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- Avritzer, Alberto A., et al.
(författare)
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A Multivariate Characterization and Detection of Software Performance Antipatterns
- 2021
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Ingår i: ICPE 2021 - Proceedings of the ACM/SPEC International Conference on Performance Engineering. - New York, NY, USA : Association for Computing Machinery, Inc. - 9781450381949 ; , s. 61-72
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Konferensbidrag (refereegranskat)abstract
- Context. Software Performance Antipatterns (SPAs) research has focused on algorithms for the characterization, detection, and solution of antipatterns. However, existing algorithms are based on the analysis of runtime behavior to detect trends on several monitored variables (e.g., response time, CPU utilization, and number of threads) using pre-defined thresholds. Objective. In this paper, we introduce a new approach for SPA characterization and detection designed to support continuous integration/delivery/deployment (CI/CDD) pipelines, with the goal of addressing the lack of computationally efficient algorithms. Method. Our approach includes SPA statistical characterization using a multivariate analysis approach of load testing experimental results to identify the services that have the largest impact on system scalability. More specifically, we introduce a layered decomposition approach that implements statistical analysis based on response time to characterize load testing experimental results. A distance function is used to match experimental results to SPAs. Results. We have instantiated the introduced methodology by applying it to a large complex telecom system. We were able to automatically identify the top five services that are scalability choke points. In addition, we were able to automatically identify one SPA. We have validated the engineering aspects of our methodology and the expected benefits by means of a domain experts' survey. Conclusion. We contribute to the state-of-The-Art by introducing a novel approach to support computationally efficient SPA characterization and detection in large complex systems using performance testing results. We have compared the computational efficiency of the proposed approach with state-of-The-Art heuristics. We have found that the approach introduced in this paper grows linearly, which is a significant improvement over existing techniques. © 2021 ACM.
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| 2. |
- Avritzer, Alberto A., et al.
(författare)
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PPTAMλ : What, Where, and How of Cross-domain Scalability Assessment
- 2021
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Ingår i: Proceedings - 2021 IEEE 18th International Conference on Software Architecture Companion, ICSA-C 2021. - : Institute of Electrical and Electronics Engineers Inc.. - 9781665439107 ; , s. 62-69
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Konferensbidrag (refereegranskat)abstract
- Software development ecosystems vary significantly among different industrial domains. Therefore, it is challenging to establish quality assurance processes that can be deployed seamlessly to multiple domains. In this paper, we extend our previous work on performance and scalability assessment by identifying the architecture variability points in our PPTAM tooling infrastructure. The goal is to design a modifiable software architecture that enables low cost deployment of our performance and scalability assessment approach. We present the scalability assessment context, architecture modifiability, and lessons learned that were derived from our experience with scalability assessment in several business domains. Specifically, we describe our experience with the application of the proposed approach to a large complex telecom system at Ericsson. © 2021 IEEE.
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| 3. |
- Avritzer, A, et al.
(författare)
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Monitoring for Security Intrusion using Performance Signatures
- 2010
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Ingår i: WOSP/SIPEW'10 - Proceedings of the 1st Joint WOSP/SIPEW International Conference on Performance Engineering. - New York, NY, USA : ACM. - 9781605585635 ; , s. 93-103
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Konferensbidrag (refereegranskat)abstract
- A new approach for detecting security attacks on software systems by monitoring the software system performance signatures is introduced. We present a proposed architecture for security intrusion detection using off-the-shelf security monitoring tools and performance signatures. Our approach relies on the assumption that the performance signature of the well-behaved system can be measured and that the performancesignature of several types of attacks can be identified. This assumption has been validated for operations support systems that are used to monitor large infrastructures and receive aggregated traffic that is periodic in nature. Examples of such infrastructures include telecommunications systems, transportation systems and power generation systems. In addition, significant deviation from well-behaved system performance signatures can be used to trigger alerts about new types of security attacks. We used a custom performance benchmark and five types of security attacks to deriveperformance signatures for the normal mode of operation and the security attack mode of operation. We observed that one of the types of thesecurity attacks went undetected by the off-the-shelf security monitoring tools but was detected by our approach of monitoring performance signatures. We conclude that an architecture for security intrusion detection can be effectively complemented by monitoring of performance signatures.
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