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BackgroundAgile principles play a pivotal role in modern software development. Unfortunately, the assessment of non-functional software properties, such as performance, can be challenging in Agile Software Development (ASD). Agile mentality tends to favor functional development over non-functional quality assurance. Additionally, frequent code changes and software releases make impractical the use of classical performance assurance approaches.ObjectiveThis paper investigates the current practices, problems and challenges of performance assurance in a real context of ASD. To the best of our knowledge, this is the first empirical study that specifically investigate performance assurance in ASD daily work.MethodThrough a 6-months industry collaboration with a large software organization that adopts ASD, we investigated practical and management problems in handling performance assurance activities. The research was conducted in line with ethnographic research, which guided towards building knowledge from participatory observations, unstructured interviews and reviews of documentations.ResultsThe study shows that the case organization still relies on a waterfall-like approach for performance assurance. Such an approach showed to be inadequate for ASD, thereby leading to a sub-optimal management of performance assessment activities. We distilled three key challenges when trying to improve the performance assurance process: (i) managing performance assessment activities, (ii) continuous performance assessment and (iii) defining the performance assessment effort.ConclusionsThe assessment of software performance in the context of ASD is still far from being flawless. The lack of guidelines and well-established practices induces the adoption of approaches that can be obsolete and inadequate for ASD. Further research is needed to improve the performance management in this context, and to enable effective continuous performance assessment.

In this paper, we present an evaluation methodology to validate the performance of a UML model, representing a software architecture. The proposed approach is based on open and well-known standards: UML for software modeling and the OMG Profile for Schedulability, Performance, and Time Specification for the performance annotations into UML models. Such specifications are collected in an intermediate model, called the Performance Context Model (PCM). The intermediate model is translated into a performance model which is subsequently evaluated. The paper is focused on the mapping from the PCM to the performance domain. More specifically, we adopt Petri nets as the performance domain, specifying a mapping process based on a compositional approach we have entirely implemented in the ArgoPerformance tool. All of the rules to derive a Petri net from a PCM and the performance measures assessable from the former are carefully detailed. To validate the proposed technique, we provide an in-depth analysis of a web application for music streaming.

Although sound performance analysis theories and techniques exist, they are not widely used because they require extensive expertise in performance modeling and measurement. The overall goal of our work is to make performance modeling more accessible by automating much of the modeling effort. We have proposed a model interoperability framework that enables performance models to be automatically exchanged among modeling (and other) tools. The core of the framework is a set of model interchange formats (MIF): a common representation for data required by performance modeling tools. Our previous research developed a representation for system performance models (PMIF) and another for software performance models (S-PMIF), both based on the Queueing Network Modeling (QNM) paradigm. In order to manage the research scope and focus on model interoperability issues, the initial MIFs were limited to QNMs that can be solved by efficient, exact solution algorithms. The overall model interoperability approach has now been demonstrated to be viable. This paper broadens the scope of PMIF and S-PMIF to represent models that can be solved with additional methods such as analytical approximations or simulation solutions. It presents the extensions considered, describes the extended meta-models, and provides verification with examples and a case study.

In this paper, we propose the towards virtualized and automated software performance test architecture. In general, test engineers use the public performance testwares such as Load Runner, Silk Performer to validate the performance efficiency of their own systems. In case that they do not allowed to use the performance testwares due to the technical limitations in the testwares, most testers should perform the testing in manually. According to the waste of computer and human resources resulted from the situation, we need to propose the test automation scheme by using the virtualization technology to prevent the dissipation in the test environment which has limited resources. The system architecture considered efficient usage of computer resources and test automation to reduce human acts are addressed mainly in this paper. we describe our proposed method which deals with the system architecture and test automation procedures. In our system architecture, we will show how to use the virtual machines and the types of the virtual machines for performance measurement. In addition, the six steps of the test automation are introduced for the automated testing procedures. Finally, a number of experiments show that the proposed schemes allow offering the possibility for automated software performance testing by using the virtualization.

