Harmonizing architectural decisions with component view models using reusable architectural knowledge transformations and constraints

Architectural design decisions (ADDs) have been used in recent years for capturing design rationale and documenting architectural knowledge (AK). However, various architectural design views still provide the most common means for describing and communicating architectural design. The evolution of software systems requires that both ADDs and architectural design views are documented and maintained, which is a tedious and time-consuming task in the long run. Also, in lack of a systematic and automated support for bridging between ADDs and architectural design views, decisions and designs tend to become inconsistent over time. In our proposal, we introduce a reusable AK transformation language for supporting the automated transformation of reusable AK knowledge to component-and-connector models, the architectural design view used most commonly today. In addition, reusable consistency checking rules verify the consistency between decisions and designs. We evaluate our approach in an industrial case study and show that it offers high reusability, provides automation, and can, in principle, deal with large numbers of recurring decisions.     

Managing architectural decision models with dependency relations, integrity constraints, and production rules

Software architects consider capturing and sharing architectural decisions increasingly important; many tacit dependencies exist in this architectural knowledge. Architectural decision modeling makes these dependencies explicit and serves as a foundation for knowledge management tools. In practice, however, text templates and informal rich pictures rather than models are used to capture the knowledge; a formal definition of model entities and their relations is missing in the current state of the art. In this paper, we propose such a formal definition of architectural decision models as directed acyclic graphs with several types of nodes and edges. In our models, architectural decision topic groups, issues, alternatives, and outcomes form trees of nodes connected by edges expressing containment and refinement, decomposition, and triggers dependencies, as well as logical relations such as (in)compatibility of alternatives. The formalization can be used to verify integrity constraints and to organize the decision making process; production rules and dependency patterns can be defined. A reusable architectural decision model supporting service-oriented architecture design demonstrates how we use these concepts. We also present tool support and give a quantitative evaluation.     

Documenting after the fact: Recovering architectural design decisions

Software architecture documentation helps people in understanding the software architecture of a system. In practice, software architectures are often documented after the fact, i.e. they are maintained or created after most of the design decisions have been made and implemented. To keep the architecture documentation up-to-date an architect needs to recover and describe these decisions.This paper presents ADDRA, an approach an architect can use for recovering architectural design decisions after the fact. ADDRA uses architectural deltas to provide the architect with clues about these design decisions. This allows the architect to systematically recover and document relevant architectural design decisions. The recovered architectural design decisions improve the documentation of the architecture, which increases traceability, communication, and general understanding of a system.     

架构设计决策管理工具的研究与设计

目前的架构设计决策隐含于最终架构制品中,导致了涉众交流困难、演化代价高、难以复用等问题。针对上述问题,通过分析架构设计决策的属性及决策制定过程,提出一种描述设计决策与其他外部元素之间关系的元模型,在此基础上设计一个结合编码化和人际化的管理策略的架构设计决策管理工具,实现对设计决策的显式编档、管理和复用。     

Past and future of software architectural decisions – A systematic mapping study

ContextThe software architecture of a system is the result of a set of architectural decisions. The topic of architectural decisions in software engineering has received significant attention in recent years. However, no systematic overview exists on the state of research on architectural decisions.ObjectiveThe goal of this study is to provide a systematic overview of the state of research on architectural decisions. Such an overview helps researchers reflect on previous research and plan future research. Furthermore, such an overview helps practitioners understand the state of research, and how research results can help practitioners in their architectural decision-making.MethodWe conducted a systematic mapping study, covering studies published between January 2002 and January 2012. We defined six research questions. We queried six reference databases and obtained an initial result set of 28,895 papers. We followed a search and filtering process that resulted in 144 relevant papers.ResultsAfter classifying the 144 relevant papers for each research question, we found that current research focuses on documenting architectural decisions. We found that only several studies describe architectural decisions from the industry. We identified potential future research topics: domain-specific architectural decisions (such as mobile), achieving specific quality attributes (such as reliability or scalability), uncertainty in decision-making, and group architectural decisions. Regarding empirical evaluations of the papers, around half of the papers use systematic empirical evaluation approaches (such as surveys, or case studies). Still, few papers on architectural decisions use experiments.ConclusionOur study confirms the increasing interest in the topic of architectural decisions. This study helps the community reflect on the past ten years of research on architectural decisions. Researchers are offered a number of promising future research directions, while practitioners learn what existing papers offer.     

