Software Engineering Productivity

2011 ◽  
Vol 2 (1) ◽  
pp. 37-47 ◽  
Author(s):  
Adrián Hernández-López ◽  
Ricardo Colomo-Palacios ◽  
Ángel García-Crespo ◽  
Fernando Cabezas-Isla
Keyword(s):  
Software Engineering ◽  
Influencing Factors ◽  
State Of The Art ◽  
Research Area ◽  
Research Community ◽  
Productivity Analysis ◽  
Shed Light ◽  
Inputs And Outputs

Software engineering productivity has been widely studied, but there are many issues that remain unsolved. Interesting works related to new metrics and more replications of past productivity analysis have emerged, however, in order to fulfill these unsolved issues, a consensus about influencing factors and well recognized and useful sets of inputs and outputs for using in measurements must be reached. In this regard, a clear state of the art may shed light on further research in software engineering productivity, which remains a promising research area. In this paper, general concepts of software engineering productivity along with general issues and recent challenges that need further attention from the research community are presented.

Software Engineering Productivity

2012 ◽  
pp. 69-79
Author(s):  
Adrián Hernández-López ◽  
Ricardo Colomo-Palacios ◽  
Ángel García-Crespo ◽  
Fernando Cabezas-Isla
Keyword(s):  
Software Engineering ◽  
Influencing Factors ◽  
State Of The Art ◽  
Research Area ◽  
Research Community ◽  
Productivity Analysis ◽  
Shed Light ◽  
Inputs And Outputs

Software engineering productivity has been widely studied, but there are many issues that remain unsolved. Interesting works related to new metrics and more replications of past productivity analysis have emerged, however, in order to fulfill these unsolved issues, a consensus about influencing factors and well recognized and useful sets of inputs and outputs for using in measurements must be reached. In this regard, a clear state of the art may shed light on further research in software engineering productivity, which remains a promising research area. In this paper, general concepts of software engineering productivity along with general issues and recent challenges that need further attention from the research community are presented.

scholarly journals Reactive Balance Control for Legged Robots under Visco-Elastic Contacts

2020 ◽  
Vol 11 (1) ◽  
pp. 353
Author(s):  
Thomas Flayols ◽  
Andrea Del Prete ◽  
Majid Khadiv ◽  
Nicolas Mansard ◽  
Ludovic Righetti
Keyword(s):  
Inverse Dynamics ◽  
State Of The Art ◽  
Balance Control ◽  
Contact Stiffness ◽  
Poor Performance ◽  
Admittance Control ◽  
Inverse Dynamics Control ◽  
Rigid Contact ◽  
Reactive Balance ◽  
Shed Light

Contacts between robots and environment are often assumed to be rigid for control purposes. This assumption can lead to poor performance when contacts are soft and/or underdamped. However, the problem of balancing on soft contacts has not received much attention in the literature. This paper presents two novel approaches to control a legged robot balancing on visco-elastic contacts, and compares them to other two state-of-the-art methods. Our simulation results show that performance heavily depends on the contact stiffness and the noises/uncertainties introduced in the simulation. Briefly, the two novel controllers performed best for soft/medium contacts, whereas “inverse-dynamics control under rigid-contact assumptions” was the best one for stiff contacts. Admittance control was instead the most robust, but suffered in terms of performance. These results shed light on this challenging problem, while pointing out interesting directions for future investigation.

scholarly journals Global and Latin American female participation in evidence-based software engineering: a systematic mapping study

2021 ◽  
Vol 27 (1) ◽  
Author(s):  
Katia Romero Felizardo ◽  
Amanda Möhring Ramos ◽  
Claudia de O. Melo ◽  
Érica Ferreira de Souza ◽  
Nandamudi L. Vijaykumar ◽  
...  
Keyword(s):  
Software Engineering ◽  
Latin American ◽  
Gender Issue ◽  
Research Area ◽  
Systematic Mapping Study ◽  
Evidence Based ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Participation Of Women ◽  
New Generation

