99 research outputs found
Communications software performance prediction
Software development can be costly and it is important that confidence in a software system be established as early as possible in the design process. Where the software supports communication services, it is essential that the resultant system will operate within certain performance constraints (e.g. response time). This paper gives an overview of work in progress on a collaborative project sponsored by BT which aims to offer performance predictions at an early stage in the software design process. The Permabase architecture enables object-oriented software designs to be combined with descriptions of the network configuration and workload as a basis for the input to a simulation model which can predict aspects of the performance of the system. The prototype implementation of the architecture uses a combination of linked design and simulation tools
Creating Responsive Information Systems with the Help of SSADM
In this paper, a program for a research is outlined. Firstly, the concept of responsive information systems is defined and then the notion of the capacity planning and software performance engineering is clarified. Secondly, the purpose of the proposed methodology of capacity planning, the interface to information systems analysis and development methodologies (SSADM), the advantage of knowledge-based approach is discussed. The interfaces to CASE tools more precisely to data dictionaries or repositories (IRDS) are examined in the context of a certain systems analysis and design methodology (e.g. SSADM)
Generating a Performance Stochastic Model from UML Specifications
Since its initiation by Connie Smith, the process of Software Performance
Engineering (SPE) is becoming a growing concern. The idea is to bring
performance evaluation into the software design process. This suitable
methodology allows software designers to determine the performance of software
during design. Several approaches have been proposed to provide such
techniques. Some of them propose to derive from a UML (Unified Modeling
Language) model a performance model such as Stochastic Petri Net (SPN) or
Stochastic process Algebra (SPA) models. Our work belongs to the same category.
We propose to derive from a UML model a Stochastic Automata Network (SAN) in
order to obtain performance predictions. Our approach is more flexible due to
the SAN modularity and its high resemblance to UML' state-chart diagram
An Enhanced Performance Analysis of Software Using Architectural Feedback
The importance of software products and their quality attributes attainment has been a thing of concern in recent time to both academia and industry experts. This research work evaluated an enhanced performance analysis of software using architectural feedback. Data collected were, classified and analysed using SPSS reveal that the Relative Importance Index (RII) in relations to an enhance performance analysis of software using the architectural feedback was 0.83 which led to the proposal of a framework for an enhanced performance analysis of software using architectural feedback
Software Performance Engineering for Cloud Applications β A Survey
Cloud computing enables application service providers to lease their computing capabilities for deploying applications depending on user QoS (Quality of Service) requirements.Cloud applications have different composition, configuration and deployment requirements.Quantifying the performance of applications in Cloud computing environments is a challenging task. Software performance engineering(SPE) techniques enable us to assess performance requirements of software applications at the early stages of development. This assessment helps the developers to fine tune their design needs so that the targeted performance goals can be met. In this paper, we try to analyseperformance related issues of cloud applications and identify any SPE techniques currently available for cloud applications
ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π½Π°Π±ΠΎΡΠ° Π΄ΠΈΠ°Π³ΡΠ°ΠΌΠΌ UML Π΄Π»Ρ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ
