Quality attributes use in architecture design decision methods: research and practice

Global software development (GSD) is considered as the coordinated activities of software development that are geographically and temporally distributed. The management of architectural knowledge, specifically, architectural design decisions (ADDs), becomes important in GSD due to the geographical, temporal, and cultural challenges in global environments. Based on our previous work on ADD management in localized software development, we present five ADD paradigms for GSD projects with different organizational structures. We also investigate the benefits and the challenges of these ADD paradigms by conducting an evaluation of the paradigms using extensive archived semi-structured interview data from industrial GSD projects. We aim to provide a fundamental framework for managing ADD documentation and evolution in GSD, as well as offer useful insights into managing architectural knowledge in a global setting.

The benefits of a software system are assessable only relative to the business goals the system has been developed to serve. In turn, these benefits result from interactions between the system's functionality and its quality attributes (such as performance, reliabilty and security). Its quality attributes are, in most cases, dictated by its architectural design decisions. Therefore, we argue in this paper that the software architecture is the crucial artifact to study in making design tradeoffs and in performing cost-benefit analyses. A substantial part of such an analysis is in determining the level of uncertainty with which we estimate both costs and benefits. In this paper we offer an architecture-centric approach to the economic modeling of software design decision making called CBAM (Cost Benefit Analysis Method), in which costs and benefits are traded off with system quality attributes. We present the CBAM, the early results from applying this method in a large-scale case study, and discuss the application of more sophisticated economic models to software decision making.

In software architectures, architectural design decisions (ADDs) strongly influence the quality of the resulting software system. Wrong decisions lead to low-quality systems and are difficult to repair later on in the development process. As of today, little is known about the impact of certain ADDs for the development of architectures for blockchain-based systems. Thus, it is difficult to predict the outcome of certain ADDs when developing architectures for such systems. In the following, we propose a simulation-based approach for blockchain architectures in which the impact of certain ADDs on certain quality attributes can be simulated. To this end, we first implemented a simulation environment for blockchain architectures. The simulation environment was then used to execute a series of experiments from which we derived a set of hypotheses about the impact of certain ADDs on quality attributes for blockchain architectures. Finally, we tested the hypotheses using statistical analyses and derived an empirical model for blockchain architectures based on the outcome of the analysis. The model can be used by architects to predict the effect of certain decisions in the design of blockchain architectures before implementing them.

In software architecture design, we explore design alternatives and make decisions about adoption or rejection of a design from a web of complex and often uncertain information. Different architectural design decisions may lead to systems that satisfy the same set of functional requirements but differ in certain quality attributes. In this paper, we propose a Bayesian Network based approach to rational architectural design. Our Bayesian Network helps software architects record and make design decisions. We can perform both qualitative and quantitative analysis over the Bayesian Network to understand how the design decisions influence system quality attributes, and to reason about rational design decisions. We use the KWIC (Key Word In Context) example to illustrate the principles of our approach.

An effective software design should ensure that all the quality requirements of a system of interest are supported. As the architecture of a software system can be seen as a set of architectural design decisions (ADDs), the identification of design issues and the choice of design alternatives heavily impact the quality of software systems. This is especially challenging in service orientation for which students need to change their mindset from system design to service-oriented design. In this paper, we present a template driven approach for documenting quality-driven ADDs in an educational setting. We next report on our experience with the usage of the template in a service-oriented software design Master course given over the past three years. We found that the template not only offers a framework guiding the students in their design but also encourages them to make sound ADDs, which leads to a service-oriented design with higher quality.

Software architecture can be represented as a set of design decisions. Exploring and analyzing architectural design decisions are difficult due to how the decisions are represented and displayed. We describe four visualization aspects that apply to architectural design decision exploration and analysis: 1) tabular listing; 2) decision structure visualization; 3) decision chronology visualization; and 4) decision impact visualization. These aspects address some situations where visualization helps people understand and utilize decisions.KeywordsDesign DecisionDecision StructureDecision AttributeDecision InformationNode CircleThese 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.

This paper presents a framework based on the analytic hierarchy process (AHP) methodology to select the most appropriate set of Knowledge Management (KM) tools to support the innovation processes in organizations. The framework builds on the theoretical foundations underlying organizational KM to identify key KM processes enabling innovation. The AHP is a multi‐criteria decision support technique that can be used to analyse and compare those KM tools that best support innovation processes. Organizations can select the most suitable KM tool by using the proposed framework to identify gaps and overlaps in the extent to which the capabilities provided and utilized by their current KM tools portfolio meet the KM needs of the organization to sustain the innovation. The main contributions of this work are the list of KM processes to support an innovation activity and the hierarchy of importance of such processes able to support the selection process of a KM tool. The framework can be of use to managers and other practitioners because of its ease of implementation. An illustrative example of a case study for the application of the framework is provided. Copyright © 2011 John Wiley & Sons, Ltd.

System quality attributes (QAs) are often considered as the most important decision drivers. In this paper, motivated by the decision making in a smart-city software ecosystem, we extend our previous approach that integrates reusable architectural design decisions (ADDs) with the QAs, by integrating tactics that support quality-driven decision making. In addition, we present an approach that enables system evolution, based on controlled and adaptable decision making and utilizing real data obtained during system monitoring. The approach integrates the previous approach that uses tactics with the existing model-driven development paradigm and the corresponding tools.

