed into an attractive area of study for obtaining organized and useful data. One of the purposes of this research is to discuss text pre-processing of automobile marketing domains in order to create a structured database. Regular expressions were used to extract data from unstructured vehicle advertisements, resulting in a well-organized database. We manually develop unique rule-based ways of extracting structured data from unstructured web pages. As a result of the information retrieved from these advertisements, a systematic search for certain noteworthy qualities is performed. There are numerous approaches for query recommendation, and it is vital to understand which one should be employed. Additionally, this research attempts to determine the optimal value similarity for query suggestions based on user-supplied parameters by comparing MySQL pattern matching and Jaccard similarity.</span>

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Section: Resultsmentioning

confidence: 99%

A web content mining application for detecting relevant pages using Jaccard similarity

Jalal

Jasim

Mahawish

2022

IJECE

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“…RegEx are essential for text processing and pattern matching, providing a flexible way to search, match, and manipulate strings based on specified patterns [17]- [25]. In natural language processing, RegEx is used for tasks like text cleaning, tokenization, and information extraction.…”

Section: Regexmentioning

confidence: 99%

Enhancing ANPR accuracy for staff car verification using convolutional neural networks and RegEX correction

AWOSEYI,

TIMOTHY,

ONUIRI

et al. 2024

IJ-AI

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This research paper presents the development and evaluation of an Automatic Number Plate Recognition (ANPR) system using Convolutional Neural Networks (CNN) with Regex correction. The aim is to enhance the accuracy and effectiveness of car verification and security processes at First Technical University, Ibadan. The ANPR system was implemented both without Regex correction and with Regex correction. The evaluation results demonstrate significant improvements in the system's performance when CNN with Regex correction is employed. The CNN-based ANPR system achieves a precision of 1.00, recall of 0.90, and F1-score of 0.95 in accurately identifying number plates. These scores indicate increased accuracy and reduce false positives compared to the system without Regex correction. The integration of CNN and Regex correction effectively handles variations and errors in the number plate data, leading to a reliable and efficient car verification process. Future work can focus on further refining the CNN model and optimizing the Regex correction algorithms to enhance the system's accuracy and robustness. The developed ANPR system, utilizing CNN with Regex correction, shows great potential for enhancing car verification and security in various domains, including law enforcement, parking management, and traffic monitoring

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“…In this work, we are mostly concerned with generating correct RegExs that represent valid solutions to a given task because writing complex RegExs that accept different answers is tedious and error-prone. Existing work on ensuring the correctness of RegExs has recently been reviewed by Zheng et al [31]. While there are numerous approaches to testing or even verifying existing RegExs, methods for creating RegExs are mostly concerned with learning them either from examples or from a natural language description.…”

Section: Related Workmentioning

confidence: 99%

Computer Aided Design and Grading for an Electronic Functional Programming Exam

Lübke,

Fuger,

Bahnsen

et al. 2023

Electron. Proc. Theor. Comput. Sci.

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Electronic exams (e-exams) have the potential to substantially reduce the effort required for conducting an exam through automation. Yet, care must be taken to sacrifice neither task complexity nor constructive alignment nor grading fairness in favor of automation. To advance automation in the design and fair grading of (functional programming) e-exams, we introduce the following: A novel algorithm to check Proof Puzzles based on finding correct sequences of proof lines that improves fairness compared to an existing, edit distance-based algorithm; an open-source static analysis tool to check source code for task relevant features by traversing the abstract syntax tree; a higher-level language and open-source tool to specify regular expressions that makes creating complex regular expressions less error-prone. Our findings are embedded in a complete experience report on transforming a paper exam to an e-exam. We evaluated the resulting e-exam by analyzing the degree of automation in the grading process, asking students for their opinion, and critically reviewing our own experiences. Almost all tasks can be graded automatically at least in part (correct solutions can almost always be detected as such), the students agree that an e-exam is a fitting examination format for the course but are split on how well they can express their thoughts compared to a paper exam, and examiners enjoy a more time-efficient grading process while the point distribution in the exam results was almost exactly the same compared to a paper exam.

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Ensuring the Correctness of Regular Expressions: A Review

Cited by 8 publications

References 71 publications

A web content mining application for detecting relevant pages using Jaccard similarity

A web content mining application for detecting relevant pages using Jaccard similarity

Enhancing ANPR accuracy for staff car verification using convolutional neural networks and RegEX correction

Computer Aided Design and Grading for an Electronic Functional Programming Exam

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