Special Issue "Special Issues on Languages Processing"

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Artificial Intelligence".

Deadline for manuscript submissions: closed (31 October 2017)

Special Issue Editors

Guest Editor
Prof. Ricardo Alexandre Peixoto de Queirós

ESMAD, Polytechnic Institute of Oporto, Portugal; Information Systems and Technologies, Center for Research in Advanced Computing Systems (CRACS), INESC TEC, Portugal
Website | E-Mail
Interests: computer science education; systems architecture; web data and services; languages processing
Guest Editor
Prof. Mário Paulo Teixeira Pinto

ESMAD, Polytechnic Institute of Oporto, Portugal; Information Systems and Technologies; International Society for Professional Innovation Management (ISPIM); Media Arts and Design Research Unit (UNIMAD), Portugal
Website | E-Mail
Interests: computer science education; information and knowledge management systems; multimedia educational resources for learning
Guest Editor
Prof. Carlos Filipe da Silva Portela

Information Systems and Technologies, ALGORITMI Research Centre, University of Minho; ESMAD, Polytechnic Institute of Oporto, Portugal
Website | E-Mail
Interests: data science; pervasive information system; artificial intelligence; decision support systems; data mining; business intelligence; biomedical informatics

Special Issue Information

Dear Colleagues,

We often use languages. First, to communicate between ourselves. Later, to communicate with computers. In addition, more recently, with the advent of networks, we found a way to make computers communicate among themselves. All these different forms of communication use languages, different languages, but languages that still share many similarities. In this Special Issue, we will publish an extended version of best papers selected from Symposium on Languages, Applications, and Technologies (SLATE'17).

In this Special Issue, the three types of processing languages are addressed: Human–Human (HHL), Human–Computer (HCL) and Computer–Computer Languages (CCL).

Prof. Ricardo Queirós
Prof. Mário Pinto
Prof. Filipe Portela
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Information is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 350 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

Open AccessArticle Source Code Documentation Generation Using Program Execution
Information 2017, 8(4), 148; doi:10.3390/info8040148
Received: 30 September 2017 / Revised: 13 November 2017 / Accepted: 14 November 2017 / Published: 17 November 2017
PDF Full-text (291 KB) | HTML Full-text | XML Full-text
Abstract
Automated source code documentation approaches often describe methods in abstract terms, using the words contained in the static source code or code excerpts from repositories. In this paper, we describe DynamiDoc: a simple automated documentation generator based on dynamic analysis. Our representation-based approach
[...] Read more.
Automated source code documentation approaches often describe methods in abstract terms, using the words contained in the static source code or code excerpts from repositories. In this paper, we describe DynamiDoc: a simple automated documentation generator based on dynamic analysis. Our representation-based approach traces the program being executed and records string representations of concrete argument values, a return value and a target object state before and after each method execution. Then, for each method, it generates documentation sentences with examples, such as “When called on [3, 1.2] with element = 3, the object changed to [1.2]”. Advantages and shortcomings of the approach are listed. We also found out that the generated sentences are substantially shorter than the methods they describe. According to our small-scale study, the majority of objects in the generated documentation have their string representations overridden, which further confirms the potential usefulness of our approach. Finally, we propose an alternative, variable-based approach that describes the values of individual member variables, rather than the state of an object as a whole. Full article
(This article belongs to the Special Issue Special Issues on Languages Processing)
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Open AccessArticle On the Implementation of a Cloud-Based Computing Test Bench Environment for Prolog Systems
Information 2017, 8(4), 129; doi:10.3390/info8040129
Received: 13 September 2017 / Revised: 10 October 2017 / Accepted: 13 October 2017 / Published: 19 October 2017
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Abstract
Software testing and benchmarking are key components of the software development process. Nowadays, a good practice in large software projects is the continuous integration (CI) software development technique. The key idea of CI is to let developers integrate their work as they produce
[...] Read more.
Software testing and benchmarking are key components of the software development process. Nowadays, a good practice in large software projects is the continuous integration (CI) software development technique. The key idea of CI is to let developers integrate their work as they produce it, instead of performing the integration at the end of each software module. In this paper, we extend a previous work on a benchmark suite for the YAP Prolog system, and we propose a fully automated test bench environment for Prolog systems, named Yet Another Prolog Test Bench Environment (YAPTBE), aimed to assist developers in the development and CI of Prolog systems. YAPTBE is based on a cloud computing architecture and relies on the Jenkins framework as well as a new Jenkins plugin to manage the underlying infrastructure. We present the key design and implementation aspects of YAPTBE and show its most important features, such as its graphical user interface (GUI) and the automated process that builds and runs Prolog systems and benchmarks. Full article
(This article belongs to the Special Issue Special Issues on Languages Processing)
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