以决策为中心的软件体系结构设计方法

提出针对体系结构层次设计的决策抽象和问题分解原则,以及基于该原则的一种以决策为中心的体系结构设计方法.该方法从决策的视角对体系结构进行建模,并通过一个从导出体系结构关键问题到对体系结构方案决策的过程完成设计,还在其中实现了候选体系结构方案的自动合成以及设计决策与理由的捕捉.这种以决策为中心的方法切合体系结构层次的特点,降低了体系结构设计的复杂性和设计决策与理由捕捉的代价.     

Streamlining patient consultations for sleep disorders with a knowledge-based CDSS

ObjectivesThis paper examines the workflow of sleep physicians during a patient consultation and how an innovative clinical decision support system (CDSS) provides efficiency and effectiveness gains.MethodsThe CDSS tools consisted of two input applications for patient data, with a knowledge based decision support system developed participatively with physicians and an international panel. An argument tree approach was used to produce diagnostic explanations and an evidence-based report for the physician using medically correct and shared terminology. A usability evaluation using a qualitative approach was carried out to ensure that the CDSS met the physicians׳ information needs, as well as the wider needs of a Sleep Investigation Unit.ResultsThe physicians found the CDSS both useful and usable with clear applications in triage and diagnostic decision-making, and in patient education.ConclusionThe CDSS both reduces the time and number of visits needed for consultations, and helps focus consultation on better individual patient care through informed explanation of diagnostic and treatment decisions.     

Classifying architectural constraints as a basis for software quality assessment

Architectural styles and patterns have been studied since the inception of software architecture as a discipline. We generalise architectural styles, patterns and similar concepts by introducing the notion of architectural constraints. An architectural constraint is a vehicle for the reuse of architectural design knowledge and for the improvement of software quality. It may be used for improving architectural analyses of quality characteristics of the software system to be realised. We present the method for surveying the literature on architectural constraint concepts, and provide a taxonomy covering various definitions of architectural styles and patterns.     

An expert survey on kinds,influence factors and documentation of design decisions in practice

Support for capturing architectural knowledge has been identified as an important research challenge. As the basis for an approach to recovering design decisions and capturing their rationale, we performed an expert survey in practice to gain insights into the different kinds, influence factors, and sources for design decisions and also into how they are currently captured in practice. The survey was conducted with 25 software architects, software team leads, and senior developers from 22 different companies in 10 different countries with more than 13 years of experience in software development on average. The survey confirms earlier work by other authors on design decision classification and influence factors, and also identifies additional kinds of decisions and influence factors not mentioned in previous work. In addition, we gained insight into the practice of capturing, the relative importance of different decisions and influence factors, and into potential sources for recovering decisions.     

Semi-automated architectural abstraction specifications for supporting software evolution

In this paper we present an approach for supporting the semi-automated architectural abstraction of architectural models throughout the software life-cycle. It addresses the problem that the design and implementation of a software system often drift apart as software systems evolve, leading to architectural knowledge evaporation. Our approach provides concepts and tool support for the semi-automatic abstraction of architecture component and connector views from implemented systems and keeping the abstracted architecture models up-to-date during software evolution. In particular, we propose architecture abstraction concepts that are supported through a domain-specific language (DSL). Our main focus is on providing architectural abstraction specifications in the DSL that only need to be changed, if the architecture changes, but can tolerate non-architectural changes in the underlying source code. Once the software architect has defined an architectural abstraction in the DSL, we can automatically generate architectural component views from the source code using model-driven development (MDD) techniques and check whether architectural design constraints are fulfilled by these models. Our approach supports the automatic generation of traceability links between source code elements and architectural abstractions using MDD techniques to enable software architects to easily link between components and the source code elements that realize them. It enables software architects to compare different versions of the generated architectural component view with each other. We evaluate our research results by studying the evolution of architectural abstractions in different consecutive versions of five open source systems and by analyzing the performance of our approach in these cases.     

Architectural knowledge discovery with latent semantic analysis: Constructing a reading guide for software product audits

Architectural knowledge is reflected in various artifacts of a software product. In a software product audit this architectural knowledge needs to be uncovered and its effects assessed in order to evaluate the quality of the software product. A particular problem is to find and comprehend the architectural knowledge that resides in the software product documentation. In this article, we discuss how the use of a technique called Latent Semantic Analysis can guide auditors through the documentation to the architectural knowledge they need. We validate the use of Latent Semantic Analysis for discovering architectural knowledge by comparing the resulting vector-space model with the mental model of documentation that auditors possess.     

