Open AccessBook
Model-Based Software Performance Analysis
TLDR
This book provides the cross-knowledge that allows developers to tackle software performance issues from the very early phases of software development and explains the basic concepts of performance analysis and describes the most representative methodologies to annotate and transform software models into performance models.Abstract:
Poor performance is one of the main quality-related shortcomings that cause software projects to fail. Thus, the need to address performance concerns early during the software development process is fully acknowledged, and there is a growing interest in the research and software industry communities towards techniques, methods and tools that permit to manage system performance concerns as an integral part of software engineering. Model-based software performance analysis introduces performance concerns in the scope of software modeling, thus allowing the developer to carry on performance analysis throughout the software lifecycle. With this book, Cortellessa, Di Marco and Inverardi provide the cross-knowledge that allows developers to tackle software performance issues from the very early phases of software development. They explain the basic concepts of performance analysis and describe the most representative methodologies used to annotate and transform software models into performance models. To this end, they go all the way from performance primers through software and performance modeling notations to the latest transformation-based methodologies. As a result, their book is a self-contained reference text on software performance engineering, from which different target groups will benefit: professional software engineers and graduate students in software engineering will learn both basic concepts of performance modeling and new methodologies; while performance specialists will find out how to investigate software performance model building.read more
Citations
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Proceedings ArticleDOI
Reinforcement Learning-Driven Continuous and Crashless Load Test Architecture
TL;DR: In this paper , a software architecture was presented, and prototype implementation was implemented for load testing of live systems with realistic loads continuously and without crashing the system, and experiments of the crashless load test module of the prototype were implemented.
Proceedings ArticleDOI
Model-driven round-trip software dependability engineering
TL;DR: This PhD program aims at introducing automation in the model-driven assessment of dependability, and proposes to leverage bidirectional model transformations to generate dependability analysis models from software models, and automatically propagate changes, driven by dependability requirements satisfaction, from analysis models back to software models.
Proceedings ArticleDOI
Statistical Learning of Markov Chains of Programs
TL;DR: In this paper, the authors present a statistical method that learns a Markov chain directly from a program, by means of execution runs with inputs sampled by given probability distributions, which can capture data dependency throughout execution paths by encoding part of the program history into each state of the chain.
Proceedings Article
Modelling decisions in layered queueing networks
Lianhau Li,Greg Franks +1 more
TL;DR: This paper defines four decision patterns: abort, timeout, infinite-retries and finite-retry, which are commonly used in the exception handling during resource allocations, and implemented in the LQN simulation tool, LQSIM.
Performance Prediction Approaches for Component-based Systems
Monika Kalotra,Kuljit Kaur +1 more
TL;DR: A basis to select an appropriate prediction method for component assemblies is established and recommendations for future research are provided, which could improve the performance prediction of component- based systems.
References
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Journal ArticleDOI
A performance model interchange format
TL;DR: The definition of a PMIF is presented by describing a meta-model of the information requirements and the transfer format derived from it, which describes how tool developers can implement the PMIF, how the model interchange via export and import works in practice, and how thePMIF can be extended.