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

<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>

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

<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>

Probabilistic modelling and verification using RoboChart and PRISM

RoboChart is a timed domain-specific language for robotics, distinctive in its support for automated verification by model checking and theorem proving. Since uncertainty is an essential part of robotic systems, we present here an extension to RoboChart to model uncertainty using probabilism. The extension enriches RoboChart state machines with probability through a new construct: probabilistic junctions as the source of transitions with a probability value. RoboChart has an accompanying tool, called RoboTool, for modelling and verification of functional and real-time behaviour. We present here also an automatic technique, implemented in RoboTool, to transform a RoboChart model into a PRISM model for verification. We have extended the property language of RoboTool so that probabilistic properties expressed in temporal logic can be written using controlled natural language.

Logical English meets legal English for swaps and derivatives

In this paper, we present an informal introduction to Logical English (LE) and illustrate its use to standardise the legal wording of the Automatic Early Termination (AET) clauses of International Swaps and Derivatives Association (ISDA) Agreements. LE can be viewed both as an alternative to conventional legal English for expressing legal documents, and as an alternative to conventional computer languages for automating legal documents. LE is a controlled natural language (CNL), which is designed both to be computer-executable and to be readable by English speakers without special training. The basic form of LE is syntactic sugar for logic programs, in which all sentences have the same standard form, either as rules of the form conclusion if conditions or as unconditional sentences of the form conclusion. However, LE extends normal logic programming by introducing features that are present in other computer languages and other logics. These features include typed variables signalled by common nouns, and existentially quantified variables in the conclusions of sentences signalled by indefinite articles. Although LE translates naturally into a logic programming language such as Prolog or ASP, it can also serve as a neutral standard, which can be compiled into other lower-level computer languages.

The Isabelle/Naproche Natural Language Proof Assistant

Abstract"Image missing" is an emerging natural proof assistant that accepts input in the controlled natural language ForTheL. "Image missing" is included in the current version of the Isabelle/PIDE which allows comfortable editing and asynchronous proof-checking of ForTheL texts. The dialect of ForTheL can be typeset by "Image missing" into documents that approximate the language and appearance of ordinary mathematical texts.

Construction of English spoken language system based on machine learning algorithm and natural language recognition

English speech recognition system is affected by a variety of interference factors. Associating the algorithm with the support of modern computer technology can increase the model effect of speech recognition system. Based on the study of the current mainstream controlled natural language thesaurus, this paper proposes a controlled natural language vocabulary classification type. Moreover, this paper defines the domain thesaurus according to the WordNet knowledge description framework, and uses WordNet’s synonym, antisense, upper and lower, etc. In this way, the controlled natural language system can use the semantic relationship of WordNet to identify the words of the non-domain thesaurus input by the user and map the non-domain definition words to the words in the domain thesaurus, thereby improving the ease of use of controlled natural language systems. In addition, this paper designed a controlled experiment to analyze the performance of this system. The research results show that the model constructed in this paper has certain significant effects.

R2D2: A Dbpedia Chatbot Using Triple-Pattern Like Queries

Chatbots, also known as conversation agents, are programs that are able to simulate and reproduce an intelligent conversation with humans. Although this type of program is not new, the explosion of the available information and the rapid increase of the users seeking this information have renewed the interest in their development. In this paper, we present R2D2, an intelligent chatbot relying on semantic web technologies and offering an intelligent controlled natural language interface for accessing the information available in DBpedia. The chatbot accepts structured input, allowing users to enter triple-pattern like queries, which are answered by the underlying engine. While typing, an auto-complete service guides users on creating the triple patterns, suggesting resources available in the DBpedia. Based on user input (in the form of triple-pattern like queries), the corresponding SPARQL queries are automatically formulated. The queries are submitted to the corresponding DBpedia SPARQL endpoint, and then the result is received by R2D2 and augmented with maps and visuals and eventually presented to the user. The usability evaluation performed shows the advantages of our solution and its usefulness.