Π Π°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ Π³Π΅Π½Π΅ΡΠ°ΡΠΈΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π΄ΠΈΠ°Π³ΡΠ°ΠΌΠΌ Π² Π½ΠΎΡΠ°ΡΠΈΠΈ UML ΠΊΠ°ΠΊ ΠΎΠ΄Π½Π° ΠΈΠ· Π±Π°Π·ΠΎΠ²ΡΡ
ΡΠΎΡΡΠ°Π²Π»ΡΡΡΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π² ΠΏΡΠΎΡΠ΅ΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΠΉ Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Software Performance Engineering (SPE), ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡΡΠΈΠΉ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΠΈΡΡ
ΠΎΠ΄Π½ΡΡ
Π΄Π°Π½Π½ΡΡ
ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΡΠ΅ ΡΠ»Π΅ΠΌΠ΅Π½ΡΡ UML ΠΈ ΡΡΠ΄ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΠΉ
ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π½Π°Π±ΠΎΡΠ° Π΄ΠΈΠ°Π³ΡΠ°ΠΌΠΌ UML Π΄Π»Ρ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΡ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ
Π Π°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°Π΅ΡΡΡ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡ Π³Π΅Π½Π΅ΡΠ°ΡΠΈΠΈ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±Π΅ΡΠΏΠ΅ΡΠ΅Π½ΠΈΡ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π΄ΠΈΠ°Π³ΡΠ°ΠΌΠΌ Π² Π½ΠΎΡΠ°ΡΠΈΠΈ UML ΠΊΠ°ΠΊ ΠΎΠ΄Π½Π° ΠΈΠ· Π±Π°Π·ΠΎΠ²ΡΡ
ΡΠΎΡΡΠ°Π²Π»ΡΡΡΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈΠ½ΡΠ΅Π³ΡΠ°ΡΠΈΠΈ Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ Π² ΠΏΡΠΎΡΠ΅ΡΡ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠΈ. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΠΉ Π½Π° ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ»ΠΎΠ³ΠΈΠΈ Software Performance Engineering (SPE), ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΡΡΠΈΠΉ Π² ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅ ΠΈΡΡ
ΠΎΠ΄Π½ΡΡ
Π΄Π°Π½Π½ΡΡ
ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΡΠ΅ ΡΠ»Π΅ΠΌΠ΅Π½ΡΡ UML ΠΈ ΡΡΠ΄ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΠΉ
ΠΠ΅ΡΠΎΠ΄Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΡ ΡΠΈΡΡΠ΅ΠΌ Π΄Π»Ρ ΠΌΠΎΠ±ΠΈΠ»ΡΠ½ΡΡ ΡΡΡΡΠΎΠΉΡΡΠ²
Π ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½Ρ ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΡ
ΡΠΈΡΡΠ΅ΠΌ Π΄Π»Ρ ΠΌΠΎΠ±ΠΈΠ»ΡΠ½ΡΡ
ΡΡΡΡΠΎΠΉΡΡΠ² Π½Π° ΡΠ°Π½Π½ΠΈΡ
ΡΡΠ°Π΄ΠΈΡΡ
ΠΆΠΈΠ·Π½Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠΈΠΊΠ»Π°, ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ ΠΈΡ
ΡΡΠ°Π²Π½ΠΈΡΠ΅Π»ΡΠ½ΡΠΉ
Π°Π½Π°Π»ΠΈΠ·, ΠΏΠΎΠΊΠ°Π·Π°Π½Ρ ΠΏΡΠΈΠΌΠ΅ΡΡ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ Π½Π° ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅. ΠΡΠΎΠ±ΠΎΠ΅ Π²Π½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΡΠ΄Π΅Π»Π΅Π½ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π²ΠΎΠΏΡΠΎΡΠ°
ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠΈΡ
ΡΠΎΡΠΌΠ°Π»ΡΠ½ΡΡ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ
ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΡΠ·ΡΠΊΠ° ΡΠΏΠ΅ΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ UML.Π£ ΡΡΠ°ΡΡΡ ΡΠΎΠ·Π³Π»ΡΠ½ΡΡΡ ΡΡΠ½ΡΡΡΡ ΠΌΠ΅ΡΠΎΠ΄ΠΈ ΠΎΡΡΠ½ΠΊΠΈ ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠ²Π½ΠΎΡΡΡ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ½ΠΈΡ
ΡΠΈΡΡΠ΅ΠΌ Π΄Π»Ρ ΠΌΠΎΠ±ΡΠ»ΡΠ½ΠΈΡ
ΠΏΡΠΈΡΡΡΠΎΡΠ² Π½Π° ΡΠ°Π½Π½ΡΡ
ΡΡΠ°Π΄ΡΡΡ
ΠΆΠΈΡΡΡΠ²ΠΎΠ³ΠΎ ΡΠΈΠΊΠ»Ρ, ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΎ ΡΡ
ΠΏΠΎΡΡΠ²Π½ΡΠ»ΡΠ½ΠΈΠΉ Π°Π½Π°Π»ΡΠ·, ΠΏΠΎΠΊΠ°Π·Π°Π½Ρ ΠΏΡΠΈΠΊΠ»Π°Π΄ΠΈ
Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ Π½Π° ΠΏΡΠ°ΠΊΡΠΈΡΡ. ΠΡΠΎΠ±Π»ΠΈΠ²Π° ΡΠ²Π°Π³Π° ΠΏΡΠΈΠ΄ΡΠ»Π΅Π½Π° Π΄ΠΎΡΠ»ΡΠ΄ΠΆΠ΅Π½Π½Ρ ΠΏΠΈΡΠ°Π½Π½Ρ Π²ΠΈΠΊΠΎΡΠΈΡΡΠ°Π½Π½Ρ ΡΡΠ½ΡΡΡΠΈΡ
ΡΠΎΡΠΌΠ°Π»ΡΠ½ΠΈΡ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ½ΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄ΡΠ² Π΄Π»Ρ ΠΎΡΡΠ½ΠΊΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠ½ΠΎΡ ΡΠΈΡΡΠ΅ΠΌΠΈ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΌΠΎΠ²ΠΈ
ΡΠΏΠ΅ΡΠΈΡΡΠΊΠ°ΡΡΡ UML.The performance estimation techniques of the mobile devices software at the early lifecycle stages is
examined in the article. There comparative analysis and examples of practice are shown. Special attention is paid to
problem of using the formal mathematical methods for estimation of software characteristics within the bounds of UML
specification language
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