Knowledge based quality-driven architecture design and evaluation

Modelling and evaluating quality properties of software is of high importance, especially when our every day life depends on the quality of services produced by systems and devices embedded into our surroundings. This paper contributes to the body of research in quality and model driven software engineering. It does so by introducing; (1) a quality aware software architecting approach and (2) a supporting tool chain. The novel approach with supporting tools enables the systematic development of high quality software by merging benefits of knowledge modelling and management, and model driven architecture design enhanced with domain-specific quality attributes. The whole design flow of software engineering is semi-automatic; specifying quality requirements, transforming quality requirements to architecture design, representing quality properties in architectural models, predicting quality fulfilment from architectural models, and finally, measuring quality aspects from implemented source code. The semi-automatic design flow is exemplified by the ongoing development of a secure middleware for peer-to-peer embedded systems.     

Exploring Alternative Software Architecture Designs: A Planning Perspective

Software architecture designs give us blueprints to build systems, enabling key early decisions that can help us achieve a system's functional and quality-attribute requirements. Architectural decisions have far-reaching effects on development in terms of quality, time, and cost. Architects apply technical knowledge and experience to guide their decision making, choosing among multiple design solutions to find a reasonable balance of quality attributes such as performance, modifiability, or security. This is complex and time consuming because qualities can conflict and lead to trade-offs. A trade-off means that the improvement of one quality comes at the cost of degrading another for example, modifiability versus performance. The DesignBots framework supports architects in searching for design alternatives by capturing quality-attribute design concepts into a hierarchical, mixed-initiative planning model. Overall, this work reinforces the argument that Al-based tools can facilitate the design of architectures driven by quality-attribute issues.     

Model-based verification of quantitative non-functional properties for software product lines

Evaluating quality attributes of a design model in the early stages of development can significantly reduce the cost and risks of developing a low quality product. To make this possible, software designers should be able to predict quality attributes by reasoning on a model of the system under development. Although there exists a variety of quality-driven analysis techniques for software systems, only a few work address software product lines. This paper describes how probabilistic model checking techniques and tools can be used to verify non-functional properties of different configurations of a software product line. We propose a model-based approach that enables software engineers to assess their design solutions for software product lines in the early stages of development. Furthermore, we discuss how the analysis time can be surprisingly reduced by applying parametric model checking instead of classic model checking. The results show that the parametric approach is able to substantially alleviate the verification time and effort required to analyze non-functional properties of software product lines.     

A knowledge-based object modeling advisor for developing quality object models

Object models or class diagrams are widely used for capturing information system requirements in terms of classes with attributes and operations, and relationships among those classes. Although numerous guidelines are available for object modeling as part of requirements modeling, developing quality object models has always been considered a challenging task, especially for novice systems analysts in business environments. This paper presents an approach that can be used to support the development of quality object models. The approach is implemented as a knowledge-based system extension to an open source CASE tool to offer recommendations for improving the quality of object models. The knowledge component of this system incorporates an ontology of quality problems that is based on a conceptual model quality framework commonly found in object models, the findings of related empirical studies, and a set of analysis patterns. The results obtained from an empirical evaluation of the prototype demonstrate the utility of this system, especially with respect to recommendations related to the model completeness aspect of semantic quality.     

An optimization framework for “build-or-buy” decisions in software architecture

Building a software architecture that meets functional requirements is a quite consolidated activity, whereas keeping high quality attributes is still an open challenge. In this paper we introduce an optimization framework that supports the decision whether to buy software components or to build them in-house upon designing a software architecture. We devise a non-linear cost/quality optimization model based on decision variables indicating the set of architectural components to buy and to build in order to minimize the software cost while keeping satisfactory values of quality attributes. From this point of view, our tool can be ideally embedded into a Cost Benefit Analysis Method to provide decision support to software architects. The novelty of our approach consists in building costs and quality attributes on a common set of decision variables related to software development. We start from a special case of the framework where the quality constraints are related to the delivery time and the product reliability, and the model solution also devises the amount of unit testing to be performed on built components. We generalize the framework formulation to represent a broader class of architectural cost-minimization problems under quality constraints, and discuss advantages and limitations of such approach.     

