José Raúl Romero

José Raúl Romero
University of Cordoba (Spain) | UCO · Department of Computer Sciences and Numerical Analysis

Associate professor

About

83
Publications
20,893
Reads
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1,572
Citations
Introduction
Jose Raul Romero is an associate professor at the University of Córdoba, Spain. His research interests include, on the one hand, the application of bioinspired algorithms to complex data mining tasks and intelligent systems. On the other hand, he works on the application of model-driven software engineering(MDE) techniques and the design of DSL (Domain Specific Languages). He also works in combining AI and SE: Search-based software engineering.
Additional affiliations
January 2006 - present
University of Cordoba (Spain)
Position
  • Professor (Associate)
October 2003 - December 2005
University of Malaga
Position
  • PhD Student
Education
September 2005 - June 2007
University of Malaga
Field of study
  • Master in ICT applied to education
October 2003 - October 2007
University of Malaga
Field of study
  • Computer Science
September 1998 - June 2001
University of Malaga
Field of study
  • Computer science

Publications

Publications (83)
Article
Most software companies have extensive test suites and re-run parts of them continuously to ensure recent changes have no adverse effects. Since test suites are costly to execute, industry needs methods for test case prioritisation (TCP). Recently, TCP methods use machine learning (ML) to exploit the information known about the system under test (S...
Preprint
Full-text available
Most software companies have extensive test suites and re-run parts of them continuously to ensure recent changes have no adverse effects. Since test suites are costly to execute, industry needs methods for test case prioritisation (TCP). Recently, TCP methods use machine learning (ML) to exploit the information known about the system under test (S...
Article
Multi‐objective optimization problems frequently appear in many diverse research areas and application domains. Metaheuristics, as efficient techniques to solve them, need to be easily accessible to users with different expertise and programming skills. In this context, metaheuristic optimization frameworks are helpful, as they provide popular algo...
Article
Design patterns (DPs) are recognised as a good practice in software development. However, the lack of appropriate documentation often hampers traceability, and their benefits are blurred among thousands of lines of code. Automatic methods for DP detection have become relevant but are usually based on the rigid analysis of either software metrics or...
Article
Since its appearance in 2001, search-based software engineering has allowed software engineers to use optimisation techniques to automate distinctive human problems related to software management and development. The scientific community in Spain has not been alien to these advances. Their contributions cover both the optimisation of software engin...
Article
Search-Based Software Engineering (SBSE) has been successfully applied to automate a wide range of software development activities. Nevertheless, in those software engineering problems where human evaluation and preference are crucial, such insights have proved difficult to characterize in search, and solutions might not look natural when that is t...
Article
Although metaheuristics have been widely recognized as efficient techniques to solve real-world optimization problems, implementing them from scratch remains difficult for domain-specific experts without programming skills. In this scenario, metaheuristic optimization frameworks are a practical alternative as they provide a variety of algorithms co...
Article
Full-text available
Search-based software engineering (SBSE) is changing the way traditional software engineering (SE) activities are carried out by reformulating them as optimisation problems. The natural evolution of SBSE is bringing new challenges, such as the need of a large number of objectives to formally represent the many decision criteria involved in the reso...
Article
While working on a software specification, designers usually need to evaluate different architectural alternatives to be sure that quality criteria are met. Even when these quality aspects could be expressed in terms of multiple software metrics, other qualitative factors cannot be numerically measured, but they are extracted from the engineers kno...
Chapter
The great variety and intrinsic complexity of current Big Data technologies hampers the development of analytic processes for large data sets in domains where their business experts are not required to have specialized knowledge in computing, such as data mining, parallel computing, machine learning or software development. New approaches are there...
Conference Paper
Designing complex software systems involves making choices. Particularly in the early stages, software architects need to consider a wide range of design alternatives in order to satisfactorily meet all the requirements. Search techniques like evolutionary algorithms can support them to better explore these choices, requiring the resolution of the...
Conference Paper
Data analysis applications have become essential to extract significant insight from heterogeneous data sources. However, their development requires technical expertise in computer science techniques like data mining, making its broad adoption by non-experts difficult. In this context, workflows have emerged as a high-level solution to define and a...
Article
Full-text available
During the design of complex systems, software architects have to deal with a tangle of abstract artefacts, measures and ideas to discover the most fitting underlying architecture. A common way to structure such complex systems is in terms of their interacting software components, whose composition and connections need to be properly adjusted. Alon...
