Software architecture design: evaluation and transformation

The application of AI technology in architectural software has brought various innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them, and analyzes the application of these technologies in architectural image recognition, generation, design optimization and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design. The application of AI technology in architectural software has brought numerous innovations and changes to the industry. By introducing convolutional neural networks and deep neural networks, architectural design software is expected to automatically identify and generate complex architectural images, optimize the design process, and provide intelligent design assistance. Through literature research, this paper aims to discuss the specific application of CNN and DNN in parametric design and the innovation brought by them; it also analyzes the application of these technologies in architectural image recognition, generation, design optimization, and other aspects. This paper aims to provide a comprehensive reference for researchers in related fields and promote the innovative application of AI technology in architectural design.

Context. Software systems play a pervasive role in people's lives. Since ethics in software systems is hardly ever considered as a first-class entity, its support of, or hindrance to, values of users and society is usually neglected. Addressing ethics requires both to consider the context in which a software system is used, and the fact that ethical values (e.g., social, cultural and personal) are intrinsically ambiguous and subjective. Software architecture and architecture design decision making are the right levels of abstraction to both consider such a context, and support reasoning about such subjectivities. Goal. We aim to embed ethical aspects in software architecture design decision making. We have studied the state of the art in ethics for software engineering, to identify the ethical aspects influencing software architecture design. We will use the learned ethical aspects to (i) support architecture design decision making with respect to ethics through proposing methods, models, and techniques, and (ii) conduct empirical studies to evaluate them in industrial practice. Method. We will adopt a design science approach for our research which includes three phases: (i) problem understanding, (ii) solution design, and (iii) solution validation. Results. Based on our previous literature study, we build models (and techniques) embedding the ethical aspects to be used in architecture design decision making. Also, we will apply design science research to use and validate these models in a method assisting practitioners and architects to embed ethical aspects in software architecture design.

This paper provides an introduction to the field of software engineering requires facility in architectural software design. The goal is to demonstrate the current state of the discipline and examine the ways in which architectural design can impact soft-ware design. Software architecture is used to describe a high level design methodology of large software systems. It provides the overall structure of a system in an abstract and structured fashion. A smart architectural demonstration holds the key to the effectiveness of a software architecture description and usage. This paper focuses on criterion to select appropriate architecture style for software system. It also gives overview of definition, goals and requirements of software architecture with various architecture styles, their benefits and applications. The authors have also described the requirements and goals of robotic software architecture. The proposal for layered robotic software architecture for a distributed system is also presented.

Metric-based Evaluation of Implemented Software Architectures

<p>The purpose of this study was to find out the challenges facing Machine Learning (ML) software development and create a design architecture and a workflow for successful deployment. Despite the promise in ML technology, more than 80% of ML software projects never make it to production. As a result, majority of companies around the world with investments in ML software are making significant losses. Current studies show that data scientists and software engineers are concerned by the challenges involved in these systems such as: limited qualified and experienced ML software experts, lack of collaboration between experts from the two domains, lack of published literature in ML software development using established platforms such as Django Rest Framework, as well as existence of cloud software tools that are difficult use. Several attempts have been made to address these issues such as: Coming up with new software models and architectures, frameworks and design patterns. However, with the lack of a clear breakthrough in overcoming the challenges, this study proposes to investigate further into the conundrum with the view of proposing an ML software design architecture and a development workflow. In the end, the study gives a conclusion on how the remedies provided helps to meet the objectives of study.</p>

Methodologies for the design of software architectures based on identified system requirements differ in procedure, phases, and artifacts. Furthermore, the consideration of functional and quality requirements during the design process leads to diverse software architecture models varying in their capability regarding adaptivity to new or changed user or quality requirements. The paper discusses a novel methodology for the design of software architecture for information systems based on user and quality requirements. The distinctiveness from methodologies discussed in the literature is given in the comprehensible and traceable deduction of a domain model for the software system architecture from user requirements. The methodology was evaluated and adapted iteratively in many R&D projects.