The Decision View's Role in Software Architecture Practice

A decision view provides a useful complement to the traditional sets of architectural views and viewpoints. It gives an explanatory perspective that illuminates the reasoning process itself and not solely its results. The decision view documents aspects of the architecture that are hard to reverse-engineer from the software itself and that are often left tacit. The decision view and the decisions that it captures embody high-level architectural knowledge that can be transferred to other practitioners and merged when systems are merged, and they offer useful support for maintaining large, long-lived software-intensive systems. This article leads readers through a succession of epiphanies: from design to architecture, then architecture representation to architecture design methods, and finally to architectural design decisions.     

Have a look around: the effect of physical environments on risk behaviour in work-related versus non-work related decision-making tasks

Abstract

Due to ubiquitous computing, knowledge workers do not only work in typical work-associated environments (e.g. the office) but also wherever it best suits their schedule or preferences (e.g. the park). In two experiments using laboratory and field methods, we compared decision making in work and non-work environments. We hypothesised that participants make riskier work-related decisions when in work-associated environments and riskier non-work-related decisions in non-work-associated environments. Therefore, if environment (work vs. non-work) and decision-making task (work-related vs. non-work-related) are incongruent, then risk-taking should be lower, as the decision maker might feel the situation is unusual or inappropriate. Although results do not reveal that work-associated environments generally encourage riskier work-related decisions (and likewise for non-work), we found environmental effects on decision making when including mood as a moderator.

Practitioner summary: Mobile workers are required to make decisions in various environments. We assumed that decisions are more risky when they are made in a fitting environment (e.g. work-related decisions in work environments). Results of the two experiments (laboratory and field) only show an environmental effect when mood is included as a moderator.     

Utilizing architectural styles to enhance the adaptation support of middleware platforms

ContextModern middleware platforms provide the applications deployed on top of them with facilities for their adaptation. However, the level of adaptation support provided by the state-of-the-art middleware solutions is often limited to dynamically loading and off-loading of software components. Therefore, it is left to the application developers to handle the details of change such that the system’s consistency is not jeopardized.ObjectiveWe aim to change the status quo by providing the middleware facilities necessary to ensure the consistency of software after adaptation. We would like these facilities to be reusable across different applications, such that the middleware can streamline the process of achieving safe adaptation.MethodOur approach addresses the current shortcomings by utilizing the information encoded in a software system’s architectural style. This information drives the development of reusable adaptation patterns. The patterns specify both the exact sequence of changes and the time at which those changes need to occur. We use the patterns to provide advanced adaptation support on top of an existing architectural middleware platform.ResultsOur experience shows the feasibility of deriving detailed adaptation patterns for several architectural styles. Applying the middleware to adapt two real-world software systems shows the approach is effective in consistently adapting these systems without jeopardizing their consistency.ConclusionWe conclude the approach is effective in alleviating the application developers from the responsibility of managing the adaptation process at the application-level. Moreover, we believe this study provides the foundation for changing the way adaptation support is realized in middleware solutions.     

An empirical investigation of architectural prototyping

Architectural prototyping is the process of using executable code to investigate stakeholders’ software architecture concerns with respect to a system under development. Previous work has established this as a useful and cost-effective way of exploration and learning of the design space of a system and in addressing issues regarding quality attributes, architectural risks, and the problem of knowledge transfer and conformance. However, the actual industrial use of architectural prototyping has not been thoroughly researched so far. In this article, we report from three studies of architectural prototyping in practice. First, we report findings from an ethnographic study of practicing software architects. Secondly, we report from a focus group on architectural prototyping involving architects from four companies. And, thirdly, we report from a survey study of 20 practicing software architects and software developers. Our findings indicate that architectural prototyping plays an important and frequent role in resolving problems experimentally, but less so in exploring alternative solutions. Furthermore, architectural prototypes include end-user or business related functionality rather than purely architectural functionality. Based on these observations we provide recommendations for effective industrial architectural prototyping.     