Article
Web service based applications often invoke services provided by third-parties in their workflow. The Quality of Service (QoS) provided by the invoked supplier can be expressed in terms of the Service Level Agreement specifying the values contracted for particular aspects like cost or throughput, among others. In this scenario, intelligent systems...
Conference Paper
The ongoing advances in multi-objective optimisation (MOO) are improving the way that complex real-world optimisation problems, mostly characterised by the definition of many conflicting objectives, are currently addressed. To put it into practice, developers require flexible implementations of these algorithms so that they can be adapted to the pr...
Article
Software architectures constitute important analysis artefacts in software projects, as they reflect the main functional blocks of the software. They provide high-level analysis artefacts that are useful when architects need to analyse the structure of working systems. Normally, they do this process manually, supported by their prior experiences. E...
Article
Full-text available
This paper proposes a novel grammar-guided genetic programming algorithm for subgroup discovery. This algorithm, called comprehensible grammar-based algorithm for subgroup discovery (CGBA-SD), combines the requirements of discovering comprehensible rules with the ability to mine expressive and flexible solutions owing to the use of a context-free g...
Chapter
Full-text available
ata pre-processing is the first step in any data mining process, being one of the most important but less studied tasks in educational data mining research. Pre-processing allows transforming the available raw educational data into a suitable format ready to be used by a data mining algorithm for solving a specific educational problem. However, mos...
Article
On the one hand, swarm intelligence (SI) is an emerging field of artificial intelligence that takes inspiration in the collective and social behaviour of different groups of simple agents. On the other hand, the automatic evolution of programs is an active research area that has attracted a lot of interest and has been mostly promoted by the geneti...
Article
Full-text available
The extraction of useful information for decision making is a challenge in many different domains. Association rule mining is one of the most important techniques in this field, discovering relationships of interest among patterns. Despite the mining of association rules being an area of great interest for many researchers, the search for well-grou...
Article
Full-text available
Extracting frequent and reliable rules has been the main interest of the association task of data mining. However, the discovery or infrequent or rare rules is attracting a lot of interest in many domains, such as banking frauds, biomedical data and network intrusion. Most of existent solutions for discovering reliable rules rarely appearing are ba...
Chapter
Full-text available
Ant programming is a kind of automatic programming that generates computer programs by using the ant colony metaheuristic as the search technique. It has demonstrated a good generalization ability for the extraction of comprehensible classifiers. To date, three ant programming algorithms for classification rule mining have been proposed in the lite...
Conference Paper
During the design of complex systems, software architects have to deal with a tangle of abstract artefacts, measures and ideas to discover the most fitting underlying architecture. A common way to structure these systems is in terms of their interacting software components, whose composition and connections need to be properly adjusted. Its abstrac...
Article
Full-text available
Association rule mining, an important data mining technique, has been widely focused on the extraction of frequent patterns. Nevertheless, in some application domains it is interesting to discover patterns that do not frequently occur, even when they are strongly related. More specifically, this type of relation can be very appropriate in e-learnin...
Conference Paper
Full-text available
Most researches in association rule mining have focused on the extraction of frequent and reliable associations. However, there is an increasing interest in finding reliable rules that rarely appear, and recently, some classical solutions have been adapted to this field. The problem is that most of these algorithms follow an exhaustive approach, wh...
Conference Paper
Full-text available
Component identification is a critical phase in software architecture analysis to prevent later errors and control the project time and budget. Obtaining the most appropriate architecture according to predetermined design criteria can be treated as an optimization problem, especially since the appearance of the Search Based Software Engineering, an...
Article
In association rule mining, the process of extracting relations from a dataset often requires the application of more than one quality measure and, in many cases, such measures involve conflicting objectives. In such a situation, it is more appropriate to attain the optimal trade-off between measures. This paper deals with the association rule mini...
Article
Full-text available
This paper treats the first approximation to the extraction of association rules by employing ant programming, a technique that has recently reported very promising results in mining classification rules. In particular, two different algorithms are presented, both guided by a context-free grammar that defines the search space, specifically suited t...
Conference Paper
This paper deals with the problem of discovering subgroups in data by means of a grammar guided genetic programming algorithm, each subgroup including a set of related patterns. The proposed algorithm combines the requirements of discovering comprehensible rules with the ability of mining expressive and flexible solutions thanks to the use of a con...
Article
This paper shows how web usage mining can be applied in e-learning systems in order to predict the marks that university students will obtain in the final exam of a course. We have also developed a specific Moodle mining tool oriented for the use of not only experts in data mining but also of newcomers like instructors and courseware authors. The p...
