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Web services evolve over time to fix bugs or update and add new features. However, the design of the Web service's interface may become more complex when aggregating many unrelated operations in terms of context and functionalities. A possible solution is to refactor the Web services interface into different modules that help the user quickly identifying relevant operations. The most challenging issue...
The degree of homogeneity of statistical distributions among data sources is a critical issue when reusing data of Integrated Data Repositories (IDR). Evaluating this data source stability is of utmost importance in order to ensure a confident data reuse. This work tackles the task of discovering and classifying patterns among the statistical distributions of multiple sources in IDRs, by means of...
Because of the popularity of cloud computing, Cloud Service Providers (CSPs) can rent virtual machines (VMs) from Cloud Providers (CPs) conveniently. In our previous work, we proposed an autonomic and elastic resource scheduling framework, named AERS, which made full use of both proactive and reactive controllers in the field of dynamic resource provision and was integrated with an availability-aware...
The growing adoption of automated data collection systems in the transit industry, such as automated fare-collection (AFC) and automated vehicle location (AVL), is providing operators with extensive data about the state of the system and its usage by passengers. The paper proposes a framework for using automated data to support the various functions, both planning and real time, and demonstrates its...
Today's advanced driver assistance systems (ADAS) are increasingly becoming more complex. The next step in this direction is the development of automated driving systems. However, along with the complexity, the effort required for development and validation of these systems is increasing as well. In order to be able to master this complexity in terms of cost and time, simulations are being used more...
In this paper, a new method with visual saliency detection for image quality assessment (IQA) is proposed. Through the experiments in this paper, we have verified the proposed method can be effective than most others.
Due to the constant evolution of technology, each day brings new programming languages, development paradigms, and ways of evaluating processes. This is no different with source code metrics, where there is always new metric classes. To use a software metric to support decisions, it is necessary to understand how to perform the metric collection, calculation, interpretation, and analysis. The tasks...
Many service desk managers are struggling with the high turnover of service desk employees. Keeping the service desk job interesting and maintaining motivation is considered as a difficult task. In this study, we aim at exploring factors that affect the motivation and demotivation among IT service provider organizations' service desk employees. We shall explore how service desk staff see the concepts...
In this paper, we propose a new version of the LBRW (Learning based Random Walk), LBRW-Co, for predicting users co-occurrence based on mobility homophily and social links. More precisely, we analyze and mine jointly spatio-temporal and social features with the aim to predict and rank users co-occurrences. Experiments are performed on the Foursquare LBSN with accurate and refined measurements. Experimental...
Predicting resource requirements for cloud services is critical for dimensioning, anomaly detection and service assurance. We demonstrate a system for real-time estimation of the needed amount of infrastructure resources, such as CPU and memory, for a given service. Statistical learning methods on server statistics and load parameters of the service are used for learning a resource prediction model...
Autonomous Mobility On Demand (MOD) systems can utilize fleet management strategies in order to provide a high customer quality of service (QoS). Previous works on autonomous MOD systems have developed methods for rebalancing single capacity vehicles, where QoS is maintained through large fleet sizing. This work focuses on MOD systems utilizing a small number of vehicles, such as those found on a...
Energy efficiency in high performance computing (HPC) systems is a relevant issue nowadays, which is approached from multiple edges and components (network, I/O, resource management, etc). HPC industry turned its focus towards embedded and low-power computational infrastructures (of RISC architecture processors) to improve energy efficiency, therefore, we use an ARM-based cluster, known as millicluster,...
Cloud computing enables end users to execute high-performance computing applications by renting the required computing power. This pay-for-use approach enables small enterprises and startups to run HPC-related businesses with a significant saving in capital investment and a short time to market. When deploying an application in the cloud, the users may a) fail to understand the interactions of the...
Studies the issue of forecasting the parameter values that describe production-and-economic systems and the projects that are realized in such systems; it examines the preparation of statistical data with gaps and suggests the advantage of using different time slots of the collected data for their further joint use in prognostic models. The article reviews the applicability of the existing forecasting...
Background: Due to tight scheduling and limitedbudget, it may not be possible to resolve all the existing bugsin a current release of a software product. The accumulation ofthe deferred bugs in the issue tracking system are obligations (liabilities) of the software team similar to financial analogyof 'debt'. Defect debt is known as latent defects which arenot resolved in the current release. Aim:...
Build systems play a crucial role in modern software engineering. Recent studies have shown that many builds fail, mostly due to neglected maintenance. This blocks teams from continuing the development and costs time and resources to fix. The target of the thesis is to reduce build breakage by investigating changes that lead to failing builds, identifying bad and best practices for build configuration,...
Today's HPC applications are producing extremely large amounts of data, such that data storage and analysis are becoming more challenging for scientific research. In this work, we design a new error-controlled lossy compression algorithm for large-scale scientific data. Our key contribution is significantly improving the prediction hitting rate (or prediction accuracy) for each data point based on...
Researchers often focus on the development process and the final product (source code) to investigate and predict software defects. Unfortunately, these models may not be applicable to software projects in which there is no access to the data sources regarding development process. For example, in cases when a company conducts tests on behalf of its business contractors, it is only possible to evaluate...
Techniques known as Nonlinear Set Membership prediction, Kinky Inference or Lipschitz Interpolation are fast and numerically robust approaches to nonparametric machine learning that have been proposed to be utilised in the context of system identification and learning-based control. They utilise presupposed Lipschitz properties in order to compute inferences over unobserved function values. Unfortunately,...
We would like to present the idea of our Continuous Defect Prediction (CDP) research and a related dataset that we created and share. Our dataset is currently a set of more than 11 million data rows, representing files involved in Continuous Integration (CI) builds, that synthesize the results of CI builds with data we mine from software repositories. Our dataset embraces 1265 software projects, 30,022...
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