Assessing practical usefulness and performance of the PREDIQT method: An industrial case study

ContextWhen adapting a system to new usage patterns, processes or technologies, it is necessary to foresee the implications of the architectural design changes on system quality. Examination of quality outcomes through implementation of the different architectural design alternatives is often unfeasible. We have developed a method called PREDIQT with the aim to facilitate model-based prediction of impacts of architectural design changes on system quality. A recent case study indicated feasibility of the PREDIQT method when applied on a real-life industrial system. The promising results encouraged further and more structured evaluation of PREDIQT.ObjectiveThis paper reports on the experiences from applying the PREDIQT method in a second and more recent case study – on a real-life industrial system from another domain and with different system characteristics, as compared to the previous case study. The objective was to evaluate the method in a fully realistic setting and with respect to carefully defined criteria.MethodThe case study conducted the first two phases of PREDIQT in their entirety, while the last (third) phase was partially covered. In addition, the method was assessed through a thought experiment-based evaluation of predictions and a postmortem review. All prediction models were developed during the analysis and the entire target system was analyzed in a fully realistic setting.ResultsThe evaluation argues that the prediction models are sufficiently expressive and comprehensible. It is furthermore argued that PREDIQT: facilitates predictions such that informed decisions can be made; is cost-effective; and facilitates knowledge management.ConclusionThe experiences and results obtained indicate that the PREDIQT method can be carried out with limited resources, on a real-life system, and result in useful predictions. Furthermore, the observations indicate that the method, particularly its process, facilitates understanding of the system architecture and its quality characteristics, and contributes to structured knowledge management.     

Tradeoff and Sensitivity Analysis in Software Architecture Evaluation Using Analytic Hierarchy Process

Software architecture evaluation involves evaluating different architecture design alternatives against multiple quality-attributes. These attributes typically have intrinsic conflicts and must be considered simultaneously in order to reach a final design decision. AHP (Analytic Hierarchy Process), an important decision making technique, has been leveraged to resolve such conflicts. AHP can help provide an overall ranking of design alternatives. However it lacks the capability to explicitly identify the exact tradeoffs being made and the relative size of these tradeoffs. Moreover, the ranking produced can be sensitive such that the smallest change in intermediate priority weights can alter the final order of design alternatives. In this paper, we propose several in-depth analysis techniques applicable to AHP to identify critical tradeoffs and sensitive points in the decision process. We apply our method to an example of a real-world distributed architecture presented in the literature. The results are promising in that they make important decision consequences explicit in terms of key design tradeoffs and the architecture's capability to handle future quality attribute changes. These expose critical decisions which are otherwise too subtle to be detected in standard AHP results. Liming Zhu is a PHD candidate in the School of Computer Science and Engineering at University of New South Wales. He is also a member of the Empirical Software Engineering Group at National ICT Australia (NICTA). He obtained his BSc from Dalian University of Technology in China. After moving to Australia, he obtained his MSc in computer science from University of New South Wales. His principle research interests include software architecture evaluation and empirical software engineering. Aybüke Aurum is a senior lecturer at the School of Information Systems, Technology and Management, University of New South Wales. She received her BSc and MSc in geological engineering, and MEngSc and PhD in computer science. She also works as a visiting researcher in National ICT, Australia (NICTA). Dr. Aurum is one of the editors of “Managing Software Engineering Knowledge”, “Engineering and Managing Software Requirements” and “Value-Based Software Engineering” books. Her research interests include management of software development process, software inspection, requirements engineering, decision making and knowledge management in software development. She is on the editorial boards of Requirements Engineering Journal and Asian Academy Journal of Management. Ian Gorton is a Senior Researcher at National ICT Australia. Until Match 2004 he was Chief Architect in Information Sciences and Engineering at the US Department of Energy's Pacific Northwest National Laboratory. Previously he has worked at Microsoft and IBM, as well as in other research positions. His interests include software architectures, particularly those for large-scale, high-performance information systems that use commercial off-the-shelf (COTS) middleware technologies. He received a PhD in Computer Science from Sheffield Hallam University. Dr. Ross Jeffery is Professor of Software Engineering in the School of Computer Science and Engineering at UNSW and Program Leader in Empirical Software Engineering in National ICT Australia Ltd. (NICTA). His current research interests are in software engineering process and product modeling and improvement, electronic process guides and software knowledge management, software quality, software metrics, software technical and management reviews, and software resource modeling and estimation. His research has involved over fifty government and industry organizations over a period of 15 years and has been funded from industry, government and universities. He has co-authored four books and over one hundred and twenty research papers. He has served on the editorial board of the IEEE Transactions on Software Engineering, and the Wiley International Series in Information Systems and he is Associate Editor of the Journal of Empirical Software Engineering. He is a founding member of the International Software Engineering Research Network (ISERN). He was elected Fellow of the Australian Computer Society for his contribution to software engineering research.     