An evaluation of timed scenario notations

There is a general consensus on the importance of good Requirements Engineering (RE) for achieving high quality software. The modeling and analysis of requirements have been the main challenges during the development of complex systems. Although semi-formal, scenario driven approaches have raised the awareness and use of requirement engineering techniques, mostly because of their intuitive representation. Scenarios are a well established approach to describe functional requirements, uncovering hidden requirements and trade-offs, as well as validating and verifying requirements.The ability to perform quantitative analysis at the requirements level supports the detection of design errors during the early stages of a software development life cycle, and helps reduce the cost of later redesign activities. In order to achieve this goal, non-functional aspects and in particular time-related aspects have to be incorporated at the software requirement phase. This is essential in order to correctly model and analyze time dependent applications at early stages in system development.The widespread interest in time modeling and analysis techniques provides the major motivation for our paper. The objective of the article is to provide readers with sufficient knowledge about existing timed scenario approaches to guide them in making informed decisions to when and how time aspects can be incorporated in their development process. In order to support this process, we present a comprehensive classification, evaluation and comparison of time-based scenario notations. In order to evaluate these existing notations, we introduce a set of eleven time-related criteria and apply them to categorize and compare forty seven scenario construction approaches.     

A Method for Extracting and Stating Software Requirements that a User Interface Prototype Contains

User interface and requirements prototyping is a requirements elicitation technique. A user interface and requirements prototype is built during the requirements engineering phase of a software system development. Along with the user interface prototype are produced various documents such as the system requirement specification. When a prototype and other documents exist, they may not describe the same functionality, particularly because there may be behaviour of the prototype, artefacts of prototyping, that may not be intended. The problem is that in later development stages, when there is a prototype and other documents, it is often difficult to reconcile the difference between the prototype and the other documents. This paper presents an approach for avoiding this difficulty. It demonstrates the approach by showing its application to parts of a real software development.     

Reuse of early life-;cycle artifacts: workproducts, methods and tools

In this article we describe the importance of reusing software artifacts resulting from the earliest stages of the development life-;cycle, i.e., software conception, requirements analysis, feasibility study, requirements specification, architectural and detailed design. Although reuse of early artifacts is deemed beneficial to software development projects, there are no readily available software tools that could facilitate their effective reuse. Hence, we identified nearly one hundred early artifact types. We analyzed, compared and contrasted them. We clustered similar artifact types into distinct artifact affinity groups. We then proposed several methods and techniques useful in the processing of these artifacts to support their reuse. We believe that the proposed methods could be utilized by tool builders to construct software development environments capable of assisting analysts, designers, architects and programmers to effectively reuse the results of early life-;cycle activities.     

A hybrid heuristic approach to optimize rule-based software quality estimation models

Software quality is defined as the degree to which a software component or system meets specified requirements and specifications. Assessing software quality in the early stages of design and development is crucial as it helps reduce effort, time and money. However, the task is difficult since most software quality characteristics (such as maintainability, reliability and reusability) cannot be directly and objectively measured before the software product is deployed and used for a certain period of time. Nonetheless, these software quality characteristics can be predicted from other measurable software quality attributes such as complexity and inheritance. Many metrics have been proposed for this purpose. In this context, we speak of estimating software quality characteristics from measurable attributes. For this purpose, software quality estimation models have been widely used. These take different forms: statistical models, rule-based models and decision trees. However, data used to build such models is scarce in the domain of software quality. As a result, the accuracy of the built estimation models deteriorates when they are used to predict the quality of new software components. In this paper, we propose a search-based software engineering approach to improve the prediction accuracy of software quality estimation models by adapting them to new unseen software products. The method has been implemented and favorable result comparisons are reported in this work.     

Identifying quality-requirement conflicts

Without a well-defined set of quality-attribute requirements, software projects are vulnerable to failure. The authors have developed QARCC, a knowledge-based tool that helps users, developers, and customers analyze requirements and identify conflicts among them     

On the relationships between QoS and software adaptability at the architectural level

Modern software operates in highly dynamic and often unpredictable environments that can degrade its quality of service. Therefore, it is increasingly important having systems able to adapt their behavior. However, the achievement of software adaptability can influence other software quality attributes, such as availability, performance or cost. This paper proposes an approach for analyzing tradeoffs between the system adaptability and its quality of service. The proposed approach is based on a set of metrics that allow the system adaptability evaluation. The approach can help software architects to guide decisions on system adaptation for fulfilling system quality requirements. The application and effectiveness of the approach are illustrated through examples and a wide set of experiments carried out with a tool we have developed.     