Article
Full-text available
This paper provides an editorial introduction to the current special issue on Open Distributed Processing. It looks back over the development of the ODP standards and at the way in which they have been used, and looks forward at the way current activities are progressing. It contains a broad bibliography covering ODP standards, related research wor...
Article
As the complexity of open distributed systems grows, the need to rely on concepts and notations for expressing and structuring their specifications becomes essential. However, having concepts and notations is not enough. The large size and complexity of the set of models that constitute the system specifications also forces the need to have tools f...
Article
Full-text available
This paper treats the first approximation to the extraction of association rules by employing ant programming, a technique that has recently reported very promising results in mining classification rules. In particular, two different algorithms are presented, both guided by a context-free grammar, specifically suited to association rule mining, whi...
Article
Full-text available
This paper proposes a multi-objective ant programming algorithm for mining classification rules, MOGBAP, which focuses on optimizing sensitivity, specificity, and comprehensibility. It defines a context-free grammar that restricts the search space and ensures the creation of valid individuals, and its heuristic function presents two complementary c...
Conference Paper
Full-text available
Classification in imbalanced domains is a challenging task, since most of its real domain applications present skewed distributions of data. However, there are still some open issues in this kind of problem. This paper presents a multi-objective grammar-based ant programming algorithm for imbalanced classification, capable of addressing this task f...
Conference Paper
Full-text available
This paper presents a free-parameter grammar-guided genetic programming algorithm for mining association rules. This algorithm uses a contex-free grammar to represent individuals, encoding the solutions in a tree-shape conformant to the grammar, so they are more expressive and flexible. The algorithm here presented has the advantages of using evolu...
Conference Paper
This paper presents VisualJCLEC, a visual framework based on JCLEC for Evolutionary Computing. In order to have a high degree of adaptability, the architecture and pattern design followed are focused on enhancing the flexibility and scalability. For illustrative purposes, a case study of an optimization classical problem (the knapsack problem) usin...
Data
Full-text available
This paper presents a proposal for the extraction of association rules called G3PARM (Grammar-Guided Genetic Programming for Association Rule Mining) that makes the knowledge extracted more expressive and flexible. This algorithm allows a context-free grammar to be adapted and applied to each specific problem or domain and eliminates the problems r...
Conference Paper
Ant programming (AP) is a kind of automatic programming that generates computer programs by using the ant colony optimization metaheuristic. It has recently demonstrated a good generalization ability when extracting classification rules. We extend the investigation on the application of AP to classification, developing an algorithm that addresses r...
Article
Full-text available
The extraction of comprehensible knowledge is one of the major challenges in many domains. In this paper, an ant programming (AP) framework, which is capable of mining classification rules easily comprehensible by humans, and, therefore, capable of supporting expert-domain decisions, is presented. The algorithm proposed, called grammar based ant pr...
Article
To date, association rule mining has mainly focused on the discovery of frequent patterns. Nevertheless, it is often interesting to focus on those that do not frequently occur. Existing algorithms for mining this kind of infrequent patterns are mainly based on exhaustive search methods and can be applied only over categorical domains. In a previous...
Conference Paper
Full-text available
This paper presents a method for extracting association rules by means of a multi-objective grammar guided ant programming algorithm. Solution construction is guided by a context-free grammar specifically suited for association rule mining, which defines the search space of all possible expressions or programs. Evaluation of individuals is consider...
Conference Paper
Whereas the extraction of frequent patterns has focused the major researches in association rule mining, the requirements of reliable rules that do not frequently appear is taking an increasing interest in a great number of areas. This field has not been explored in depth and most algorithms for mining infrequent association rules follow an exhaust...
Article
Nowadays, there are a great number of both specific and general data mining tools available to carry out association rule mining. However, it is necessary to use several of these tools in order to obtain only the most interesting and useful rules for a given problem and dataset. To resolve this drawback, this paper describes a fully integrated fram...
Article
Full-text available
This paper presents a proposal for the extraction of association rules called G3PARM (Grammar-Guided Genetic Programming for Association Rule Mining) that makes the knowledge extracted more expressive and flexible. This algorithm allows a context-free grammar to be adapted and applied to each specific problem or domain and eliminates the problems r...
Conference Paper
Full-text available
This work presents a novel proposal for incremental intruder detection in collaborative recommender systems. We explore the use of rare association rule mining to reveal the existence of a suspected raid of attackers that would alter the normal behaviour of a rating-based system. In this position paper we have extended our previous G3PARM algorithm...