Mining Patterns from Change Logs to Support Reuse-Driven Evolution of Software Architectures

Modern software systems are subject to a continuous evolution under frequently varying requirements and changes in systems’ operational environments. Lehman’s law of continuing change demands for long-living and continuously evolving software to prolong its productive life and economic value by accommodating changes in existing software. Reusable knowledge and practices have proven to be successful for continuous development and evolution of the software effectively and efficiently. However, challenges such as empirical acquisition and systematic application of the reusable knowledge and practices must be addressed to enable or enhance software evolution. We investigate architecture change logs — mining histories of architecture-centric software evolution — to discover change patterns that 1) support reusability of architectural changes and 2) enhance the efficiency of the architecture evolution process. We model architecture change logs as a graph and apply graph-based formalism (i.e., graph mining techniques) to discover software architecture change patterns. We have developed a prototype that enables tool-driven automation and user decision support during software evolution. We have used the ISO-IEC-9126 model to qualitatively evaluate the proposed solution. The evaluation results suggest that the proposed solution 1) enables the reusability of frequent architectural changes and 2) enhances the efficiency of architecture-centric software evolution process. The proposed solution promotes research efforts to exploit the history of architectural changes to empirically discover knowledge that can guide architecture-centric software evolution.     

A method to optimize the scope of a software product platform based on end-user features

ContextDue to increased competition and the advent of mass customization, many software firms are utilizing product families – groups of related products derived from a product platform – to provide product variety in a cost-effective manner. The key to designing a successful software product family is the product platform, so it is important to determine the most appropriate product platform scope related to business objectives, for product line development.AimThis paper proposes a novel method to find the optimized scope of a software product platform based on end-user features.MethodThe proposed method, PPSMS (Product Platform Scoping Method for Software Product Lines), mathematically formulates the product platform scope selection as an optimization problem. The problem formulation targets identification of an optimized product platform scope that will maximize life cycle cost savings and the amount of commonality, while meeting the goals and needs of the envisioned customers’ segments. A simulated annealing based algorithm that can solve problems heuristically is then used to help the decision maker in selecting a scope for the product platform, by performing tradeoff analysis of the commonality and cost savings objectives.ResultsIn a case study, PPSMS helped in identifying 5 non-dominated solutions considered to be of highest preference for decision making, taking into account both cost savings and commonality objectives. A quantitative and qualitative analysis indicated that human experts perceived value in adopting the method in practice, and that it was effective in identifying appropriate product platform scope.     

Application of knowledge-based approaches in software architecture: A systematic mapping study

ContextKnowledge management technologies have been employed across software engineering activities for more than two decades. Knowledge-based approaches can be used to facilitate software architecting activities (e.g., architectural evaluation). However, there is no comprehensive understanding on how various knowledge-based approaches (e.g., knowledge reuse) are employed in software architecture.ObjectiveThis work aims to collect studies on the application of knowledge-based approaches in software architecture and make a classification and thematic analysis on these studies, in order to identify the gaps in the existing application of knowledge-based approaches to various architecting activities, and promising research directions.MethodA systematic mapping study is conducted for identifying and analyzing the application of knowledge-based approaches in software architecture, covering the papers from major databases, journals, conferences, and workshops, published between January 2000 and March 2011.ResultsFifty-five studies were selected and classified according to the architecting activities they contribute to and the knowledge-based approaches employed. Knowledge capture and representation (e.g., using an ontology to describe architectural elements and their relationships) is the most popular approach employed in architecting activities. Knowledge recovery (e.g., documenting past architectural design decisions) is an ignored approach that is seldom used in software architecture. Knowledge-based approaches are mostly used in architectural evaluation, while receive the least attention in architecture impact analysis and architectural implementation.ConclusionsThe study results show an increased interest in the application of knowledge-based approaches in software architecture in recent years. A number of knowledge-based approaches, including knowledge capture and representation, reuse, sharing, recovery, and reasoning, have been employed in a spectrum of architecting activities. Knowledge-based approaches have been applied to a wide range of application domains, among which “Embedded software” has received the most attention.