Exploiting Visual Languages Generation and UML Meta Modeling to Construct Meta-CASE Workbenches

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Exploiting XPG for Visual Languages Definition, Analysis and Development

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Using the GPU to Green an Intensive and Massive Computation System

In this paper, we present the early results of an ongoing project aimed at giving an existing software system a more eco-sustainable lease of life. We defined a strategy and a process for migrating a subject system that performs intensive and massive computation to a Graphics Processing Unit (GPU) based architecture. We validated our solutions on a software system for path finding robot simulations. An initial comparison on the energy consumption of the original system and the greened one has been also executed. The obtained results suggested that the application of our solution produced more eco-sustainable software

Assessing the Effectiveness of Sequence Diagrams in the Comprehension of Functional Requirements: Results from a Family of Five Experiments

Modeling is a fundamental activity within the requirements engineering process and concerns the construction of abstract descriptions of requirements that are amenable to interpretation and validation. The choice of a modeling technique is critical whenever it is necessary to discuss the interpretation and validation of requirements. This is particularly true in the case of functional requirements and stakeholders with divergent goals and different backgrounds and experience. This paper presents the results of a family of experiments conducted with students and professionals to investigate whether the comprehension of functional requirements is influenced by the use of dynamic models that are represented by means of the UML sequence diagrams. The family contains five experiments performed in different locations and with 112 participants of different abilities and levels of experience with the UML. The results show that sequence diagrams improve the comprehension of the modeled functional requirements in the case of high ability and more experienced participants

Assessing the Usability of a Visual Tool for the definition of E-learning Processes

In this paper, we present a usability study aiming at assessing a visual language-based tool for developing adaptive e-learning processes. The tool implements the adaptive self-consistent learning object SET (ASCLO-S) visual language, a special case of flow diagrams, to be used by instructional designers to define classes of learners through stereotypes and to specify the more suited adaptive learning process for each class of learners. The usability study is based on the combined use of two techniques: a questionnaire-based survey and an empirical analysis. The survey has been used to achieve feedbacks from the subjects' point of view. In particular, it has been useful to capture the perceived usability of the subjects. The outcomes show that both the proposed visual notation and the system prototype are suitable for instructional designers with or without experience on the computer usage and on tools for defining e-learning processes. This result is further confirmed by the empirical analysis we carried out by analysing the correlation between the effort to develop adaptive e-learning processes and some measures suitable defined for those processes. Indeed, the empirical analysis revealed that the effort required to model e-learning processes is not influenced by the experience of the instructional designer with the use of e-learning tools, but it only depends on the size of the developed process

Using tabu search to configure support vector regression for effort estimation

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Do software models based on the UML aid in source-code comprehensibility? Aggregating evidence from 12 controlled experiments

In this paper, we present the results of long-term research conducted in order to study the contribution made by software models based on the Unified Modeling Language (UML) to the comprehensibility of Java source-code deprived of comments. We have conducted 12 controlled experiments in different experimental contexts and on different sites with participants with different levels of expertise (i.e., Bachelor’s, Master’s, and PhD students and software practitioners from Italy and Spain). A total of 333 observations were obtained from these experiments. The UML models in our experiments were those produced in the analysis and design phases. The models produced in the analysis phase were created with the objective of abstracting the environment in which the software will work (i.e., the problem domain), while those produced in the design phase were created with the goal of abstracting implementation aspects of the software (i.e., the solution/application domain). Source-code comprehensibility was assessed with regard to correctness of understanding, time taken to accomplish the comprehension tasks, and efficiency as regards accomplishing those tasks. In order to study the global effect of UML models on source-code comprehensibility, we aggregated results from the individual experiments using a meta-analysis. We made every effort to account for the heterogeneity of our experiments when aggregating the results obtained from them. The overall results suggest that the use of UML models affects the comprehensibility of source-code, when it is deprived of comments. Indeed, models produced in the analysis phase might reduce source-code comprehensibility, while increasing the time taken to complete comprehension tasks. That is, browsing source code and this kind of models together negatively impacts on the time taken to complete comprehension tasks without having a positive effect on the comprehensibility of source code. One plausible justification for this is that the UML models produced in the analysis phase focus on the problem domain. That is, models produced in the analysis phase say nothing about source code and there should be no expectation that they would, in any way, be beneficial to comprehensibility. On the other hand, UML models produced in the design phase improve source-code comprehensibility. One possible justification for this result is that models produced in the design phase are more focused on implementation details. Therefore, although the participants had more material to read and browse, this additional effort was paid back in the form of an improved comprehension of source code

