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The quality of enterprise software applications plays a crucial role for the satisfaction of the users and the economic success of the enterprises. Software applications with unsatisfying performance and scalability are perceived by its users as low in quality, as less interesting and less attractive, and cause frustration when preventing the users from attaining their goals. This book proposes an approach for a recommendation system that enables developers who are novices in software perform.
Software development is replete with risks. Will the finished software run quickly enough? Will the underlying hardware and network infrastructure be sufficient? Will the system scale? You can now get the answers you need, up-front, in time to act. This book introduces Software Performance Engineering (SPE), a proven step-by-step methodology for predicting the development challenges and performance of any object-oriented system -- and for managing development to achieve performance objectives. Performance experts Connie Smith and Lloyd Williams show how to build quantitative models of software before it is built, analyzing performance based on proposed architecture and design. Learn how to elicit performance objectives, gather relevant data, and evaluate performance throughout development and the rest of the software lifecycle. For software engineers, developers, architects, analysts, performance specialists, project managers, and other IT professionals who want to deliver higher-performance object-oriented software systems.
In this work, the authors analysed the co-dependency between models and analyses, particularly the structure and interdependence of artefacts and the feature-based decomposition and composition of model-based analyses. Their goal is to improve the maintainability of model-based analyses. They have investigated the co-dependency of Domain-specific Modelling Languages (DSMLs) and model-based analyses regarding evolvability, understandability, and reusability.
Previously, software architects were unable to effectively and efficiently apply reusable knowledge (e.g., architectural styles and patterns) to architectural analyses. This work tackles this problem with a novel method to create and apply templates for reusable knowledge. These templates capture reusable knowledge formally and can efficiently be integrated in architectural analyses.
This work introduces architectural security analyses for detecting access violations and attack paths in software architectures. It integrates access control policies and vulnerabilities, often analyzed separately, into a unified approach using software architecture models. Contributions include metamodels for access control and vulnerabilities, scenario-based analysis, and two attack analyses. Evaluation demonstrates high accuracy in identifying issues for secure system development.
When complex IT systems are being developed, the usage of several programming and modelling languages can lead to inconsistencies that yield faulty designs and implementations. To address this problem, this work contributes a classification of consistency preservation challenges and an approach for preserving consistency. It is formalized using set theory and monitors changes to avoid matching and diffing problems. Three new languages that follow this preservation approach are presented.
Although tremendous progress has been made in Artificial Intelligence (AI), it entails new challenges. The growing complexity of learning tasks requires more complex AI components, which increasingly exhibit unreliable behaviour. In this book, we present a model-driven approach to model architectural safeguards for AI components and analyse their effect on the overall system reliability.
When models of a system change, analyses based on them have to be reevaluated in order for the results to stay meaningful. In many cases, the time to get updated analysis results is critical. This thesis proposes multiple, combinable approaches and a new formalism based on category theory for implicitly incremental model analyses and transformations. The advantages of the implementation are validated using seven case studies, partially drawn from the Transformation Tool Contest (TTC).