Now showing 1 - 3 of 3
  • Publication
    Towards an Efficient Log Data Protection in Software Systems through Data Minimization and Anonymization
    IT infrastructures of companies generate large amounts of log data every day. These logs are typically analyzed by software engineers to gain insights about activities occurring within a company (e.g., to debug issues exhibited by the production systems). To facilitate this process, log data management is often outsourced to cloud providers. However, logs may contain information that is sensitive by nature and considered personal identifiable under most of the new privacy protection laws, such as the European General Data Protection Regulation (GDPR). To ensure that companies do not violate regulatory compliance, they must adopt, in their software systems, appropriate data protection measures. Such privacy protection laws also promote the use of anonymization techniques as possible mechanisms to operationalize data protection. However, companies struggle to put anonymization in practice due to the lack of integrated, intuitive, and easy-to-use tools that accommodate effectively with their log management systems. In this paper, we propose an automatic approach (SafeLog) to filter out information and anonymize log streams to safeguard the confidentiality of sensitive data and prevent its exposure and misuse from third parties. Our results show that atomic anonymization operations can be effectively applied to log streams to preserve the confidentiality of information, while still allowing to conduct different types of analysis tasks such as users behavior, and anomaly detection. Our approach also reduces the amount of data sent to cloud vendors, hence decreasing the financial costs and the risk of overexposing information.
      375Scopus© Citations 3
  • Publication
    DYNAMOJM: A JMeter Tool for Performance Testing Using Dynamic Workload Adaptation
    Performance testing is a critical task to assure optimal experience for users, especially when there are high loads of concurrent users. JMeter is one of the most widely used tools for load and stress testing. With JMeter, it is possible to test the performance of static and dynamic resources on the web. This paper presents DYNAMOJM, a novel tool built on top of JMeter that enables testers to create a dynamic workload for performance testing. This tool implements the DYNAMO approach, which has proven useful to find performance issues more efficiently than static testing techniques.
      330
  • Publication
    Towards an Efficient Performance Testing Through Dynamic Workload Adaptation
    Performance testing is a critical task to ensure an acceptable user experience with software systems, especially when there are high numbers of concurrent users. Selecting an appropriate test workload is a challenging and time-consuming process that relies heavily on the testers’ expertise. Not only are workloads application-dependent, but also it is usually unclear how large a workload must be to expose any performance issues that exist in an application. Previous research has proposed to dynamically adapt the test workloads in real-time based on the application behavior. By reducing the need for the trial-and-error test cycles required when using static workloads, dynamic workload adaptation can reduce the effort and expertise needed to carry out performance testing. However, such approaches usually require testers to properly configure several parameters in order to be effective in identifying workload-dependent performance bugs, which may hinder their usability among practitioners. To address this issue, this paper examines the different criteria needed to conduct performance testing efficiently using dynamic workload adaptation. We present the results of comprehensively evaluating one such approach, providing insights into how to tune it properly in order to obtain better outcomes based on different scenarios. We also study the effects of varying its configuration and how this can affect the results obtained.
      231