The Importance of the Correlation in Crossover Experiments

Context: In empirical software engineering, crossover designs are popular for experiments comparing software engineering techniques that must be undertaken by human participants. However, their value depends on the correlation ( r ) between the outcome measures on the same participants. Software engineering theory emphasizes the importance of individual skill differences, so we would expect the values of r to be relatively high. However, few researchers have reported the values of r . Goal: To investigate the values of r found in software engineering experiments. Method: We undertook simulation studies to investigate the theoretical and empirical properties of r . Then we investigated the values of r observed in 35 software engineering crossover experiments. Results: The level of r obtained by analysing our 35 crossover experiments was small. Estimates based on means, medians, and random effect analysis disagreed but were all between 0.2 and 0.3. As expected, our analyses found large variability among the individual r estimates for small sample sizes, but no indication that r estimates were larger for the experiments with larger sample sizes that exhibited smaller variability. Conclusions: Low observed r values cast doubts on the validity of crossover designs for software engineering experiments. However, if the cause of low r values relates to training limitations or toy tasks, this affects all Software Engineering (SE) experiments involving human participants. For all human-intensive SE experiments, we recommend more intensive training and then tracking the improvement of participants as they practice using specific techniques, before formally testing the effectiveness of the techniques

An aphid RNA transcript migrates systemically within plants and is a virulence factor

Aphids are sap-feeding insects that colonize a broad range of plant species and often cause feeding damage and transmit plant pathogens, including bacteria, viruses, and viroids. These insects feed from the plant vascular tissue, predominantly the phloem. However, it remains largely unknown how aphids, and other sap-feeding insects, establish intimate long-term interactions with plants. To identify aphid virulence factors, we took advantage of the ability of the green peach aphid Myzus persicae to colonize divergent plant species. We found that a M. persicae clone of near-identical females established stable colonies on nine plant species of five representative plant eudicot and monocot families that span the angiosperm phylogeny. Members of the novel aphid gene family Ya are differentially expressed in aphids on the nine plant species and are coregulated and organized as tandem repeats in aphid genomes. Aphids translocate Ya transcripts into plants, and some transcripts migrate to distal leaves within several plant species. RNAi-mediated knockdown of Ya genes reduces M. persicae fecundity, and M. persicae produces more progeny on transgenic plants that heterologously produce one of the systemically migrating Ya transcripts as a long noncoding (lnc) RNA. Taken together, our findings show that beyond a range of pathogens, M. persicae aphids translocate their own transcripts into plants, including a Ya lncRNA that migrates to distal locations within plants, promotes aphid fecundity, and is a member of a previously undescribed host-responsive aphid gene family that operate as virulence factors

The Usability of E-learning Platforms in Higher Education: A Systematic Mapping Study

The use of e-learning in higher education has increased significantly in recent years, which has led to several studies being conducted to investigate the usability of the platforms that support it. A variety of different usability evaluation methods and attributes have been used, and it has therefore become important to start reviewing this work in a systematic way to determine how the field has developed in the last 15 years. This paper describes a systematic mapping study that performed searches on five electronic libraries to identify usability issues and methods that have been used to evaluate e-learning platforms. Sixty-one papers were selected and analysed, with the majority of studies using a simple research design reliant on questionnaires. The usability attributes measured were mostly related to effectiveness, satisfaction, efficiency, and perceived ease of use. Furthermore, several research gaps have been identified and recommendations have been made for further work in the area of the usability of online learning