UML-based performance engineering possibilities and techniques

Dimitrov, Evgeni; Schmietendorf, Andreas; Dumhe, R.

doi:10.1109/52.976944

Cited by 18 publications

(8 citation statements)

References 4 publications

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“…Dimitrov et al provided numerous examples of how existing UML diagrams can be augmented to represent performance related attributes such as timing and execution rates [3]. However, in order to support speculation, the UML modeling environment must be executable and must provide some output that can be compared to a specified performance requirement.…”

Section: Uml Modelsmentioning

confidence: 99%

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Automating speculative queries through event-based requirements traceability

Cleland‐Huang

Chang

Sethi³

et al.

Proceedings IEEE Joint International Conference on Requirements Engineering

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Posing speculative questions about a software system is an important yet often unsupported activity. Current impact analysis techniques tend to focus upon the functionality of the system, whilst the effects of change upon performance requirements are largely ignored until after implementation. This tendency can lead to costly and time-consuming mistakes. Event-Based traceability provides a robust method for handling both long-term evolutionary change as well as the short-term speculative change needed to support performance related impact analysis. By establishing dynamic links, capable of propagating data values and commands between requirements and performance models, it becomes possible to automate a wide range of speculative queries and to enhance the overall ability to predict the impact of change upon the performance of the system.

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Section: Uml Modelsmentioning

confidence: 99%

“…Although there has traditionally been a tendency within the Object-Oriented community to defer performance related issues until after implementation, recently emphasis has been placed on performance engineering throughout the development process in order to control the risks inherent to constructing large systems [2,3,4,5].…”

Section: Changementioning

confidence: 99%

Automating speculative queries through event-based requirements traceability

Cleland‐Huang

Chang

Sethi³

et al.

Proceedings IEEE Joint International Conference on Requirements Engineering

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Section: Modelling and Predictionmentioning

confidence: 99%

“…Among the most common techniques are Petri-Nets [19] and Layered Queuing Network [13][21] [20] models. We envisage that models created automatically by monitoring the system can be simulated and predictions derived for different workloads using LQN and Markov chains [19] techniques. Distinctive from related approaches, the proposed framework can perform the simulations at different abstraction levels, and developers can choose to refine particular simulations that are more likely to yield performance alerts.…”

Section: Modelling and Predictionmentioning

confidence: 99%

Performance management in component-oriented systems using a Model Driven Architecture/spl trade/ approach

Mos

Murphy

Proceedings. Sixth International Enterprise Distributed Object Computing

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Developers often lack the time or knowledge to profoundly understand the performance issues in largescale component-oriented enterprise applications. This situation is further complicated by the fact that such applications are often built using a mix of in-house and Commercial-Off-The-Shelf (COTS) components.This paper presents a methodology for understanding and predicting the performance of component-oriented distributed systems both during development and after they have been built. The methodology is based on three conceptually separate parts: monitoring, modelling and performance prediction. Performance predictions are based on UML models created dynamically by monitoring-and-analysing a live or under-development system. The system is monitored using non-intrusive methods and run-time data is collected. In addition, static data is obtained by analysing the deployment configuration of the target application. UML models enhanced with performance indicators are created based on both static and dynamic data, showing performance hot spots. To facilitate the understanding of the system, the generated models are traversable both horizontally at the same abstraction level between transactions, and vertically between different layers of abstraction using the concepts defined by the Model Driven Architecture. The system performance is predicted and performance-related issues are identified in different scenarios by generating workloads and simulating the performance models.Work is under way to implement a framework for the presented methodology with the current focus on the Enterprise Java Beans technology.

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“…A framework that allows UML diagrams to be used for building performance models is presented by Kahkipuro [12]. Dimitrov et.al [5] presented various kinds of UML extensions that are used to annotate and embed performance aspects of various UML diagrams. A UML-driven framework is presented and several interesting and useful approaches of direct and expanded extensions to UML are presented, such as, load-andtime weighted use case diagrams, sequence and activity diagrams with time information, state diagrams with transition probability and most importantly deployment diagrams (which map the various software components to the system hardware platform).…”

Section: Performance Based Risk Related Workmentioning

confidence: 99%

Software risk assessment based on UML models

Appukkutty¹

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Software Risk Assessment based on UML models Kalaivani Appukkutty Risk is the possibility of suffering loss. Risks identified during the early stages of software development are easier and cheaper to handle by making changes to the software architecture. This thesis presents methodologies to assess software risk using Unified Modeling Language (UML) specifications of the software from the early design stages. We present methodologies to assess two types of software risk: Requirementsbased risk and Performance-based risk. In assessing requirements-based risk, each requirement is mapped to a specific operational scenario in UML. The risk factor of a scenario in a failure mode is obtained by combining the probability of failure of the scenario and the severity of the failure. For the performance-based risk analysis, we use UML diagrams with performance related annotations, build a software execution model for each scenario and then map it to a system execution model using the deployment information. For estimating the performance-based failures of each scenario we use an asymptotic bounding analysis. The methodologies are applied on various case studies.

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UML-based performance engineering possibilities and techniques

Cited by 18 publications

References 4 publications

Automating speculative queries through event-based requirements traceability

Automating speculative queries through event-based requirements traceability

Performance management in component-oriented systems using a Model Driven Architecture/spl trade/ approach

Software risk assessment based on UML models

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