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.     

A time series tool to support the multi-criteria performance evaluation of rainfall-runoff models

A multi-criteria model evaluation protocol is presented to check the performance of rainfall-runoff models during model calibration and validation phases based on a high frequency (e.g. hourly, daily) river flow series. The multiple criteria or objectives are based on multiple and non-commensurable measures of information derived from river flow series by means of a number of sequential time series processing tasks. These include separation of the river flow series in subflows, split of the series in nearly independent quick and slow flow hydrograph periods, and the extraction of nearly independent peak and low flows. The protocol accounts for the statistical assumptions and requirements on independency and homoscedasticity of the model residuals, significantly advanced through the use of nearly independent flow values extracted from the flow series. Next to the separate evaluation of the subflow recessions, the quick and slow runoff peak and low values and event volumes, also the performance of the model in predicting extreme high and low flow statistics is validated. To support the time series processing tasks as well as the application of the multi-criteria model evaluation protocol, a Microsoft Excel-based tool (WETSPRO: Water Engineering Time Series PROcessing tool) has been developed. It is based on the assessment of graphical displays, which complement traditional goodness-of-fit statistics.     

II. Supporting models and applications

Baaed on TOC (Task Operating Characteristic) and ROC (Resource Operating Characteristic) curves (Braswell 1971), P(t) and R(t), a family of feasible curves are experimentally selected with parameter specifications for a and S. Additional models are developed for activity progress and resource utilization monitoring and control. A resource allocation method is developed and a Best 1'ath (JJP) strategy is presented to reprogramme progress of assignments and rates of resource expending. Task Progress (TP) and Rosource Depletion (RD) models are developed. Examples, and figures illustrate applications.     

Supporting the reconciliation of models of object behaviour

This paper presents Reconciliation+, a method which identifies overlaps between models of software systems behaviour expressed as UML object interaction diagrams (i.e., sequence and/or collaboration diagrams), checks whether the overlapping elements of these models satisfy specific consistency rules and, in cases where they violate these rules, guides software designers in handling the detected inconsistencies. The method detects overlaps between object interaction diagrams by using a probabilistic message matching algorithm that has been developed for this purpose. The guidance to software designers on when to check for inconsistencies and how to deal with them is delivered by enacting a built-in process model that specifies the consistency rules that can be checked against overlapping models and different ways of handling violations of these rules. Reconciliation+ is supported by a toolkit. It has also been evaluated in a case study. This case study has produced positive results which are discussed in the paper.     

Event-B patterns and their tool support

Event-B has given developers the opportunity to construct models of complex systems that are correct-by-construction. However, there is no systematic approach, especially in terms of reuse, which could help with the construction of these models. We introduce the notion of design patterns within the framework of Event-B to shorten this gap. Our approach preserves the correctness of the models, which is critical in formal methods and also reduces the proving effort. Within our approach, an Event-B design pattern is just another model devoted to the formalisation of a typical sub-problem. As a result, we can use patterns to construct a model which can subsequently be used as a pattern to construct a larger model. We also present the interaction between developers and the tool support within the associated RODIN Platform of Event-B. The approach has been applied successfully to some medium-size industrial case studies.     

Expectations,learning and empirical macroeconomic models

The developments in the treatment of expectations in empirical macroeconomic models that have taken place over the last 30 years are surveyed. The main concern is to focus on the implications of expectation effects in the practical use of models, i.e. in forecasting and policy analysis, rather than to consider either the theoretical literature or the literature on econometric estimation and identification, both of which are already well surveyed. The general development in expectations models is discussed first. Then the literature on linear models is considered and the development of expectations effects to large nonlinear econometric models is examined.     

Deriving software architectural models from requirements models for adaptive systems: the STREAM-A approach

Some quality attributes are known to have an impact on the overall architecture of a system, so that they are required to be properly handled from the early beginning of the software development. For example, adaptability is a key concern for autonomic and adaptive systems, which brings to them the capability to alter their behavior in response to changes on their surrounding environments. In this paper, we propose a Strategy for Transition between Requirements and Architectural Models for Adaptive systems (STREAM-A). In particular, we use goal models based on the i* (i-Star) framework to support the design and evolution of systems that require adaptability. To obtain software architectures for such systems, the STREAM-A approach uses model transformations from i* models to architectural models expressed in Acme. Both the requirements and the architectural model are refined to accomplish the adaptability requirement.     

软件构件化生产集成支撑平台研发

对大型软件构件化生产过程中的构件识别与映射、构件建模、构件测试和构件评估进行了研究,报告了软件构件化研究和实践现状和存在的问题,提出了一套基于业务构件组装开发支撑平台实现框架,详细阐述了构件功能之间的关联关系,给出了构件化组装技术原理和实现过程,阐述了业务构件框架与原子业务构件组装过程,为基于业务构件组装的软件构件化生产提供了一种新的解决方案。     

Supporting concurrent ontology development: Framework, algorithms and tool

We propose a novel approach to facilitate the concurrent development of ontologies by different groups of experts. Our approach adapts Concurrent Versioning, a successful paradigm in software development, to allow several developers to make changes concurrently to an ontology. Conflict detection and resolution are based on novel techniques that take into account the structure and semantics of the ontology versions to be reconciled by using precisely-defined notions of structural and semantic differences between ontologies and by extending state-of-the-art ontology debugging and repair techniques. We also present ContentCVS, a system that implements our approach, and a preliminary empirical evaluation which suggests that our approach is both computationally feasible and useful in practice.     

