Automation of the Continuous Integration (CI) - Continuous Delivery/Deployment (CD) Software Development

Continuous Integration (CI) is a practice in software development where developers periodically merge code changes in a central shared repository, after which automatic versions and tests are executed. CI entails an automation component (the target of this project) and a cultural one, as developers have to learn to integrate code periodically. The main goal of CI is to reduce the time to feedback over the software integration process, allowing to locate and fix bugs more easily and quickly, thus enhancing it quality while reducing the time to validate and publish new soIn traditional software development, where teams of developers worked on the same project in isolation, often led to problems integrating the resulting code. Due to this isolation, the project was not deliverable until the integration of all its parts, which was tedious and generated errors. The Continuous Integration (CI ) emerged as a practice to solve the problems of traditional methodology, with the aim of improving the quality of the code. This thesis sets out what is it and how Continuous Integration is achieved, the principles that makes it as effective as possible and the processes that follow as a consequence, to thus introduce the context of its objective: the creation of a system that automates the start-up and set-up of an environment to be able to apply the methodology of continuous integration

Explaining global increases in water use efficiency: why have we overestimated responses to rising atmospheric CO(2) in natural forest ecosystems?

BackgroundThe analysis of tree-ring carbon isotope composition (δ(13)C) has been widely used to estimate spatio-temporal variations in intrinsic water use efficiency (iWUE) of tree species. Numerous studies have reported widespread increases in iWUE coinciding with rising atmospheric CO(2) over the past century. While this could represent a coherent global response, the fact that increases of similar magnitude were observed across biomes with no apparent effect on tree growth raises the question of whether iWUE calculations reflect actual physiological responses to elevated CO(2) levels.Methodology/resultsHere we use Monte Carlo simulations to test if an artifact of calculation could explain observed increases in iWUE. We show that highly significant positive relationships between iWUE and CO(2) occur even when simulated data (randomized δ(13)C values spanning the observed range) are used in place of actual tree-ring δ(13)C measurements. From simulated data sets we calculated non-physiological changes in iWUE from 1900 to present and across a 4000 m altitudinal range. This generated results strikingly similar to those reported in recent studies encompassing 22 species from tropical, subtropical, temperate, boreal and mediterranean ecosystems. Only 6 of 49 surveyed case studies showed increases in iWUE significantly higher than predicted from random values.Conclusions/significanceOur results reveal that increases in iWUE estimated from tree-ring δ(13)C occur independently of changes in (13)C discrimination that characterize physiological responses to elevated CO(2). Due to a correlation with CO(2) concentration, which is used as an independent factor in the iWUE calculation, any tree-ring δ(13)C data set would inevitably generate increasing iWUE over time. Therefore, although consistent, previously reported trends in iWUE do not necessarily reflect a coherent global response to rising atmospheric CO(2). We discuss the significance of these findings and suggest ways to distinguish real from artificial responses in future studies

Planificación óptima de datacenters desagregados: Diseño, implementación y evaluación de técnicas para la planificación óptima de Datacenters virtuales (VDC) en entornos de Datacenters desagregados interconectados con redes ópticas

