Antipattern-based model refactoring for software performance improvement

Arcelli, Davide; Cortellessa, Vittorio; Trubiani, Catia

doi:10.1145/2304696.2304704

Cited by 38 publications

(28 citation statements)

References 19 publications

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“…This approach was first used in 24 for software performance improvement. In 1,7,8,9,11,20,21 various approaches have been proposed to automatically detect software performance antipatterns in software architectural model and remove them.…”

Section: Antipattern Based Approachmentioning

confidence: 99%

Automatic Feedback Generation in Software Performance Engineering: A Review

Iqbal

Haq

2017

Orient. J. Chem

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Automation in generation of architectural feedback from performance indexes like probability distributions, mean values and variances has been of interest to the researchers from last decade. It is well established that due to the complexity in interpreting the performance indices obtained from performance analysis of software architecture and short time to the market, an automated approach is vital for acceptance of architecture based software performance engineering approach by software industry. In last decade some work has beendone in this direction. Aim of this paper is to explore the existing research in the field, which will be valuable for researchers looking forward to contributing to this research.

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Section: Antipattern Based Approachmentioning

confidence: 99%

Automatic Feedback Generation in Software Performance Engineering: A Review

Iqbal

Haq

2017

Orient. J. Chem

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“…In particular, language-specific and project-specific metrics, smells, and refactorings for the design level may be defined based on graph transformations. A refactoring approach considering performance optimization of models, i.e., runtime level, is presented in Arcelli et al (2012). In this context, refactorings are used to eliminate anti-patterns that may have a negative impact on performance aspects.…”

Section: Model Refactoringsmentioning

confidence: 99%

“…A variety of refactoring work has been proposed in the literature (Fowler et al 1999;Mens and Tourwé 2004), and the majority of them focus only on the source code level. Despite its importance, model refactoring is still in its teenage years (Mens 2006;Mens et al 2007b;Arcelli et al 2012). In fact, model refactoring is more difficult and challenging than code refactoring for several reasons.…”

Section: Introductionmentioning

confidence: 99%

Multi-view refactoring of class and activity diagrams using a multi-objective evolutionary algorithm

et al. 2015

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To improve the quality of software systems, one of the widely used techniques is refactoring defined as the process of improving the design of an existing system by changing its internal structure without altering the external behavior. The majority of existing refactoring work focuses mainly on the source code level. The suggestion of refactorings at the model level is more challenging due to the difficulty to evaluate: (a) the impact of the suggested refactorings applied to a diagram on other related diagrams to improve the overall system quality, (b) their feasibility, and (c) interdiagram consistency. We propose, in this paper, a novel framework that enables software designers to apply refactoring at the model level. To this end, we used a multi-objective evolutionary algorithm to find a trade-off between improving the quality of class and activity diagrams. The proposed multi-objective approach provides a multi-view for software designers to evaluate the impact of suggested refactorings applied to class diagrams on related activity diagrams in order to evaluate the overall quality, and check their feasibility and behavior preservation. The statistical evaluation performed on models extracted from four opensource systems confirms the efficiency of our approach.

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“…These program parts are then instrumented using the code manipulation interface of Recoder, which simply adds appropriate event generators tracing the dynamic execution of the candidates and providing runtime information. Recently, in [14], the authors convert the Software Architectural Model (UML annotated with MARTE, PCM ) of application to a Performance Model like Queuing Network and identify performance antipatterns (from design specifications) in them using First order Predicate Logic to represent antipatterns and the defined thresholds for various features like maximum connections, messages, hardware utilization, etc. In [15], the authors propose a framework for detecting performance antipatterns in component based systems using dynamic analysis, by applying techniques borrowed from the field of Knowledge Discovery in Databases (KDD).…”

Section: Importance Of Performance Antipatterns In Context Of Thementioning

confidence: 99%

Performance Antipatterns: Detection and Evaluation of Their Effects in the Cloud

Sharma¹,

Anwer

2014

2014 IEEE International Conference on Services Computing

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The way an application is designed and certain patterns thereof, play a significant role and might have a positive or a negative effect on the performance of the application. Some design patterns that have a negative effect on performance, also called performance antipatterns, may become important when evaluating migrating the application to the Cloud. Although there has been work done in the past related to defining performance antipatterns, there has been none that highlights the importance and effects of these performance antipatterns when an application is migrated to Cloud. In this work we present an approach to automatically detect important performance antipatterns in an application, by leveraging static code analysis and information about prospective deployment of the application components on the Cloud. We also experimentally show that these antipatterns may become prominent and pull down the application's performance if the application is migrated to the Cloud. Our results show that the performance of the parts of the application with such antipatterns suffer significantly and hence, the detection of these antipatterns has an overarching significance in the domain of software development for the Cloud. The approach we present here has also been implemented in a prototype cloud migration assessment tool.

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Antipattern-based model refactoring for software performance improvement

Cited by 38 publications

References 19 publications

Automatic Feedback Generation in Software Performance Engineering: A Review

Automatic Feedback Generation in Software Performance Engineering: A Review

Multi-view refactoring of class and activity diagrams using a multi-objective evolutionary algorithm

Performance Antipatterns: Detection and Evaluation of Their Effects in the Cloud

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