11,049 research outputs found

    Introducing Energy Efficiency into SQALE

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    Energy Efficiency is becoming a key factor in software development, given the sharp growth of IT systems and their impact on worldwide energy consumption. We do believe that a quality process infrastructure should be able to consider the Energy Efficiency of a system since its early development: for this reason we propose to introduce Energy Efficiency into the existing quality models. We selected the SQALE model and we tailored it inserting Energy Efficiency as a sub-characteristic of efficiency. We also propose a set of six source code specific requirements for the Java language starting from guidelines currently suggested in the literature. We experienced two major challenges: the identification of measurable, automatically detectable requirements, and the lack of empirical validation on the guidelines currently present in the literature and in the industrial state of the practice as well. We describe an experiment plan to validate the six requirements and evaluate the impact of their violation on Energy Efficiency, which has been partially proved by preliminary results on C code. Having Energy Efficiency in a quality model and well verified code requirements to measure it, will enable a quality process that precisely assesses and monitors the impact of software on energy consumptio

    Developments and Development Directions of Electronic Trade Platforms in US and European Agri-Food Markets: Impact on Sector Organization

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    Electronic trade platforms support trading transactions between enterprises. They have entered the business landscape including the agri-food sector only a few years ago. However, there already have been dramatic changes in the agri-food sectorÂ’s platform infrastructures. This paper analyzes developments in electronic trade platform infrastructures in the agri-food sector of the US and Europe between 2000 and 2002 and identifies development strategies of successful platforms. Of 85 platforms in existence in the year 2000, only 25 remained active in 2002. But there are still market entries of new platforms and existing platforms form various types of partnerships. The analysis could identify a range of strategic development lines of successful platforms. Initiating cooperation with other platforms on the use of specific features and the development and use of standards, gaining support by major market participants, the improvement of trading functionalities and the expansion of value-added services are the primary lines of development and evolvement of platforms. Platform evolvement tendencies and the present occurrence of the trade platform infrastructure allow for projecting the emergence of an agri-food sector with embedded, interconnected e-commerce infrastructure or mega-hub leading towards a more networked agri-food industry.Electronic commerce, Electronic trade platforms, Agri-food markets, Agribusiness, Marketing,

    Towards Automated Performance Bug Identification in Python

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    Context: Software performance is a critical non-functional requirement, appearing in many fields such as mission critical applications, financial, and real time systems. In this work we focused on early detection of performance bugs; our software under study was a real time system used in the advertisement/marketing domain. Goal: Find a simple and easy to implement solution, predicting performance bugs. Method: We built several models using four machine learning methods, commonly used for defect prediction: C4.5 Decision Trees, Na\"{\i}ve Bayes, Bayesian Networks, and Logistic Regression. Results: Our empirical results show that a C4.5 model, using lines of code changed, file's age and size as explanatory variables, can be used to predict performance bugs (recall=0.73, accuracy=0.85, and precision=0.96). We show that reducing the number of changes delivered on a commit, can decrease the chance of performance bug injection. Conclusions: We believe that our approach can help practitioners to eliminate performance bugs early in the development cycle. Our results are also of interest to theoreticians, establishing a link between functional bugs and (non-functional) performance bugs, and explicitly showing that attributes used for prediction of functional bugs can be used for prediction of performance bugs

    An Efficient Monte Carlo-based Probabilistic Time-Dependent Routing Calculation Targeting a Server-Side Car Navigation System

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    Incorporating speed probability distribution to the computation of the route planning in car navigation systems guarantees more accurate and precise responses. In this paper, we propose a novel approach for dynamically selecting the number of samples used for the Monte Carlo simulation to solve the Probabilistic Time-Dependent Routing (PTDR) problem, thus improving the computation efficiency. The proposed method is used to determine in a proactive manner the number of simulations to be done to extract the travel-time estimation for each specific request while respecting an error threshold as output quality level. The methodology requires a reduced effort on the application development side. We adopted an aspect-oriented programming language (LARA) together with a flexible dynamic autotuning library (mARGOt) respectively to instrument the code and to take tuning decisions on the number of samples improving the execution efficiency. Experimental results demonstrate that the proposed adaptive approach saves a large fraction of simulations (between 36% and 81%) with respect to a static approach while considering different traffic situations, paths and error requirements. Given the negligible runtime overhead of the proposed approach, it results in an execution-time speedup between 1.5x and 5.1x. This speedup is reflected at infrastructure-level in terms of a reduction of around 36% of the computing resources needed to support the whole navigation pipeline

    Ancient and historical systems

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