Restricted Natural Language and Model-based Adaptive Test Generation for Autonomous Driving

2021 ◽  
Author(s):  
Yize Shi ◽  
Chengjie Lu ◽  
Man Zhang ◽  
Huihui Zhang ◽  
Tao Yue ◽  
...  
Keyword(s):  
Natural Language ◽  
Test Generation ◽  
Autonomous Driving ◽  
Adaptive Test ◽  
Model Based

scholarly journals Towards an Automated Model-Based Test Generation Approach from Controlled Natural Language Specifications Written in Arabic

2021 ◽  
Author(s):  
Moez Krichen ◽  
Seifeddine Mechti
Keyword(s):  
Natural Language ◽  
Test Generation ◽  
Arabic Language ◽  
Test Cases ◽  
New Model ◽  
Controlled Natural Language ◽  
Model Based ◽  
Case Grammar ◽  
Model Based Testing ◽  
Testing Approach

<div>We propose a new model-based testing approach which takes as input a set of requirements described in Arabic Controlled Natural Language (CNL) which is a subset of the Arabic language generated by a specific grammar. The semantics of the considered requirements is defined using the Case Grammar Theory (CTG). The requirements are translated into Transition Relations which serve as an input for test cases generation tools.</div>

scholarly journals Towards an Automated Model-Based Test Generation Approach from Controlled Natural Language Specifications Written in Arabic

2021 ◽  
Author(s):  
Moez Krichen ◽  
Seifeddine Mechti
Keyword(s):  
Natural Language ◽  
Test Generation ◽  
Arabic Language ◽  
Test Cases ◽  
New Model ◽  
Controlled Natural Language ◽  
Model Based ◽  
Case Grammar ◽  
Model Based Testing ◽  
Testing Approach

<div>We propose a new model-based testing approach which takes as input a set of requirements described in Arabic Controlled Natural Language (CNL) which is a subset of the Arabic language generated by a specific grammar. The semantics of the considered requirements is defined using the Case Grammar Theory (CTG). The requirements are translated into Transition Relations which serve as an input for test cases generation tools.</div>

Application of natural language processing for systematic requirement management in model‐based systems engineering

2021 ◽  
Vol 31 (1) ◽  
pp. 806-815
Author(s):  
Michael Riesener ◽  
Christian Dölle ◽  
Annika Becker ◽  
Sofia Gorbatcheva ◽  
Eric Rebentisch ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Systems Engineering ◽  
Model Based ◽  
Requirement Management ◽  
Model Based Systems Engineering

scholarly journals Sentiment Analysis on Twitter Airline Data

2021 ◽  
Vol 9 (VI) ◽  
pp. 3767-3770
Author(s):  
Kirti Jain
Keyword(s):  
Machine Learning ◽  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Learning Task ◽  
Model Based ◽  
Sentiment Mining ◽  
General Opinion

Sentiment analysis, also known as sentiment mining, is a submachine learning task where we want to determine the overall sentiment of a particular document. With machine learning and natural language processing (NLP), we can extract the information of a text and try to classify it as positive, neutral, or negative according to its polarity. In this project, We are trying to classify Twitter tweets into positive, negative, and neutral sentiments by building a model based on probabilities. Twitter is a blogging website where people can quickly and spontaneously share their feelings by sending tweets limited to 140 characters. Because of its use of Twitter, it is a perfect source of data to get the latest general opinion on anything.

Migrating from ISO/IEC 9126 to SQUARE

2017 ◽  
pp. 160-178
Author(s):  
Paula Estrella ◽  
Nikos Tsourakis
Keyword(s):  
Natural Language ◽  
Potential User ◽  
Use Case ◽  
Relative Importance ◽  
Quality Model ◽  
Evaluation Methodologies ◽  
Model Based ◽  
Fair Comparison ◽  
Definition Of ◽  
Current Standards

When it comes to the evaluation of natural language systems, it is well acknowledged that there is a lack of common evaluation methodologies, making the fair comparison of such systems a difficult task. Many attempts to standardize this process have used a quality model based on the ISO/IEC 9126 standards. The authors have also used these standards for the definition of a weighted quality model for the evaluation of a medical speech translator, showing the relative importance of the system's features depending on the potential user (patient or doctor, developer). More recently, ISO/IEC 9126 has been replaced by a new series of standards, the 25000 or SQuaRE series, indicating that the model should be migrated to the new series in order to maintain compliance adherence to current standards. This chapter demonstrates how to migrate from ISO/IEC 9126 to ISO 25000 by using the authors' previous work as a use case.

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