Veure document adjunt.Traditional DCs (Data Center) can suffer from computing resource underutilization due to the constrained capacity of server units. To overcome these limitations, the disaggregated DC paradigm has been recently introduced. Thanks to resource disaggregation, it is possible to allocate the exact amount of resources needed to provision a VDC (Virtual Data Center) instance. In this project, we focus on the static planning of an all-optical disaggregated DC infrastructure in support of a known set of VDC instances to be deployed on top of a shared physical infrastructure. To this end, we provide optimal and sub-optimal techniques to determine the necessary capacity (both in terms of computing and network resources) required to support the demand set. In this study we show how disaggregated DC architectures can help on reducing the amount of computing resources needed when allocating VDC instances on top of a shared physical infrastructure. Around 46% average reductions can be experimented for fairly balanced Virtual Machine (VM) profiles while the reductions can increase up to 60% in the case of highly specialized VMs. Such results indicate that disaggregated DCs can overcome the limitations of current architectures in regards of efficient computing resource utilization, pleading for their adoption in future DC architectures.Los DCs (Data Center) tradicionales no aprovechan al máximo sus recursos debido a la restricción de capacidad de sus servidores. Para mejorar esta limitación, el paradigma de DC desagregado ha sido introducido recientemente. Gracias a la desagregación de los recursos, es posible asignar exactamente los recursos necesarios para aprovisionar a una instancia VDC (Virtual Data Center). En este proyecto nos centramos en la planificación estática de una infraestructura de DC desagregado puramente óptica siendo conocido el conjunto de VDCs que tienen que ser desplegadas. En este contexto, proporcionamos técnicas óptimas y sub-óptimas para determinar las necesidades de capacidad (tanto en término de recursos computacionales como de red) se requieren para satisfacer estas demandas. En este estudio hemos mostrado como las arquitecturas de DC desagregado pueden ayudar a la reducción de recursos computacionales necesarios para albergar instancias VDC en la infraestructura física. Alrededor de un 46% de reducciones promedio pueden ser experimentadas en perfiles de VM (Máquinas Virtuales) balanceadas, mientras que estas reducciones pueden llegar hasta al 60% en el caso de VMs especializadas. Estos resultados nos indican que los DCs desagregados pueden sobreponerse a las limitaciones de las arquitecturas actuales en términos de utilizar eficientemente los recursos computacionales, esperando su adopción en futuras arquitecturas DC.Els DCs (Data Center) tradicionals no aprofiten al màxim els seus recursos a causa de la restricció de capacitat dels seus servidors. Per millorar aquesta limitació, el paradigma de DC desagregat ha estat introduït recentment. Gràcies a la desagregació dels recursos, és possible assignar exactament els recursos necessaris per aprovisionar una instància VDC (Virtual Data Center). En aquest projecte ens centrem a la planificació estàtica d'una infraestructura de DC desagregat totalment òptica sent conegut el conjunt de VDCs que han de ser desplegades. En aquest context, proporcionem tècniques òptimes i sub-òptimes per determinar les necessitats de capacitat (tant en termes de recursos computacionals com de xarxa) que es requereixen per satisfer aquestes demandes. En aquest estudi hem mostrat com les arquitectures DC desagregades poden ajudar a la reducció de recursos computacionals necessaris per albergar instàncies VDC en la infraestructura física. Al voltant d'un 46% de reduccions de mitjana poden ser experimentades en perfils de VM (Màquines Virtuals) balancejades, mentre que aquestes reduccions poden arribar fins al 60% en el cas de VMs especialitzades. Aquests resultats ens indiquen que els DCs desagregats poden sobreposar-se a les limitacions de les arquitectures actuals en termes d'utilitzar eficientment els recursos computacionals, esperant la seva adopció en futures arquitectures DC

Optimal VDC service provisioning in optically interconnected disaggregated data centers

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Virtual data center (VDC) is a key service in modern data center (DC) infrastructures. However, the rigid architecture of traditional servers inside DCs may lead to blocking situations when deploying VDC instances. To overcome this problem, the disaggregated DC paradigm is introduced. In this letter, we present an integer linear programming (ILP) formulation to optimally allocate VDC requests on top of an optically interconnected disaggregated DC infrastructure, aiming to quantify the benefits that such an architecture can bring when compared with traditional server-centric DCs. Moreover, a lightweight simulated annealing-based heuristic is provided for the scenarios where the ILP scalability is challenged. The obtained numerical results reveal the substantial benefits yielded by the resource disaggregation paradigm.Peer ReviewedPostprint (author's final draft

RASPODJELA I SASTAV POPULACIJE KUNJKE Arca noae U PAŠMANSKOM KANALU

Noah’s Ark shell Arca noae is an edible bivalve that is commercially exploited in the eastern Adriatic and is harvested primarily by SCUBA divers. There are no reliable data catch statistics data for this species nor there any data on distribution and population biology of exploited stocks, all of which are crucial for establishing sustainable level of exploitation. The objective of this research was to determine distribution and population structure of A. noae in one of the harvesting area — Pašman channel. Study was conducted in May 2008 using SCUBA visual census method at six transects. Although there are no previous data on distribution of A. noae in this area, low population density, length frequency distribution with domination of individuals smaller than 5 cm and sex ratio analysis all indicate that present level of harvesting is unsustainable.Kunjka (Arca noae) jestivi je školjkaš koji se komercijalno sakuplja u istočnom dijelu Jadrana, primarno metodom autonomnog ronjenja. Nema pouzdanih statističkih podataka o sakupljanju ove vrste kao ni podataka o raspodjeli i sastavu populacija iskorištavanih »stokova«, što je nužno za uspostavu održive razine eksploatacije. Cilj je ovog istraživanja bio određivanje raspodjele i sastava populacije vrste A. noae u jednom od područja sakupljanja — Pašmanskom kanalu. Istraživanje je provedeno u svibnju 2008. godine metodom vizualnog cenzusa na šest profila autonomnog ronjenja. Iako nema prethodnih podataka o raspodjeli vrste A. noae na ovom području, niska gustoća naseljenosti, histogram dužinskih frekvencija na kojem prevladavaju jedinke manje od 5 cm i omjer spolova upućuju na to da je postojeća razina eksploatacije neodrživa