Incorporating Agile with MDA Case Study: Online Polling System

Nowadays agile software development is used in greater extend but for small organizations only, whereas MDA is suitable for large organizations but yet not standardized. In this paper the pros and cons of Model Driven Architecture (MDA) and Extreme programming have been discussed. As both of them have some limitations and cannot be used in both large scale and small scale organizations a new architecture has been proposed. In this model it is tried to opt the advantages and important values to overcome the limitations of both the software development procedures. In support to the proposed architecture the implementation of it on Online Polling System has been discussed and all the phases of software development have been explained.Comment: 14 pages,1 Figure,1 Tabl

Learning to Infer Graphics Programs from Hand-Drawn Images

We introduce a model that learns to convert simple hand drawings into graphics programs written in a subset of \LaTeX. The model combines techniques from deep learning and program synthesis. We learn a convolutional neural network that proposes plausible drawing primitives that explain an image. These drawing primitives are like a trace of the set of primitive commands issued by a graphics program. We learn a model that uses program synthesis techniques to recover a graphics program from that trace. These programs have constructs like variable bindings, iterative loops, or simple kinds of conditionals. With a graphics program in hand, we can correct errors made by the deep network, measure similarity between drawings by use of similar high-level geometric structures, and extrapolate drawings. Taken together these results are a step towards agents that induce useful, human-readable programs from perceptual input

Software languages engineering: experimental evaluation

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia InformáticaDomain-Specific Languages (DSLs) are programming languages that offer, through appropriate notation and abstraction, still enough an expressive control over a particular problem domain for more restricted use. They are expected to contribute with an enhancement of productivity, reliability, maintainability and portability, when compared with General Purpose Programming Languages (GPLs). However, like in any Software Product without passing by all development stages namely Domain Analysis, Design, Implementation and Evaluation, some of the DSLs’ alleged advantages may be impossible to be achieved with a significant level of satisfaction. This may lead to the production of inadequate or inefficient languages. This dissertation is focused on the Evaluation phase. To characterize DSL community commitment concerning Evaluation, we conducted a systematic review. The review covered publications in the main fora dedicated to DSLs from 2001 to 2008, and allowed to analyse and classify papers with respect to the validation efforts conducted by DSLs’ producers, where have been observed a reduced concern to this matter. Another important outcome that has been identified is the absence of a concrete approach to the evaluation of DSLs, which would allow a sound assessment of the actual improvements brought by the usage of DSLs. Therefore, the main goal of this dissertation concerns the production of a Systematic Evaluation Methodology for DSLs. To achieve this objective, has been carried out the major techniques used in Experimental Software Engineering and Usability Engineering context. The proposed methodology was validated with its use in several case studies, whereupon DSLs evaluation has been made in accordance with this methodology

Model Variations and Automated Refinement of Domain-Specific Modeling Languages for Robot-Motion Control

This paper presents an approach to handling frequent variations of modeling languages and models. The approach is based on Domain-Specific Modeling and linking of modeling tools with adaptive Run-Time Systems. The applicability of our solution is illustrated on an example of domain-specific languages for robot control. Special attention was given to the following problems: 1) model-level debugging; 2) performing fast transformation of models to native code for various hardware platforms and operating systems; and 3) specification of views and view-based generation of applications for validation of meta-models, models, and generated code. The feedback for automated refinement of models and meta-models is provided by a custom adaptive Run-Time System. For the purpose of synchronizing models, meta-models, and the target Run-Time System, we introduce action reports, which allow model-level debugging. In order to simplify handling of frequent model variations, we have introduced the linguistic concept of a modifier