Formalizing the software development process

Object-oriented software development process, such as the Unified Process [Jacobson 99], Catalysis [D´Souza 98] and Fusion [Coleman 94] among others, is a set of activities needed to transform user’s requirements into a software system. A software development process typically consists of a set of software development artifacts together with a graph of tasks and activities. Software artifacts are the products resulting from software development, for example, a use case model, a class model or source code. Tasks are small behavioral units that usually results in a software artifact. Examples of tasks are construction of a use case model, construction of a class model and writing code. Activities (or workflows) are units that are larger than a task. Activities generally include several tasks and software artifacts. Examples of activities are requirements, analysis, design and implementation.\nModern software development processes are iterative and incremental, they repeat over a series of iterations making up the life cycle of a system. Each iteration takes place over time and it consists of one pass through the requirements, analysis, design, implementation and test activities, building a number of different artifacts. All these artifacts are not independent. They are related to each other, they are semantically overlapping and together represent the system as a whole. Elements in one artifact have trace dependencies to other artifacts.\nFor instance, a use case (in the use-case model) can be traced to a collaboration (in the design model) representing its realization.Eje: Ingeniería del Softwar

Model-based approaches to support process improvement in complex product development

The performance of product development processes is important to the commercial success of new products. The improvement of these processes is thus a strategic imperative for many engineering companies — the aero-engine is one example of a complex product for which market pressures necessitate ever-shorter development times. This thesis argues that process modelling and simulation can support the improvement of complex product development processes. A literature review identified that design process modelling is a well-established research area encompassing a diverse range of approaches. However, most existing tools and methods are not widely applied in industry. An extended case study was therefore conducted to explore the pragmatic utility of process modelling and simulation. It is argued that iteration is a key driver of design process behaviour which cannot be fully reflected in a mechanistic model. Understanding iteration can help select an appropriate representation for a given process domain and modelling objective. A model-based approach to improve the management of iterative design processes was developed. This approach shows that design process simulation models can support practice despite their limited fidelity. The modelling and simulation framework resulting from this work was enhanced for application to a wider range of process improvement activities. A robust and extensible software platform was also developed. The framework and software tool have made significant contribution to research projects investigating process redesign, process robustness and process optimisation. These projects are discussed to validate the framework and tool and to highlight their applicability beyond the original approach. The research results were disseminated in academia and industry — 72 copies of the software were distributed following requests in the first three months of its release

Formalizing the software development process

Object-oriented software development process, such as the Unified Process [Jacobson 99], Catalysis [D´Souza 98] and Fusion [Coleman 94] among others, is a set of activities needed to transform user’s requirements into a software system. A software development process typically consists of a set of software development artifacts together with a graph of tasks and activities. Software artifacts are the products resulting from software development, for example, a use case model, a class model or source code. Tasks are small behavioral units that usually results in a software artifact. Examples of tasks are construction of a use case model, construction of a class model and writing code. Activities (or workflows) are units that are larger than a task. Activities generally include several tasks and software artifacts. Examples of activities are requirements, analysis, design and implementation. Modern software development processes are iterative and incremental, they repeat over a series of iterations making up the life cycle of a system. Each iteration takes place over time and it consists of one pass through the requirements, analysis, design, implementation and test activities, building a number of different artifacts. All these artifacts are not independent. They are related to each other, they are semantically overlapping and together represent the system as a whole. Elements in one artifact have trace dependencies to other artifacts. For instance, a use case (in the use-case model) can be traced to a collaboration (in the design model) representing its realization.Eje: Ingeniería del SoftwareRed de Universidades con Carreras en Informática (RedUNCI

High-Dimensional Bayesian Geostatistics

With the growing capabilities of Geographic Information Systems (GIS) and user-friendly software, statisticians today routinely encounter geographically referenced data containing observations from a large number of spatial locations and time points. Over the last decade, hierarchical spatiotemporal process models have become widely deployed statistical tools for researchers to better understand the complex nature of spatial and temporal variability. However, fitting hierarchical spatiotemporal models often involves expensive matrix computations with complexity increasing in cubic order for the number of spatial locations and temporal points. This renders such models unfeasible for large data sets. This article offers a focused review of two methods for constructing well-defined highly scalable spatiotemporal stochastic processes. Both these processes can be used as "priors" for spatiotemporal random fields. The first approach constructs a low-rank process operating on a lower-dimensional subspace. The second approach constructs a Nearest-Neighbor Gaussian Process (NNGP) that ensures sparse precision matrices for its finite realizations. Both processes can be exploited as a scalable prior embedded within a rich hierarchical modeling framework to deliver full Bayesian inference. These approaches can be described as model-based solutions for big spatiotemporal datasets. The models ensure that the algorithmic complexity has $\sim n$ floating point operations (flops), where $n$ the number of spatial locations (per iteration). We compare these methods and provide some insight into their methodological underpinnings

IMPLEMENTASI JARINGAN SYARAF TIRUAN DALAM SISTEM PENDUKUNG KEPUTUSAN (SPK) UNTUK MEMILIH PERGURUAN TINGGI

This research is focusing on back-propagation algorithm with neural network that have to be implemented with MATLAB software. The data is observe directly and studying about university election by the graduate high school student. This research wants to find the direct problem, so it can be implemented with neural network by using back-propagation algorithm. This research using three (3) model of neural network back-propagation algorithm. From the data have been analyze with MATLAB software, the training convergence process stop at 5th iteration, last MSE = 1,01777. Meanwhile the testing convergence process stop at 5th iteration, with last MSE = 0,288833

Hot & Cold: The FINCH Thermal Simulator

Thermal modelling is an integral part of thesatellite design process. However, detailed simulations require high-fidelity models and resources that are not readily available in the preliminary design stage. To gain insight into the on-orbit temperature ranges and heatloads that FINCH, a 3U hyperspectral imaging CubeSat, will experience, a six-node numerical model was developed in MATLAB. This model was developed as an alternative to industry modelling software during preliminary design stages. The model: Allows teams to conduct rapid iteration of thermal design with reduced barrier to entry. Provides a platform to make informed decisions early in the design cycle. Encourages a first principles understanding of heat transfer and thermal modelling

Development of a Statistical Shape-Function Model of the Implanted Knee to Predict Joint Mechanics

Outcomes of total knee replacement are dependent on surgical technique, patient variability, and implant design. Non-optimal design choices may result in undesirable contact mechanics and joint kinematics. Specifically, the design process requires significant investments of time, software, and expertise for even a single iteration. Our objective was the development of a statistical shape-function model of a posterior stabilized knee implant to predict output mechanics in a resource efficient matter. Finite element methods were combined with design of experiments to produce predictive models relating nine implant design parameters to key outputs for a tibial-femoral joint performing a squat cycle