scholarly journals TANDEM: A Taxonomy and a Dataset of Real-World Performance Bugs

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 107214-107228
Author(s):  
Ana B. Sanchez ◽  
Pedro Delgado-Perez ◽  
Inmaculada Medina-Bulo ◽  
Sergio Segura
Keyword(s):  
Real World ◽  
Performance Bugs

scholarly journals Understanding and detecting real-world performance bugs

2012 ◽  
Vol 47 (6) ◽  
pp. 77-88 ◽  
Author(s):  
Guoliang Jin ◽  
Linhai Song ◽  
Xiaoming Shi ◽  
Joel Scherpelz ◽  
Shan Lu
Keyword(s):  
Real World ◽  
Performance Bugs

Predicting Performance Anomalies in Software Systems at Run-time

2021 ◽  
Vol 30 (3) ◽  
pp. 1-33
Author(s):  
Guoliang Zhao ◽  
Safwat Hassan ◽  
Ying Zou ◽  
Derek Truong ◽  
Toby Corbin
Keyword(s):  
Resource Utilization ◽  
Real World ◽  
Negative Impact ◽  
Software Systems ◽  
System Response ◽  
Normal System ◽  
Software System ◽  
Predicting Performance ◽  
Run Time ◽  
Performance Bugs

High performance is a critical factor to achieve and maintain the success of a software system. Performance anomalies represent the performance degradation issues (e.g., slowing down in system response times) of software systems at run-time. Performance anomalies can cause a dramatically negative impact on users’ satisfaction. Prior studies propose different approaches to detect anomalies by analyzing execution logs and resource utilization metrics after the anomalies have happened. However, the prior detection approaches cannot predict the anomalies ahead of time; such limitation causes an inevitable delay in taking corrective actions to prevent performance anomalies from happening. We propose an approach that can predict performance anomalies in software systems and raise anomaly warnings in advance. Our approach uses a Long-Short Term Memory neural network to capture the normal behaviors of a software system. Then, our approach predicts performance anomalies by identifying the early deviations from the captured normal system behaviors. We conduct extensive experiments to evaluate our approach using two real-world software systems (i.e., Elasticsearch and Hadoop). We compare the performance of our approach with two baselines. The first baseline is one state-to-the-art baseline called Unsupervised Behavior Learning. The second baseline predicts performance anomalies by checking if the resource utilization exceeds pre-defined thresholds. Our results show that our approach can predict various performance anomalies with high precision (i.e., 97–100%) and recall (i.e., 80–100%), while the baselines achieve 25–97% precision and 93–100% recall. For a range of performance anomalies, our approach can achieve sufficient lead times that vary from 20 to 1,403 s (i.e., 23.4 min). We also demonstrate the ability of our approach to predict the performance anomalies that are caused by real-world performance bugs. For predicting performance anomalies that are caused by real-world performance bugs, our approach achieves 95–100% precision and 87–100% recall, while the baselines achieve 49–83% precision and 100% recall. The obtained results show that our approach outperforms the existing anomaly prediction approaches and is able to predict performance anomalies in real-world systems.

Replications can cause distorted belief in scientific progress

2018 ◽  
Vol 41 ◽  
Author(s):  
Michał Białek
Keyword(s):  
Real World ◽  
Scientific Progress ◽  
The Public ◽  
Psychological Science

AbstractIf we want psychological science to have a meaningful real-world impact, it has to be trusted by the public. Scientific progress is noisy; accordingly, replications sometimes fail even for true findings. We need to communicate the acceptability of uncertainty to the public and our peers, to prevent psychology from being perceived as having nothing to say about reality.

Current Issues: Evidence-Based Practice for the Real World: Thoughts on Clinical Education in Communication Disorders

2010 ◽  
Vol 20 (3) ◽  
pp. 100-105 ◽  
Author(s):  
Anne K. Bothe
Keyword(s):  
Clinical Education ◽  
Real World ◽  
Evidence Based Practice ◽  
Communication Disorders ◽  
University Faculty ◽  
Evidence Based ◽  
Speech Language Pathology ◽  
Basic Principles ◽  
The Real ◽  
Language Pathology

This article presents some streamlined and intentionally oversimplified ideas about educating future communication disorders professionals to use some of the most basic principles of evidence-based practice. Working from a popular five-step approach, modifications are suggested that may make the ideas more accessible, and therefore more useful, for university faculty, other supervisors, and future professionals in speech-language pathology, audiology, and related fields.

Qualitative Case Study Research Design

2015 ◽  
Vol 25 (1) ◽  
pp. 39-45 ◽  
Author(s):  
Jennifer Tetnowski
Keyword(s):  
Research Design ◽  
Real World ◽  
Qualitative Case Study ◽  
Case Study Research ◽  
Study Research

Qualitative case study research can be a valuable tool for answering complex, real-world questions. This method is often misunderstood or neglected due to a lack of understanding by researchers and reviewers. This tutorial defines the characteristics of qualitative case study research and its application to a broader understanding of stuttering that cannot be defined through other methodologies. This article will describe ways that data can be collected and analyzed.

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