Carlos Huertas

NLARE, a natural language processing tool for automatic requirements evaluation

Most research works have found that an important root cause of software project failure comes from the requirements; their quality has an important impact over other artifacts. As the requirements are expressed in natural language, they can be an important source of defects. Aspects such as non ambiguity, completeness, and atomicity can be affected due the characteristics of natural language. Traditional practices focus on finding software bugs, as a corrective approach, until the project has been coded already, instead assuring quality since the beginning. By other hand, evaluating such quality attributes can be a difficult task. In this paper we propose some guidelines for a disciplined sentence structure for expressing the requirements, which allows natural language processing techniques to evaluate quality. We also propose a tool for automatic requirement evaluation based on the grammar structure of sentences expressed in natural language. With this tool we have a huge speed increase over manual evaluation. In order to validate our proposal we have implemented a set of experiments with real projects, assessing the impact of requirements quality over project results.

Problems in the Adoption of Agile-Scrum Methodologies: A Systematic Literature Review

Agile methodologies are focused on the people and functional product delivery in short periods of time. There are methodologies that change considerably the work habits of software developers. Scrum is an agile methodology that involves an iterative, incremental, and empiric process. Besides it is designed to add value, focus, clarity and transparency to the activities and products of a project. Nowadays, most companies are interested in the adoption of agile methodologies. Although Scrum is a light process and easy to understand, its adoption sometimes is difficult. Agile methodologies are not obvious by themselves, so they are difficult to introduce in the culture of a company. In order to identify the problems presented during the adoption, a Systematic Literature Review is performed focusing in Scrum. We found several problems, these are categorized in four groups: people, process, project, and company (organization). The results represent a basis to propose a framework to support the agile adoption.

A formal approach for measuring the lexical ambiguity degree in natural language requirement specification: Polysemes and Homonyms focused

In natural language regardless the presentation, being spoken or written we can distinguish different types of ambiguity. In this paper we will focus on written lexical ambiguity, which is caused when a word or set of words has more than one meaning. This inherent problem of natural language is generated by two types of words: Polysemes and Homonyms. Commonly requirement specifications are expressed in natural language even with the knowledge of inherent problems this have. Measuring ambiguity typically only includes the language itself as the universe; in this paper we include the transport channel and communication model to give a formal approach to find ambiguity degree based on stakeholder knowledge and how readers brain resolves ambiguity for a given text.

Automated Generation of User-Interface Prototypes Based on Controlled Natural Language Description

Most software applications are derived from customer needs, which mainly are expressed as functional requirements. These requirements are the basis for software construction. Identifying user actions, system actions, inputs and outputs from functional requirements, is a fundamental task for deriving usability aspects. In this paper we present a proposal for automating the generation of user interface prototypes with the main idea of minimize the task overload and take advantage of work that is already done in development cycle such as: requirements and use case description expressed in natural language. This proposal allows us to integrate functionality and usability since the beginning of the software development process. Also, we present a basis for the automation of adaptive user interfaces generation.

Developing Software Engineering Competences in Undergraduate Students: A Project-Based Learning Approach in Academy-Industry Collaboration

Project-based learning approach is focused in preparing students to work in industry. In traditional academic environments, it is difficult to reproduce real scenarios such as in industry. Software Engineering courses require practice and learning hands-on, however, with such limitations in academy, it is not easy to develop the competences to work in real world practice. In this paper we present our experiences working with undergraduate students in real projects in collaboration academy-industry. This environment allows us to develop Software Engineering competences to students. We assessed how our students get the set of competences suggested by the Software Engineering Education Knowledge standard, having encouraging results for a Computer Engineering undergraduate program.

Heat Map Based Feature Selection: A Case Study for Ovarian Cancer

Public health is a critical issue, therefore we can find a great research interest to find faster and more accurate methods to detect diseases. In the particular case of cancer, the use of mass spectrometry data has become very popular but some problems arise due to that the number of mass-to-charge ratios exceed by a huge margin the number of patients in the samples. In order to deal with the high dimensionality of the data, most works agree with the necessity to use pre-processing. In this work we propose an algorithm called Heat Map Based Feature Selection (HmbFS) that can work with huge data without the need of pre-processing, thanks to a built-in compression mechanism based on color quantization. Results shows that our proposal is very competitive against some of the most popular algorithms and succeeds where other methodologies may fail due to the high dimensionality of the data.