Distribution-free consistency of empirical risk minimization and support vector regression

In this paper, we focus on the generalization ability of the empirical risk minimization technique in the framework of agnostic learning, and consider the support vector regression method as a special case. We give a set of analytic conditions that characterize the empirical risk minimization methods and their approximations that are distribution-free consistent. Then utilizing the weak topology of the feature space, we show that the support vector regression, possibly with a discontinuous kernel, is distribution-free consistent. Moreover, a tighter generalization error bound is shown to be achieved in certain cases if the value of the regularization parameter grows as the sample size increases. The results carry over to the ν-support vector regression.     

Generating 3D architectural models based on hand motion and gesture

This paper presents a novel method for rapidly generating 3D architectural models based on hand motion and design gestures captured by a motion capture system. A set of sign language-based gestures, architectural hand signs (AHS), has been developed. AHS is performed on the left hand to define various “components of architecture”, while “location, size and shape” information is defined by the motion of Marker-Pen on the right hand. The hand gestures and motions are recognized by the system and then transferred into 3D curves and surfaces correspondingly. This paper demonstrates the hand gesture-aided architectural modeling method with some case studies.     

Guilt-based handling of software performance antipatterns in palladio architectural models

Antipatterns are conceptually similar to patterns in that they document recurring solutions to common design problems. Software performance antipatterns document common performance problems in the design as well as their solutions. The definition of performance antipatterns concerns software properties that can include static, dynamic, and deployment aspects. To make use of such knowledge, we propose an approach that helps software architects to identify and solve performance antipatterns. Our approach provides software performance feedback to architects, since it suggests the design alternatives that allow overcoming the detected performance problems.The feedback process may be quite complex since architects may have to assess several design options before achieving the architectural model that best fits the end-user expectations. In order to optimise such process we introduce a ranking methodology that identifies, among a set of detected antipatterns, the “guilty” ones, i.e. the antipatterns that more likely contribute to the violation of specific performance requirements. The introduction of our ranking process leads the system to converge towards the desired performance improvement by discarding a consistent part of design alternatives. Four case studies in different application domains have been used to assess the validity of the approach.     

Comprehending object and process models: an empirical study

We report the results of an empirical study comparing user comprehension of object oriented (OO) and process oriented (PO) models. The fundamental difference is that while OO models tend to focus on structure, PO models tend to emphasize behaviour or processes. Proponents of the OO modeling approach argue that it lends itself naturally to the way humans think. However, evidence from research in cognitive psychology and human factors suggests that human problem solving is innately procedural. Given these conflicting viewpoints, we investigate empirically if OO models are in fact easier to understand than PO models. But, as suggested by the theory of cognitive fit, model comprehension may be influenced by task-specific characteristics. We therefore compare OO and PO models based on whether the comprehension activity involves: 1) only structural aspects, 2) only behavioral aspects, or 3) a combination of structural and behavioral aspects. We measure comprehension through subjects' responses to questions designed along these three dimensions. Results show that for most of the simple questions, no significant difference was observed insofar as model comprehension is concerned. For most of the complex questions, however, the PO model was found to be easier to understand than the OO model. In addition to describing the process and the outcomes of the experiments, we present the experimental method employed as a viable approach for conducting research into various phenomena related to the efficacy of alternative systems analysis and design methods. We also identify areas where future research is necessary, along with a recommendation of appropriate research methods for empirical examination     

Tool support for the design and management of context models

A central task in the development of context-aware applications is the modeling and management of complex context information. In this paper, we present the NexusEditor, which can ease this task by providing a graphical user interface to design schemas for spatial and technical context models, interactively create queries, send them to a server and visualize the results. One main contribution is to show how schema awareness can improve such a tool: The NexusEditor dynamically parses the underlying data model and provides additional syntactic checks, semantic checks, and short-cuts based on the schema information. Furthermore, the tool helps to design new schema definitions based on the existing ones, which is crucial for an iterative and user-centric development of context-aware applications. Finally, it provides interfaces to existing information spaces and visualization tools for spatial data like GoogleEarth.     

Bayesian analysis of empirical software engineering cost models

Many parametric software estimation models have evolved in the last two decades (L.H. Putnam and W. Myers, 1992; C. Jones, 1997; R.M. Park et al., 1992). Almost all of these parametric models have been empirically calibrated to actual data from completed software projects. The most commonly used technique for empirical calibration has been the popular classical multiple regression approach. As discussed in the paper, the multiple regression approach imposes a few assumptions frequently violated by software engineering datasets. The paper illustrates the problems faced by the multiple regression approach during the calibration of one of the popular software engineering cost models, COCOMO II. It describes the use of a pragmatic 10 percent weighted average approach that was used for the first publicly available calibrated version (S. Chulani et al., 1998). It then moves on to show how a more sophisticated Bayesian approach can be used to alleviate some of the problems faced by multiple regression. It compares and contrasts the two empirical approaches, and concludes that the Bayesian approach was better and more robust than the multiple regression approach