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Software fault prediction models are employed to optimize testing resource allocation by identifying fault-prone classes before testing phases. We apply three different ensemble methods to develop a model for predicting fault proneness. We propose a framework to validate the source code metrics and select the right set of metrics with the objective to improve the performance of the fault prediction...
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...
Just-In-Time (JIT) defect prediction models aim to predict the commits that will introduce defects in the future. Traditionally, JIT defect prediction models are trained using metrics that are primarily derived from aspects of the code change itself (e.g., the size of the change, the author’s prior experience). In addition to the code that is submitted during a commit, authors write commit messages,...
Performance variation is a significant problem forlarge scale HPC systems and will increase on future exascalesystems. In this work, we show that performance variationimpacts the performance and energy efficiency of contemporarylarge-scale computing systems in highly temporally inconsistentways. We thus present a case for criticality models, a learningbased mechanism that allows a system to generate...
Tuning large applications requires a clever exploration of the design and configuration space. Especially on supercomputers, this space is so large that its exhaustive traversal via performance experiments becomes too expensive, if not impossible. Manually creating analytical performance models provides insights into optimization opportunities but is extremely laborious if done for applications of...
In this paper, we present a combined experimental and analytical investigation of the impact of security compliance on a three-tier web application hosted on a virtualized platform. We used two-group experimental design for our experiments, and analyzed the impact of security using the ANCOVA model. The results of experiments suggest that security measures have significant impact on system performance...
Lorenz time-series is characterized by non-linearity, noise, volatility and is chaotic in nature thus making the process of forecasting cumbersome. The main aim of forecasters is to apply an approach that focuses on improving accuracy in both one-step and multi-step-ahead forecasts. This paper presents an empirical analysis of Lorenz time-series using Scaled UKF-NARX hybrid model to perform one-step...
Over the past twenty years, trading in financial markets has evolved from a human-oriented process to one that is highly automated. One of the most influential and revolutionary processes in financial markets is algorithmic trading. The focus of this work is to increase trading efficiency by improving the accuracy of intraday volume forecasts, which are used in algorithmic trading. An intraday volume...
Free/Libre Open Source Software (FLOSS) community management is an important issue. Contributor churn (joining or leaving a project) causes failure of the majority of software projects. In this paper, we present a framework to characterize stability of the community in software maintenance projects by mining Issue Tracking System (ITS). We identify key stability indicators and propose metrics to measure...
Efficient design of predictable systems on top of multiprocessor-based architectures is challenging. It demands an integration effort to support system models relying on Models-of- Computation (MoC) theory, supporting real-time (RT) analysis and electronic system-level (ESL) design techniques. This paper presents a SystemC-based framework for modelling and time analysis of predictable embedded systems...
Cloud computing has emerging as an extremely popular and cost-effective computational service model using pay-as-you-go executing environments that scale transparently to the user. However, cloud providers should tackle the challenge of configuring their systems to provide maximal performance while minimizing customer's cost of computing resources, which satisfy the customers' various workload requirements...
Although peer-to-peer system is scalable for content distribution, its lifespan is shorter than traditional systems. More and more researchers pay close attention to swarm lifespan and propose specialized methods to extend it. Bundling technique and SRE (Share Ratio Enforcement) mechanism in Private Tracker system are two successful enhancements which are proved by practical systems. However, they...
In Mobile ad hoc Networks (MANETs), some mobility metrics are directly related to the performance of routing protocols. Creating accurate predict models for mobility metrics is an important advance for designing better mobility-adaptive protocols. Through regression analysis, we propose predictive formulas for three mobility metrics: link duration, node degree, and network partitioning, considering...
Predicting application performance for any hardware change is challenging as multiple factors like environment, application architecture, workload etc also need to be considered. Industry benchmarks that provide means to compare hardware performance however lack in giving insight into the applications' service levels. LQN models help in performance analysis of multi-tiered, distributed applications;...
With the rapid growth of the Internet and database technologies in recent years, question answering systems (QAS) have emerged as important applications. As most evaluation models focus on system-centered evaluation, user-centered evaluation has attracted little attention. Although many QAS have been implemented, little work has been done on the development of a user-centered evaluation for QAS. User-centered...
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