Antinisca Di Marco

Model-Based Software Performance Analysis

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.

From UML models to software performance results: an SPE process based on XML interchange formats

The SPE process uses multiple performance assessment tools depending on the state of the software and the amount of performance data available. This paper describes two XML based interchange formats that facilitate using a variety of performance tools in a plug-and-play manner thus enabling the use of the tool best suited to the analysis. The Software Performance Model Interchange Format (S-PMIF) is a common representation that is used to exchange information between (UML-based) software design tools and software performance engineering tools. On the other hand, the performance model interchange format (PMIF 2.0) is a common representation for system performance model data that can be used to move models among system performance modeling tools that use a queueing network model paradigm. This paper first defines an XML based S-PMIF based on an updated SPE meta-model Then it demonstrates the feasibility of using both the S-PMIF and the PMIF 2.0 to automatically translate an architecture description in UML into both a software performance model and a system performance model to study the performance characteristics of the architecture. This required the implementation of some extensions to the XPRIT software in order to export UML models into the S-PMIF and a new function in the SPEED software to import S-PMIF models, which are also described. The SPE process and an experimental proof of concept are presented.

An approach for modeling and detecting software performance antipatterns based on first-order logics

The problem of interpreting the results of performance analysis is quite critical in the software performance domain. Mean values, variances and probability distributions are hard to interpret for providing feedback to software architects. Instead, what architects expect are solutions to performance problems, possibly in the form of architectural alternatives (e.g. split a software component in two components and re-deploy one of them). In a software performance engineering process, the path from analysis results to software design or implementation alternatives is still based on the skills and experience of analysts. In this paper, we propose an approach for the generation of feedback based on performance antipatterns. In particular, we focus on the representation and detection of antipatterns. To this goal, we model performance antipatterns as logical predicates and we build an engine, based on such predicates, aimed at detecting performance antipatterns in an XML representation of the software system. Finally, we show the approach at work on a case study.

Experimenting different software architectures performance techniques: a case study

In this paper we describe our experience in performance analysis of the software architecture of the NICE ease study which is responsible for providing several secure communications in a naval communication system. We applied two complementary techniques, one based on stochastic process algebras and one based on simulation, in order to derive some performance indices at the software architectural level. The case study analysis allows us to point out the relative merit of the considered techniques including the performance model derivation, the type of analysis and performance results that we can carry out, and the feedback at the design level, e.g. performance results interpretation that we obtain. Finally, we discuss how to take advantage of the integration of different techniques in software architecture performance analysis.

Digging into UML models to remove performance antipatterns

Performance antipatterns have been informally defined and characterized as bad practices in software design that can originate performance problems. Such special type of patterns can involve static and dynamic aspects of software as well as deployment features. It has been shown that quite often the inability to meet performance requirements is due to the presence of antipatterns in the software design. However the problem of formally defining antipatterns and automatically detect them within a design model has not been investigated yet. In this paper we examine this problem within the UML context and show how performance antipatterns can be defined and detected in UML models by mean of OCL. A case study in UML annotated with the MARTE profile is presented where, after a performance analysis that shows unsatisfactory results, performance antipatterns are detected through an OCL engine. The identification of an antipattern suggests the architectural alternatives that can remove that specific problem. We show in our example that the removal of a certain antipattern actually allows to overcome a specific performance problem.

Model-based system reconfiguration for dynamic performance management

Recently, growing attention focused on run-time management of Quality of Service (QoS) of complex software systems. In this context, system reconfiguration is considered a useful technique to manage QoS. Several reconfiguration approaches to performance management exist that help systems to maintain performance requirements at run time. However, many of them use prefixed strategies that are in general coded in the application or in the reconfiguration framework.In this work we propose a framework to manage performance of software systems at run time based on monitoring and model-based performance evaluation. The approach makes use of software architectures as abstractions of the managed system to avoid unnecessary details that can heavily affect the model evaluation in terms of complexity and resolution time.

A Development Process for Self-adapting Service Oriented Applications

Software services in the near ubiquitous future will need to cope with variability, as they are deployed on an increasingly large diversity of computing platforms, operate in different execution environments, and communicate through Beyond 3G (B3G) networks. Heterogeneity of the underlying communication and computing infrastructure, physical mobility of platform devices, and continuously evolving requirements claim for services to be adaptable according to the context changes without degrading their quality. Supporting the development and execution of software services in this setting raises numerous challenges that involve languages, methods and tools. However these challenges taken in isolation are not new in the service domain. Integrated solutions to these challenges are the main targets of the IST PLASTIC project. In this paper we introduce the PLASTIC development process model for self-adapting context-aware services, in which we propose model-based solutions to address the main issues of this domain in a comprehensive way. We instantiate the process model by providing methodologies to generate Quality of Service models and adaptable code from UML service models. All these methodologies are supported by an integrated framework which is based on an UML profile that we have defined for the PLASTIC domain.

Towards a model-driven infrastructure for runtime monitoring

In modern pervasive dynamic and eternal systems, software must be able to self-organize its structure and self-adapt its behavior to enhance its resilience and provide the desired quality of service. In this high-dynamic and unpredictable scenario, flexible and reconfigurable monitoring infrastructures become key instruments to verify at runtime functional and non-functional properties. In this paper, we propose a property-driven approach to runtime monitoring that is based on a comprehensive Property Meta-Model (PMM) and on a generic configurable monitoring infrastructure. PMM supports the definition of quantitative and qualitative properties in a machine-processable way making it possible to configure the monitors dynamically. Examples of implementation and applications of the proposed model-driven monitoring infrastructure are excerpted from the ongoing CONNECT European Project.

Software performance model-driven architecture

Model transformations in MDA mostly aim at stepping from a Platform Independent Model (PIM) to a Platform Specific Model (PSM) from a functional viewpoint. In order to develop high quality software products, non-functional attributes (such as performance) must be taken into account. In this paper we extend the canonical view of the MDA approach to embed additional types of models that allow to structure a Model Driven approach keeping into account performance issues. We define the relationships between MDA typical models and the newly introduced models, as well as relationships among the latter ones. In this extended framework new types of model-to-model transformations also need to be devised. We place an existing methodology for transforming software models into performance models within the scope of this framework.

Performance Antipatterns as Logical Predicates

The problem of interpreting the results of performance analysis is quite critical in the software performance domain. Mean values, variances, probability distributions are hard to interpret for providing feedback to software architects. Instead, what architects expect are solutions to performance problems, possibly in the form of architectural alternatives (e. g. split a software component in two components and re-deploy one of them). In a software performance engineering approach this path from analysis results to software alternatives still lacks of automation and is based on the skills and experience of analysts. In this paper we propose an automated approach for the performance feedback generation process based on performance antipatterns. To this aim, we model performance antipatterns as logical predicates and we provide a java engine, based on such predicates, that is able to detect performance antipatterns in an XML representation of the software system. Finally, we show the approach at work on a simple case study.