Component-based software engineering (CBSE) poses challenges for predicting and evaluating software performance but also offers several advantages. Software performance engineering can benefit from CBSE ideas and concepts. The MediaStore, a fictional system, demonstrates how to achieve compositional reasoning about software performance.

Bioinformatics is a branch of science that uses computers, algorithms, and databases to solve biological problems. To achieve more accurate results, researchers need to use large and complex datasets. Sequence alignment is a well-known field of bioinformatics that allows the comparison of different genomic sequences. The comparative genomics field allows the comparison of different genomic sequences, leading to benefits in areas such as evolutionary biology, agriculture, and human health (e.g., mutation testing connects unknown genes to diseases). However, software engineering best practices, such as software performance engineering, are not taken into consideration in most bioinformatics tools and frameworks, which may lead to serious performance problems. Having an estimate of the software performance in the early phases of the Software Development Life Cycle (SDLC) is beneficial in making better decisions relating to the software design. Software performance engineering provides a reliable and observable method to build systems that can achieve their required performance goals. In this paper, we introduce the use of the Palladio Component Modeling (PCM) methodology to predict the performance of a sequence alignment system. Software performance engineering was not considered during the original system development. As a result of the performance analysis, an alternative design is proposed. Comparing the performance of the proposed design against the one already developed, a better response time is obtained. The response time of the usage scenario is reduced from 16 to 8.6 s. The study results show that using performance models at early stages in bioinformatics systems can help to achieve better software system performance.

Distributed applications are being developed that contain one or more layers of software servers. Software processes within such systems suffer contention delays both for shared hardware and at the software servers. The responsiveness of these systems is affected by the software design, the threading level and number of instances of software processes, and the allocation of processes to processors. The Method of Layers (MOL) is proposed to provide performance estimates for such systems. The MOL uses the mean value analysis (MVA) linearizer algorithm as a subprogram to assist in predicting model performance measures.< >

El rendimiento es un importante atributo de calidad de un sistema de software. La Ingeniería de rendimiento del software comprende las actividades de análisis, diseño, construcción, medición y validación, que atienden los requerimientos de rendimiento a lo largo del proceso de desarrollo de software.  En los sistemas de software que utilizan comunicación basada en mensajes, el rendimiento depende en gran medida del middleware orientado a mensajes (Message-Oriented Middleware – MOM). Los arquitectos de software necesitan considerar su organización, configuración y uso para predecir el comportamiento de un sistema que use tal plataforma. La inclusión de un MOM en una arquitectura de software requiere conocer el impacto de la mensajería y de la infraestructura utilizada. Omitir la influencia del MOM llevaría a la generación de predicciones erróneas. En este artículo se explora tal influencia, mediante el modelado y la simulación basados en componentes, utilizando el enfoque Palladio Component Model – PCM. En particular, una aplicación modelada en PCM fue adaptada para incluir comunicación basada en mensajes. Las simulaciones sobre el modelo, mediciones sistemáticas y pruebas de carga sobre la aplicación permitieron determinar cómo cambios introducidos en el modelo influyen en las predicciones del comportamiento de la aplicación en cuanto a rendimiento y confiabilidad. Fue posible identificar un cuello de botella que impacta negativamente el rendimiento y la confiabilidad del sistema original. La introducción de MOM mejoró la confiabilidad del sistema, a expensas del rendimiento. La simulación del rendimiento basado en componentes reveló diferencias significativas respecto de los experimentos basados en pruebas de carga y mediciones.

Software performance engineering (SPE) provides an approach to constructing systems to meet performance objectives. The authors illustrate the application of SPE to an example with some real-time properties and demonstrate how to compare performance characteristics of design alternatives. They show how SPE can be integrated with design methods and demonstrate that performance requirements can be achieved without sacrificing other desirable design qualities such as understandability, maintainability, and reusability.< >