The goal of debugging is location and correction of bugs in arbitrary programs to improve their reliability. Since errors are established by an application’s source code, which is in most cases implemented with some kind of textual language, the traditional focus of debugging is on textual representations. While this may be sufficient for sequential programs, it limits the usefulness of paralle...

This paper describes the joint participation of the TIA-LabTL (INAOE) and the MindLab research group (UNAL) at the ImageCLEF 2015 Scalable Concept Image Annotation challenge subtask 2: generation of textual descriptions of images noisy track. Our strategy relies on a multimodal representation that is built in an unsupervised way by using the associated text to images and the visual features tha...

In this paper, we explore the help of visual features to cross-language image retrieval. We propose an approach that transforms textual queries into visual representations. The relationships between text and images are modeled. Visual queries are constructed from textual queries using the relationships. The retrieval results using textual and visual queries are combined to generate the final ra...

In this paper we present the evaluation of different features for multiligual and crosslevel semantic textual similarity. Three different types of features were used: lexical, knowledge-based and corpus-based. The results obtained at the Semeval competition rank our approaches above the average of the rest of the teams highlighting the usefulness of the features presented in this paper.

Most goal-oriented modeling languages, including i*, Tropos, KAOS and the Goal-oriented Requirement Language (GRL), offer a graphical syntax, sometimes accompanied by a textual interchange format (e.g., in XML). Graphical representations of goal models excel at supporting discussions and at visualizing analysis results. However, creating/modifying goal models is often a tedious task with curren...

Contemporary code review tools are a popular choice for software quality assurance. Using these tools, reviewers able to post linkage between two patches during discussion. Large development teams that use review-then-commit model risk being unaware of linkages. Our objective is first explore how patch impacts the process. We then propose and evaluate models detect based on realistic time inter...

Traditionally, collections of texts are digitally represented as a set of documents containing the text along with some kind of markup to define extra information, like metadata, annotations, etc. We propose a different approach that models the textual information in a dual way: as a formatted sequence of characters, as well as a composition of a particular kind of objects, called textual objec...

Textual Inference is a research trend in Natural Language Processing (NLP) that has recently received a lot of attention by the scientific community. Textual Entailment (TE) is a specific task in Textual Inference that aims at determining whether a hypothesis is entailed by a text. Usually tackled by machine learning techniques employing features which represent similarity between texts, the re...