A knowledge representation semantic network for a natural language syntactic analyzer based on the UML

The need for improving software processes approximated the software engineering and artificial intelligence areas. Artificial intelligence techniques have been used as a support to software development processes, particularly through intelligent assistants that offer a knowledge-based support to software process’ activities. The context of the present work is a project for an intelligent assistant that implements a linguistic technique with the purpose of extracting object-oriented elements from requirement specifications in natural language through two main functionalities: the syntactic and semantic analyses. The syntactic analysis has the purpose of extracting the syntactic constituents from a sentence; and the semantic analysis has the goal of extracting the meaning from a set of sentences, i.e., a text. This paper focuses on the syntactic analysis functionality and applies the UML to its core as a semantic network for knowledge representation, based on the premise that the UML is de facto a standard general modeling language for software development.Applications in Artificial Intelligence - Language ProcessingRed de Universidades con Carreras en Informática (RedUNCI

A knowledge representation semantic network for a natural language syntactic analyzer based on the UML

The need for improving software processes approximated the software engineering and artificial intelligence areas. Artificial intelligence techniques have been used as a support to software development processes, particularly through intelligent assistants that offer a knowledge-based support to software process’ activities. The context of the present work is a project for an intelligent assistant that implements a linguistic technique with the purpose of extracting object-oriented elements from requirement specifications in natural language through two main functionalities: the syntactic and semantic analyses. The syntactic analysis has the purpose of extracting the syntactic constituents from a sentence; and the semantic analysis has the goal of extracting the meaning from a set of sentences, i.e., a text. This paper focuses on the syntactic analysis functionality and applies the UML to its core as a semantic network for knowledge representation, based on the premise that the UML is de facto a standard general modeling language for software development.Applications in Artificial Intelligence - Language ProcessingRed de Universidades con Carreras en Informática (RedUNCI

Automated Problem Domain Cognition Process in Information Systems Design

An automated cognitive approach for the design of Information Systems is presented. It is supposed to be used at the very beginning of the design process, between the stages of requirements determination and analysis, including the stage of analysis. In the context of the approach used either UML or ERD notations may be used for model representation. The approach provides the opportunity of using natural language text documents as a source of knowledge for automated problem domain model generation. It also simplifies the process of modelling by assisting the human user during the whole period of working upon the model (using UML or ERD notations)

The ModelCC Model-Driven Parser Generator

Syntax-directed translation tools require the specification of a language by means of a formal grammar. This grammar must conform to the specific requirements of the parser generator to be used. This grammar is then annotated with semantic actions for the resulting system to perform its desired function. In this paper, we introduce ModelCC, a model-based parser generator that decouples language specification from language processing, avoiding some of the problems caused by grammar-driven parser generators. ModelCC receives a conceptual model as input, along with constraints that annotate it. It is then able to create a parser for the desired textual syntax and the generated parser fully automates the instantiation of the language conceptual model. ModelCC also includes a reference resolution mechanism so that ModelCC is able to instantiate abstract syntax graphs, rather than mere abstract syntax trees.Comment: In Proceedings PROLE 2014, arXiv:1501.0169

A prior case study of natural language processing on different domain

In the present state of digital world, computer machine do not understand the human’s ordinary language. This is the great barrier between humans and digital systems. Hence, researchers found an advanced technology that provides information to the users from the digital machine. However, natural language processing (i.e. NLP) is a branch of AI that has significant implication on the ways that computer machine and humans can interact. NLP has become an essential technology in bridging the communication gap between humans and digital data. Thus, this study provides the necessity of the NLP in the current computing world along with different approaches and their applications. It also, highlights the key challenges in the development of new NLP model

UmobiTalk: Ubiquitous Mobile Speech Based Learning Language Translator for Sesotho Language

Published ThesisThe need to conserve the under-resourced languages is becoming more urgent as some of them are becoming extinct; natural language processing can be used to redress this. Currently, most initiatives around language processing technologies are focusing on western languages such as English and French, yet resources for such languages are already available. The Sesotho language is one of the under-resourced Bantu languages; it is mostly spoken in Free State province of South Africa and in Lesotho. Like other parts of South Africa, Free State has experienced high number of migrants and non-Sesotho speakers from neighboring provinces and countries; such people are faced with serious language barrier problems especially in the informal settlements where everyone tends to speak only Sesotho. Non-Sesotho speakers refers to the racial groups such as Xhosas, Zulus, Coloureds, Whites and more, in which Sesotho language is not their native language. As a solution to this, we developed a parallel corpus that has English as source and Sesotho as a target language and packaged it in UmobiTalk - Ubiquitous mobile speech based learning translator. UmobiTalk is a mobile-based tool for learning Sesotho for English speakers. The development of this tool was based on the combination of automatic speech recognition, machine translation and speech synthesis

Identifying functional requirements inconsistencies in multiteam projects framed into a model-based methodology

REP (Requirements Engineering Process) is one of the most essential processes within the software project life cycle because it allows describing software product requirements. This specification should be as consistent as possible to enable estimating in a suitable manner the effort required to obtain the final product. REP is complex in itself, but this complexity is greatly increased in big, distributed and heterogeneous projects with multiple analyst teams and high integration among functional modules. This paper presents an approach for the systematic conciliation of functional requirements in big projects dealing with a model based approach. It also explains how this approach may be implemented in the context of NDT (Navigational Development Techniques) methodology and finally, it describes a preliminary evaluation of our proposal in CALIPSOneo project by analyzing the improvements obtained with our approach.Ministerio de Economía y Competitividad TIN2016-76956-C3-2-R (POLOLAS)Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2015-71938-RED

Recognizing design patterns in C++ programs with the integration of Columbus and Maisa

A method for recognizing design patterns from C++ programs is presented. The method consists of two separate phases, analysis and reverse engineering of the C++ code, and architectural pattern matching over the reverse-engineered intermediate code representation. It is shown how the pattern recognition effect can be realized by integrating two specialized software tools, the reverse engineering framework Columbus and the architectural metrics analyzer Maisa. The method and the integrated power of the tool set are illustrated with small experiments

SOFTENG 2023: the ninth international conference on advances and trends in software engineering

The Ninth International Conference on Advances and Trends in Software Engineering (SOFTENG 2023), held between April 24th and April 28th, 2023, continued a series of events focusing on these challenging aspects for software development and deployment, across the whole life-cycle. Software engineering exhibits challenging dimensions in the light of new applications, devices, and services. Mobility, user-centric development, smart-devices, e-services, ambient environments, e-health and wearable/implantable devices pose specific challenges for specifying software requirements and developing reliable and safe software. Specific software interfaces, agile organization and software dependability require particular approaches for software security, maintainability, and sustainability. We take here the opportunity to warmly thank all the members of the SOFTENG 2023 technical program committee, as well as all the reviewers. The creation of such a high-quality conference program would not have been possible without their involvement. We also kindly thank all the authors who dedicated much of their time and effort to contribute to SOFTENG 2023. We truly believe that, thanks to all these efforts, the final conference program consisted of top-quality contributions. We also thank the members of the SOFTENG 2023 organizing committee for their help in handling the logistics of this event. We hope that SOFTENG 2023 was a successful international forum for the exchange of ideas and results between academia and industry and for the promotion of progress in the field of software engineering