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Resultados de búsqueda para Search-Based Software Engineering

Many-Objective Test Suite Generation for Software Product Lines

A Software Product Line (SPL) is a set of products builtfrom a number of features, the set of valid products being dened bya feature model. Typically, it does not make sense to test all productsdened by an SPL and one instead chooses a set of products to test(test selection) and, ideally, derives a good order in which to test them(test prioritisation). Since one cannot know in advance which productswill reveal faults, test selection and prioritisation are normally based onobjective functions that are known to relate to likely effectiveness orcost. This article introduces a new technique, the grid-based evolutionstrategy (GrES), which considers several objective functions that assessa selection or prioritisation and aims to optimise on all of these. Theproblem is thus a many-objective optimisation problem. We use a newapproach, in which all of the objective functions are considered but one(pairwise coverage) is seen as the most important. We also derive a novelevolution strategy based on domain knowledge. The results of the evalua-tion, on randomly generated and realistic feature models, were promising,with GrES outperforming previously proposed techniques and a range ofmany-objective optimisation algorithms.

Autores: Rob Hierons / Miqing Li / Xiaohui Liu / José Antonio Parejo Maestre / Sergio Segura Rueda / Xin Yao / 
Palabras Clave: Evolutionary algorithms - many-objectives optimization - Search-Based Software Engineering - software product lines - Testing

Looking for novelty in SBSE problems

Search-based software engineering (SBSE) was conceived to support engineers searching for innovative ideas to solve recurrent software engineering problems along the software project lifecycle. However, current approaches require the engineer to formulate and quantify their search objectives, which may be challenging. As SBSE consolidates as a discipline, problems become more demanding, and consequently the definition of the search problem and the characteristics of the search space remain oversimplified. Thus the evaluation of problem solutions by means of a fitness function could be failing to address essential aspects that can cause disappointment for the engineer after reaching final results. This position paper launches the idea that novelty search opens up a new scenario, as it rewards solution novelty, a concept mapping to problem characteristics other than fitness and whose definition might be more intuitive to the engineer. We explore its applicability to SBSE and discuss some preliminary findings of interest to the SBSE community.

Autores: José Raúl Romero / Aurora Ramírez / Christopher L. Simons / 
Palabras Clave: next release problem - novelty search - Search-Based Software Engineering

SIP: Optimal Product Selection from Feature Models Using Many-Objective Evolutionary Optimization

Robert M. Hierons, Miqing Li, Xiaohui Liu, Sergio Segura, and Wei Zheng. 2016. SIP: Optimal Product Selection from Feature Models Using Many-Objective Evolutionary Optimization. ACM Trans. Softw. Eng. Methodol. 25, 2, Article 17 (April 2016), 39 pages. DOI: http://dx.doi.org/10.1145/2897760 Indicadores de calidad: – Revista de referencia en el área de Ingeniería del Software (CS-SE: 21/106). – Colaboración internacional con los profesores Robert Hierons [1] y XiaoHui Liu [2]. – Hemos sido invitados a presentar el trabajo en FSE16 e ICSE17 como parte de la iniciativa journal-first (ver programa de la conferencia [3]). – Ha recibido 6 citas desde su publicación en abril de 2016 [4]. [1] http://dblp.uni-trier.de/pers/hd/h/Hierons:Robert_M= [2] http://dblp.uni-trier.de/pers/hd/l/Liu:Xiaohui [2] http://icse2017.gatech.edu/?q=technical-research-accepted [4] https://goo.gl/XyTmQR

Autores: Rob Hierons / Miqing Li / Xiaohui Liu Liu / Sergio Segura / Wei Zheng / 
Palabras Clave: Optimization - Search-Based Software Engineering - software product lines

Hacia un Algoritmo Exacto para Resolver el Problema de Agrupamiento de Módulos Software

El problema de agrupamiento de módulos software consiste en encontrar una partición del conjunto de módulos de un determinado software de tal forma que se maximice la cohesión entre módulos pertenecientes al mismo componente de la partición a la vez que se minimiza el acoplamiento entre módulos pertenecientes a distintos componentes. El objetivo es estructurar el software de una manera que mejore el desarrollo y la mantenibilidad del sistema. Este problema, conocido como emph{Software Module Clustering}, ha sido abordado en el pasado usando principalmente algoritmos heurísticos y metaheurísticas. En este trabajo describimos un algoritmo exacto basado en ramificación y poda.

Autores: Miguel Ángel Domínguez / Francisco Chicano / Enrique Alba / 
Palabras Clave: Agrupamiento de módulos software - Algoritmos exactos - Ramificación y poda - Search-Based Software Engineering

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