Conference Paper
Full-text available
Rare association rules are those that only appear infrequently even though they are highly associated with very specific data. In consequence, these rules can be very appropriate for using with educational datasets since they are usually imbalanced. In this paper, we explore the extraction of rare association rules when gathering student usage data...
Conference Paper
There are both advantages and disadvantages of using visual and textual notations for expressing large system specifications. Each kind of notation seems to be more apt for expressing and managing some aspects, and there is no clear winner. A solution can be the use of both styles, with synchronization mechanisms that always keep them in synch. In...
Conference Paper
Full-text available
This paper presents the G3PARM algorithm for mining representative association rules. G3PARM is an evolutionary algorithm that uses G3P (Grammar Guided Genetic Programming) and an auxiliary population made up of its best individuals who will then act as parents for the next generation. Due to the nature of G3P, the G3PARM algorithm allows us to obt...
Conference Paper
Full-text available
This paper focuses on the application of a new ACO-based automatic programming algorithm to the classification task of data mining. This new model, called GBAP algorithm, is based on a context-free grammar that properly guides the creation of new valid individuals. Moreover, its most differentiating factors, such as the use of two complementary heu...
Conference Paper
This paper presents an evolutionary algorithm using G3P (Grammar Guided Genetic Programming) for mining association rules in different real-world databases. This algorithm, called G3PARM, uses an auxiliary population made up of its best individuals that will then act as parents for the next generation. The individuals are defined through a context-...
Conference Paper
Full-text available
In this paper we present a novel algorithm, named GBAP, that jointly uses automatic programming with ant colony optimization for mining classification rules. GBAP is based on a context-free grammar that properly guides the search process of valid rules. Furthermore, its most important characteristics are also discussed, such as the use of two diffe...
Chapter
In this paper we present a novel algorithm, named GBAP, that jointly uses automatic programming with ant colony optimization for mining classification rules. GBAP is based on a context-free grammar that properly guides the search process of valid rules. Furthermore, its most important characteristics are also discussed, such as the use of two diffe...
Conference Paper
Full-text available
Viewpoint modeling is an effective technique for specifying complex software systems in terms of a set of independent viewpoints and correspondences between them. Each viewpoint focuses on a particular aspect of the system, abstracting away from the rest of the concerns. Correspondences specify the relationships between the elements in different vi...
Article
Full-text available
Viewpoint modeling has demonstrated to be an effective approach for specifying complex software systems by means of a set of independent views and correspondences between them. As any other software system, a Web ap-plication evolves during its lifetime, and its specifications change to meet new requirements or to adapt to business changes. As a co...
Conference Paper
Full-text available
Although Model Driven Software Development (MDSD) is achieving significant progress, it is still far from becoming a real Engineering discipline. In fact, many of the difficult problems of the engineering of complex software systems are still unresolved, or simplistically addressed by many of the current MDSD approaches. In this position paper we o...
Conference Paper
Full-text available
Viewpoint modeling is an effective technique for specifying complex software systems in terms of a set of independent viewpoints and correspondences between them. Each viewpoint focuses on a particular aspect of the system, abstracting away from the rest of the concerns. Correspondences specify the relationships between the elements in different vi...
Conference Paper
Full-text available
Service Enterprise Architecture (SEA) is nowadays gaining a wider audience in companies using large-scale IT systems. It combines service orientation and viewpoint modeling. Hence, service orientation is attractive due to its ability to virtualize component architecture and to enable easier composition and contractualization. However, services may...
Article
Full-text available
The open distributed processing (ODP) computational viewpoint describes the functionality of a system and its environment in terms of a configuration of objects interacting at interfaces, independently of their distribution. Quality of service (QoS) contracts and service level agreements are an integral part of any computational specification, whic...
Conference Paper
Full-text available
Distributed Software Engineering (DSE) concepts in Computer Science (or Engineering) Degrees are commonly introduced using a hands-on approach mainly consisting of teaching a particular distributed and component-based technology platform (such as Java Enterprise Edition or Microsoft .NET) and proposing the students to develop a small distributed so...
Chapter
Full-text available
Model-Driven Software Development (MDSD) is becoming a widely accepted approach for developing complex distributed applications. MDSD advocates the use of models as the key artifacts in all phases of development, from system specification and analysis to design and implementation. Each model usually addresses one concern, independently from the res...