Abstract Context While the digital economy requires a new generation of technology for scientists and practitioners, the software engineering (SE) field faces a gender crisis. SE research is a global enterprise that requires the participation of both genders for the advancement of science and evidence-based practice. However, women across the world tend to be significantly underrepresented in such research, receiving less funding and less participation, frequently, than men as authors in research publications. Data about this phenomenon is still sparse and incomplete; particularly in evidence-based software engineering (EBSE), there are no studies that analyze the participation of women in this research area. Objective The objective of this work is to present the results of a systematic mapping study (SM) conducted to collect and evaluate evidence on female researchers who have contributed to the area of EBSE. Method Our SM was performed by manually searching studies in the major conferences and journals of EBSE. We identified 981 studies and 183 were authored/co-authored by women and, therefore, included. Results Contributions from women in secondary studies have globally increased over the years, but it is still concentrated in European countries. Additionally, collaboration among research groups is still fragile, based on a few women as a bridge. Latin American researchers contribute a great deal to the field, despite they do not collaborate as much within their region. Conclusions The findings from this study are expected to be aggregated to the existing knowledge with respect to women’s contribution to the EBSE area. We expect that our results bring up a reflection on the gender issue and motivate actions and policies to attract female researchers to this area.

scholarly journals Technology-enhanced and game based learning for children with special needs: a systematic mapping study

2021 ◽  
Author(s):  
Jose A. Gallud ◽  
Monica Carreño ◽  
Ricardo Tesoriero ◽  
Andrés Sandoval ◽  
María D. Lozano ◽  
...  
Keyword(s):  
Special Needs ◽  
State Of The Art ◽  
Research Community ◽  
Systematic Mapping Study ◽  
Children With Special Needs ◽  
Game Based Learning ◽  
Mapping Study ◽  
Systematic Mapping ◽  
Wide Range ◽  
Research Questions

AbstractTechnology-based education of children with special needs has become the focus of many research works in recent years. The wide range of different disabilities that are encompassed by the term “special needs”, together with the educational requirements of the children affected, represent an enormous multidisciplinary challenge for the research community. In this article, we present a systematic literature review of technology-enhanced and game-based learning systems and methods applied on children with special needs. The article analyzes the state-of-the-art of the research in this field by selecting a group of primary studies and answering a set of research questions. Although there are some previous systematic reviews, it is still not clear what the best tools, games or academic subjects (with technology-enhanced, game-based learning) are, out of those that have obtained good results with children with special needs. The 18 articles selected (carefully filtered out of 614 contributions) have been used to reveal the most frequent disabilities, the different technologies used in the prototypes, the number of learning subjects, and the kind of learning games used. The article also summarizes research opportunities identified in the primary studies.

scholarly journals X-Mark: a benchmark for node-attributed community discovery algorithms

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Salvatore Citraro ◽  
Giulio Rossetti
Keyword(s):  
State Of The Art ◽  
Graph Clustering ◽  
Clustering Methods ◽  
Community Discovery ◽  
Attributed Graphs ◽  
Node Labels ◽  
Discovery Algorithms ◽  
Shed Light

AbstractGrouping well-connected nodes that also result in label-homogeneous clusters is a task often known as attribute-aware community discovery. While approaching node-enriched graph clustering methods, rigorous tools need to be developed for evaluating the quality of the resulting partitions. In this work, we present X-Mark, a model that generates synthetic node-attributed graphs with planted communities. Its novelty consists in forming communities and node labels contextually while handling categorical or continuous attributive information. Moreover, we propose a comparison between attribute-aware algorithms, testing them against our benchmark. Accordingly to different classification schema from recent state-of-the-art surveys, our results suggest that X-Mark can shed light on the differences between several families of algorithms.

scholarly journals Preface to the April 2018 Issue including selected works from CIbSE 2017 and LACLO 2016

