142 research outputs found
Validation of Constraints Among Configuration Parameters Using Search-Based Combinatorial Interaction Testing
The appeal of highly-configurable software systems lies in their adaptability to users’ needs. Search-based Combinatorial Interaction Testing (CIT) techniques have been specifically developed to drive the systematic testing of such highly-configurable systems. In order to apply these, it is paramount to devise a model of parameter configurations which conforms to the software implementation. This is a non-trivial task. Therefore, we extend traditional search-based CIT by devising 4 new testing policies able to check if the model correctly identifies constraints among the various software parameters. Our experiments show that one of our new policies is able to detect faults both in the model and the software implementation that are missed by the standard approaches
Mining Architectural Information: A Systematic Mapping Study
Context: Mining Software Repositories (MSR) has become an essential activity
in software development. Mining architectural information to support
architecting activities, such as architecture understanding and recovery, has
received a significant attention in recent years. However, there is an absence
of a comprehensive understanding of the state of research on mining
architectural information. Objective: This work aims to identify, analyze, and
synthesize the literature on mining architectural information in software
repositories in terms of architectural information and sources mined,
architecting activities supported, approaches and tools used, and challenges
faced. Method: A Systematic Mapping Study (SMS) has been conducted on the
literature published between January 2006 and November 2021. Results: Of the 79
primary studies finally selected, 8 categories of architectural information
have been mined, among which architectural description is the most mined
architectural information; 12 architecting activities can be supported by the
mined architectural information, among which architecture understanding is the
most supported activity; 81 approaches and 52 tools were proposed and employed
in mining architectural information; and 4 types of challenges in mining
architectural information were identified. Conclusions: This SMS provides
researchers with promising future directions and help practitioners be aware of
what approaches and tools can be used to mine what architectural information
from what sources to support various architecting activities.Comment: 68 pages, 5 images, 15 tables, Manuscript submitted to a Journal
(2022
CONTEXT MANAGEMENT: TOWARD ASSESSING QUALITY OF CONTEXT PARAMETERS IN A UBIQUITOUS AMBIENT ASSISTED LIVING ENVIRONMENT
This paper provides an approach to assessing Quality of Context (QoC) parameters in a ubiquitous Ambient Assisted Living (AAL) environment. Initially, the study presents a literature review on QoC, generating taxonomy. Then it introduces the context management architecture used. The proposal is verified with the Siafu simulator in an AAL scenario where the user’s health is monitored with information about blood pressure, heart rate and body temperature. Considering some parameters, the proposed QoC assessment allows verifying the extent to which the context information is up-to-date, valid, accurate, complete and significant. The implementation of this proposal might mean a big social impact and a technological innovation applied to AAL, at the disposal and support of a significant number of individuals such as elderly or sick people, and with a more precise technology
Towards Effective Bug Triage with Software Data Reduction Techniques
International audienceSoftware companies spend over 45 percent of cost in dealing with software bugs. An inevitable step of fixing bugs is bug triage, which aims to correctly assign a developer to a new bug. To decrease the time cost in manual work, text classification techniques are applied to conduct automatic bug triage. In this paper, we address the problem of data reduction for bug triage, i.e., how to reduce the scale and improve the quality of bug data. We combine instance selection with feature selection to simultaneously reduce data scale on the bug dimension and the word dimension. To determine the order of applying instance selection and feature selection, we extract attributes from historical bug data sets and build a predictive model for a new bug data set. We empirically investigate the performance of data reduction on totally 600,000 bug reports of two large open source projects, namely Eclipse and Mozilla. The results show that our data reduction can effectively reduce the data scale and improve the accuracy of bug triage. Our work provides an approach to leveraging techniques on data processing to form reduced and high-quality bug data in software development and maintenance
Transferencia de conocimiento en la gestión de calidad de la ingenierÃa de software
Los procesos y actividades en la gestión de calidad de la ingenierÃa de software generan un gran volumen de conocimiento, con lo cual es considerado como un factor crÃtico para la calidad de producto software, por lo tanto, exige una creciente demanda en la mejora de la efectividad y cumplimiento de las tareas que la componen, es ahà donde el uso de métodos y principios de gestión de conocimiento se convierte en la base para gestionarla.
Con base en este argumento, se indagan los desafÃos de los modelos de gestión de conocimiento existentes en el domino de la calidad de software para identificar las falencias de los modelos existentes y a partir de estas, proponer una solución para la ingenierÃa de software en el ámbito de la gestión de conocimiento, basado en la utilización de metodologÃas ontológicas en el dominio de la fase de pruebas.Workshop: WIS – IngenierÃa de SoftwareRed de Universidades con Carreras en Informátic
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