This paper illustrates an approach for architectural design of a Learning Management System (LMS), which is verifiable against the Learning Technology System Architecture (LTSA) conformance rules. We introduce a new method for software architectural design that extends the Unified Modeling Language (UML) component diagram with the formal architectural style of Acme, hence, combines the advantages of the visual appeal of a graphical method and preciseness of a formal method. We propose some new stereotypes for UML component-connector style to incorporate Acme style within UML. A UML meta-model for the design components is also proposed to elucidate the relationships between the components. We also propose a verification method to ensure that the design artifact is holding conformance with LTSA standard. The design process as well as the verification process entails additional knowledge about the domain, which is supplied by the domain Ontology. The LTSA conformance rules, written in natural language, are represented more formally with help of Conceptual Graph representation, before using them in the verification process. Finally, we introduce a verification method that tries to find out a design pattern in the architectural design that conforms to the particular conformance rule intended to check. The verification process also introduces a goodness measure of the conformance.

Software architecture involves a series of decisions based on many factors in a wide range of software development. Architects face recurring issues in different software architecture design, and to reduce huge cost and risks, software architecture decisions can rely on a set of idiomatic patterns commonly named architectural styles or patterns. Architectural pattern determines the vocabulary of components and connectors that are used in instances of the pattern together with a set of constraints to combine the two. Little contemporary data exists to document actual practices used by software professionals when selecting and incorporating architectural patterns for their projects in industry. Therefore, a comprehensive survey of software professionals was conducted to attempt to discover these practices. This exploratory survey and its quantitative results offer opportunities for further interpretation and comparison. Data from this survey are presented in this paper and include characteristics of projects, practices, organizations, and practitioners related to the usage of architectural patterns. Some of the notable findings include that architectural patterns are widely used in software projects with the Model–View–Controller being the most common. Despite reported difficulties in incorporating architectural patterns, the majority of the software professionals revealed that patterns were the most essential for completing the projects. The most difficult pattern to implement and the most expensive to adopt was the peer-to-peer, while the easiest was the client–server.

The problem of compounding the method of software architecture (SA) design with flexible techniques of production to assure software quality is discussed. The initial architecture decision is assessed and selected among the set of alternatives with applying of Analytical Hierarchy Process (AHP). Selected decision is implemented with flexible techniques. Quality characteristics of SA are corrected with applying the method of compensation by substitution for taking into account changes. The control of matching changed architecture to requirements is made with using of goal function that is built by the Group Method of Data Handling (GMDH).

The use of agents is spreading as a means to develop different kinds of software systems, among which we can find Intelligent Virtual Environments for Training. The agent community has already started to pay attention to software engineering issues to develop agent-oriented systems, but they are mainly focused on methodologies and, to some extent, design patterns. However, not much attention has been paid to software architecture for the moment. We compare two agent-based software architectures for Intelligent Virtual Environments for Training that are intended to be easily extended and modified. The first one was designed using an organizational approach recommended by some agent oriented methodologies. The second one is a redesign of the first architecture using more formal principles and methods of software architecture design. A comparison between both architectures highlights the need to pay more attention to software architecture design in this field.KeywordsVirtual EnvironmentMultiagent SystemSoftware ArchitectureIntelligent Tutoring SystemAgent PlatformThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Recently, more attention is paid to the researches and practices on how to use software architecture in software maintenance and evolution to reduce their complexity and cost. The key in such architecture-based maintenance and evolution is to recover software architecture from existing systems. Almost all studies on architecture recovery focus on analyzing the source code and other documents. Such recovered software architecture can hardly capture runtime states and behaviors of the system. At the same time, current work pays little attention on how to change the system directly via manipulating the recovered software architecture. This paper presents a novel approach to recovering software architecture from component based systems at runtime and changing the runtime systems via manipulating the recovered software architecture. Containing much more details than the designed software architecture, the recovered software architecture can accurately and thoroughly describe the actual states and behaviors of the runtime system. It can be described formally with the extension of traditional architecture description language, which enables the recovered software architecture to absorb the semantics embedded in the designed software architecture. The recovered software architecture can be represented as multiple views so as to help different users to control the complexity from different concerns. Based on the reflective ability of the component framework, the recovered software architecture is up-to-date at any time and changes made on it will immediately lead to the corresponding changes in the runtime system. The approach presented in this paper is demonstrated on PKUAS, a reflective J2EE (Java 2 Platform Enterprise Edition) application server, and the performance is also evaluated.