2018 ◽  
Vol 21 (1) ◽  
Author(s):  
Héctor Cancela ◽  
Isabel Brito ◽  
Luca Cernuzzi ◽  
Marcela Genero ◽  
Jesús García Molina ◽  
...  
Keyword(s):  
Costa Rica ◽  
Software Engineering ◽  
Latin American ◽  
Buenos Aires ◽  
Review Paper ◽  
State Of The Art ◽  
Contextual Information ◽  
Learning Objects ◽  
The State ◽  
San Jose

This issue of the CLEIej consists of three main parts: i) a review paper on the state of the art of how contextual information extracted from a user task can help to improve searches for contents relevant to this task; ii) extended and revised versions of Selected Papers (which correspond to the second and third best paper from each track) presented at the XX Ibero-American Conference on Software Engineering (CIbSE 2017), which took place in Buenos Aires, Argentina, in May 2017; and, iii) extended and revised versions of selected papers from LACLO 2016, the XI Latin American Conference on Learning Objects and Technology, which took place in San José, Costa Rica, in October 2016.

scholarly journals Electronic records management – a state of the art review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Babatunde Oladejo ◽  
Sunčica Hadžidedić
Keyword(s):  
State Of The Art ◽  
Academic Research ◽  
Research Area ◽  
Electronic Records ◽  
Records Management ◽  
Content Type ◽  
Search Results ◽  
Search Tool ◽  
Research And Education ◽  
Electronic Records Management

Purpose This paper aims to examine the state of the art in electronic records management (ERM) with the goal of identifying the prevailing research topics, gaps and issues in the field. Design/methodology/approach First, a wide search was performed on academic research databases, limited to the period between 2008–2018. Second, the search results were reviewed for relevance and duplicates. Finally, the study sources were checked against the list of journals and conferences ranked by computing research and education and JourQual. The final sample of 55 selected studies was analyzed in depth. Findings ERM has lost some research momentum due to being deeply embedded in affiliate information systems areas and the changing records management landscape. Additionally, the requirement models specified by Governmental/National Archives might have constrained technology innovation in ERM. A lack of application was identified for the social media research area. Research limitations/implications Limitations were encountered in available search tool functionality and keyword confusion leading to inflated search results. While effort has been made to obtain optimal search results, some relevant articles may have been omitted. Originality/value The last ERM state-of-the-art review was in 1997. A lot has changed since then. This paper will help researchers understand the current state of ERM research, its understudied areas and identify gaps for future studies.

scholarly journals Learning Long- and Short-Term User Literal-Preference with Multimodal Hierarchical Transformer Network for Personalized Image Caption

2020 ◽  
Vol 34 (05) ◽  
pp. 9571-9578 ◽  
Author(s):  
Wei Zhang ◽  
Yue Ying ◽  
Pan Lu ◽  
Hongyuan Zha
Keyword(s):  
State Of The Art ◽  
Natural Extension ◽  
Target Image ◽  
Short Term ◽  
Image Representations ◽  
High Level ◽  
Image Descriptions ◽  
Shed Light ◽  
Image Caption

Personalized image caption, a natural extension of the standard image caption task, requires to generate brief image descriptions tailored for users' writing style and traits, and is more practical to meet users' real demands. Only a few recent studies shed light on this crucial task and learn static user representations to capture their long-term literal-preference. However, it is insufficient to achieve satisfactory performance due to the intrinsic existence of not only long-term user literal-preference, but also short-term literal-preference which is associated with users' recent states. To bridge this gap, we develop a novel multimodal hierarchical transformer network (MHTN) for personalized image caption in this paper. It learns short-term user literal-preference based on users' recent captions through a short-term user encoder at the low level. And at the high level, the multimodal encoder integrates target image representations with short-term literal-preference, as well as long-term literal-preference learned from user IDs. These two encoders enjoy the advantages of the powerful transformer networks. Extensive experiments on two real datasets show the effectiveness of considering two types of user literal-preference simultaneously and better performance over the state-of-the-art models.

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