10 years of software architecture knowledge management: Practice and future

Every software development organization strives for customer satisfaction. It is universally accepted that the success of software development lies in the clear understanding of the client requirements. During requirement elicitation and analysis stage, the system analyst identifies the functional and non-functional requirements from the customer. Security, usability, reliability, performance, scalability and supportability are the significant quality attributes of a software system. These quality attributes are also referred as non-functional requirements. Only a few functional and quality attributes requirement help to identify and shape the software architecture. A software system’s architecture is the set of prime design decisions made about the system. If the requirement influences the architectural design decision then, it is referred as Architecturally Significant Requirement (ASR). Identifying and specifying all the possible ASR are important tasks in the requirement elicitation and analysis stage.In this research, general problems that are faced while capturing and specifying ASR in requirement elicitation and analysis is studied. Among the different requirement elicitation techniques, use case diagram has been identified and enhanced to solve the problem of capturing and specifying ASR during the requirement elicitation and analysis phase

Building blockchain-based applications and deciding which elements of an architecture should employ blockchain technologies poses several challenges. Architectural design decisions have a strong impact on quality attributes such as privacy, operational cost, transparency, risk and user experience (UX). To deal with these challenges, we propose a structured approach using existing architectural concepts such as strategies, tactics and design patterns and illustrate their application using the Meta-Transaction design pattern. Meta-Transactions are cryptographically signed function calls (i.e. transactions) a user sends to a backend. The backend submits the transaction to the blockchain and pays the fees on behalf of the user. Due to the cryptographic signature, the backend is not able to manipulate the function name or its parameters, thus acting as a trustless proxy. Several other design patterns exist in the area of blockchain-oriented applications but it remains unclear how to decide which are suitable for a given use case and how quality attributes of the resulting system are affected. By using the Meta-Transaction design pattern as an example, this paper motivates why Blockchain Tactics and corresponding design patterns are necessary and help to structure best practices and common solutions for challenges of using blockchain technology.

Capturing and using design rationale is becoming a hot topic for software architects, as architectural design decisions are now considered first class entities that should be recorded and documented explicitly. Capturing such architecture knowledge has been underestimated for several years as architects have been only focused on documenting their architectures and neglecting the rationale that led to them. The importance of recording design rationale becomes enormous for maintenance and evolution activities, as design decisions can be replayed in order to avoid highly cost architecture recovery processes. Hence, in this work we describe how architecture design decisions can be captured and documented with specific tool support. We also provide effort estimation in capturing such knowledge and we compare this with architecture modeling efforts in order to analyze the viability of knowledge capturing strategies.

Designing and maintaining a software system’s architecture typically involve making numerous design decisions, each potentially affecting the system’s functional and nonfunctional properties. Understanding these design decisions can help inform future decisions and implementation choices and can avoid introducing regressions and architectural inefficiencies later. Unfortunately, design decisions are rarely well documented and are typically a lost artifact of the architecture creation and maintenance process. The loss of this information can thus hurt development. To address this shortcoming, we develop RecovAr, a technique for automatically recovering design decisions from the project’s readily available history artifacts, such as an issue tracker and version control repository. RecovAr uses state-of-the-art architectural recovery techniques on a series of version control commits and maps those commits to issues to identify decisions that affect system architecture. While some decisions can still be lost through this process, our evaluation on Hadoop and Struts, two large open-source systems with over 8 years of development each and, on average, more than 1 million lines of code, shows that RecovAr has the recall of 75% and a precision of 77%. Our work formally defines architectural design decisions and develops an approach for tracing such decisions in project histories. Additionally, the work introduces methods to classify whether decisions are architectural and to map decisions to code elements. Finally, our work contributes a methodology engineers can follow to preserve design-decision knowledge in their projects.

Software architecture forms the cornerstone for achieving and ensuring various software quality attributes. It encompasses the collected requirements of the product, serving as a blueprint that delineates quality features for all project stakeholders, along with methods for measurement and control. Despite the significant increase in IoT-based agricultural systems, there is a dearth of studies on the quality elements of their software architecture. To address this need, this study offers an overview of components and services tailored to address specific quality attributes pertinent to agriculture systems. It identifies, investigates, and presents quality attributes influencing the design of software architecture for IoT-based agriculture systems. This paper identified and discussed several quality attributes, including performance, scalability, flexibility, interoperability, productivity, extensibility, and security, and mapped them to corresponding components of the IoT-based agriculture software architecture. Also, several issues were identified and discussed for the software architecture quality of IoT-based agriculture systems, such as real-time processing and interoperability due to the various devices and protocols utilized in these systems. The findings of this study offer valuable insights for developing, executing, and refining IoT-based agricultural systems to fulfill the changing requirements of the agriculture industry.

When engineering complex software systems, the key Architectural Design Decisions (ADD) and the reasoning underlying those decisions need to be fully understood by all stakeholders. Achieving such understanding usually requires the use of ADD management tools. Most existing ADD management tools apply prescriptive ADD models and do not provide sufficient customizability. However, forcing architects to follow an ADD model that does not fit their specific needs can cause significant problems (e.g., extra cost is needed, and architects' willingness and motivation can negatively be affected). This research project aims at solving this issue by developing a highly customizable solution, which can enable practitioners to define ADD models according to their preferences and working situations. The detailed needs for ADD model customization will be identified by multiple case studies and semi-structured interviews; the proposed solution will be evaluated using different empirical research methods.