This paper presents an initial model for evaluating and improving the availability of a software architecture design. The model is implemented as a reasoning framework in the ArchE architecture expert system developed jointly with the Software Engineering Institute. To ensure continuous availability many automotive electronic control units (ECUs) employ an external watchdog running on a separate CPU to monitor the software running on the ECU. If the ECU has a failure that causes interruption of its functionality, the watchdog can detect this and reset the ECU to restore correct operation. The availability model can automatically evaluate the effectiveness of a watchdog design in the software architecture and can propose improvements to achieve better availability before implementation decisions are made. The model enables a quantitative analysis of system availability that can better guide software architecture and dependability design decisions and potentially reduce implementation and testing effort.

Currently, various industries around the world are advocating innovation, and the design of architectural spaces is no exception. However, the innovation of traditional architectural space design methods is not enough. In view of the problems of the traditional architectural space design methods, such as weak quantification, weak logic, and low level of science and technology, this paper used the particle swarm optimization algorithm in the data algorithm to study the architectural space design methods. This paper introduced the principles of architectural space design, studied some existing design methods and problems, and used particle swarm optimization algorithm to make some innovations in architectural space design methods. Experts and scholars were invited to score to verify the superiority of particle swarm optimization algorithm for architectural space design. The residents’ satisfaction rate with the building space design method using particle swarm optimization algorithm was more than 91.65%, and the average satisfaction rate of 20 residents was 93.2%. At the same time, the space experts who used the particle swarm optimization algorithm to design the building space design method scored more than 8.34 points. Innovative design of architectural space requires methods. Only by applying the right approach can the ideal design effect be achieved as quickly as possible to ensure the quality of the design.

Architectural styles represent composition patterns and constraints at the software architectural level and are targeted at families of systems with shared characteristics. While both style-specific and style-neutral modeling environments for software architectures exist, creation of such environments is expensive and frequently involves reinventing the wheel. This paper describes the rapid design of a style-neutral architectural modeling environment, ViSAC. ViSAC is based on Alfa, a framework for constructing style-based software architectures from architectural primitives, and is obtained by configuring Vanderbilt University's generic modeling environment (GME). Users can define their own styles in ViSAC and, in turn, use them to design software architectures. Moreover, ViSAC supports the hierarchical design of heterogeneous software architectures, i.e., using multiple styles. The rich user interface of GME and support for domain-specific semantics enable interactive design of well-formed styles and architectures.

Software architectures play a key role for the development and evolution of software systems because they have to enable their quality properties such as scalability, flexibility, and security. Software architectural decisions represent a transition from problem space with quality goals and requirements on one side to solution space with technical solutions on the other side. Technical solutions are reusable elements for the work of the architect as for example patterns, styles, frameworks and building blocks. For long-term evolution of the systems, an explicit mapping between goals and solutions is helpful for expressing design knowledge and fundamental decisions. Such a mapping has to bridge between the fields of requirements engineering, software architectural design, and software quality thus enabling reuse. In this paper the Goal Solution Scheme is discussed, which maps quality goals and goal refinements to architectural principles and solutions. The paper extends the approach from the previously discussed forward engineering to re-engineering activities thus covering evolutionary development processes. The evaluation of the approach has been performed in several case studies and projects including a large industrial one.