Identification of non-functional requirements in textual specifications: A semi-supervised learning approach

ContextEarly detection of non-functional requirements (NFRs) is crucial in the evaluation of architectural alternatives starting from initial design decisions. The application of supervised text categorization strategies for requirements expressed in natural language has been proposed in several works as a method to help analysts in the detection and classification of NFRs concerning different aspects of software. However, a significant number of pre-categorized requirements are needed to train supervised text classifiers, which implies that analysts have to manually assign categories to numerous requirements before being able of accurately classifying the remaining ones.ObjectiveWe propose a semi-supervised text categorization approach for the automatic identification and classification of non-functional requirements. Therefore, a small number of requirements, possibly identified by the requirement team during the elicitation process, enable learning an initial classifier for NFRs, which could successively identify the type of further requirements in an iterative process. The goal of the approach is the integration into a recommender system to assist requirement analysts and software designers in the architectural design process.MethodDetection and classification of NFRs is performed using semi-supervised learning techniques. Classification is based on a reduced number of categorized requirements by taking advantage of the knowledge provided by uncategorized ones, as well as certain properties of text. The learning method also exploits feedback from users to enhance classification performance.ResultsThe semi-supervised approach resulted in accuracy rates above 70%, considerably higher than the results obtained with supervised methods using standard collections of documents.ConclusionEmpirical evidence showed that semi-supervision requires less human effort in labeling requirements than fully supervised methods, and can be further improved based on feedback provided by analysts. Our approach outperforms previous supervised classification proposals and can be further enhanced by exploiting feedback provided by analysts.     

Guidelines for Eliciting Usability Functionalities

Like any other quality attribute, usability imposes specific constraints on software components. Features that raise the software system's usability have to be considered from the earliest development stages. But, discovering and documenting usability features is likely to be beyond the usability knowledge of most requirements engineers, developers, and users. We propose an approach based on developing specific guidelines that capitalize upon key elements recurrently intervening in the usability features elicitation and specification process. The use of these guidelines provides requirements analysts with a knowledge repository. They can use this repository to ask the right questions and capture precise usability requirements information.     

XTraQue: traceability for product line systems

Product line engineering has been increasingly used to support the development and deployment of software systems that share a common set of features and are developed based on the reuse of core assets. The large number and heterogeneity of documents generated during the development of product line systems may cause difficulties to identify common and variable aspects among applications, and to reuse core assets that are available under the product line. In this paper, we present a traceability approach for product line systems. Traceability has been recognised as an important task in software system development. Traceability relations can improve the quality of the product being developed and reduce development time and cost. We present a rule-based approach to support automatic generation of traceability relations between feature-based object-oriented documents. We define a traceability reference model with nine different types of traceability relations for eight types of documents. The traceability rules used in our work are classified into two groups namely (a) direct rules, which support the creation of traceability relations that do not depend on the existence of other relations, and (b) indirect rules, which require the existence of previously generated relations. The documents are represented in XML and the rules are represented in an extension of XQuery. A prototype tool called XTraQue has been implemented. This tool, together with a mobile phone product line case study, has been used to demonstrate and evaluate our work in various experiments. The results of these experiments are encouraging and comparable with other approaches that support automatic generation of traceability relations. This work has been partially supported by Dhurakijpundit University, Thailand.     

Integrating usability requirements that can be evaluated in design time into Model Driven Engineering of Web Information Systems

In recent years, Web Engineering development projects have grown increasingly complex for and critical to the smooth running of organizations. However, recent studies reveal that a high percentage of these projects fail to attain the quality parameters required by stakeholders. The inadequate consideration of requirements management activities together with the absence of attention to the elicitation and evaluation of requirements and metrics related to certain quality attributes which are of special importance in this kind of systems, such as usability, have proved to be some of the main causes of this failure. This paper attempts to reduce some of the quality failures detected in Web Engineering development projects by proposing the consideration and evaluation of quality attributes from early stages of the development process. The presented approach therefore commences with a reinforcement of the requirements related activities in this discipline, which is carried out by using a requirements metamodel. Once these requirements have been identified, the approach focuses on the extension of the conceptual models used by Web Engineering methodologies with the aim of allowing the explicit consideration of usability requirements along with the evaluation of quality metrics during the design of the system. An example of an application illustrating how the approach can be used, along with the automatic support which was developed for it, are also shown.     

Decision support for the software product line domain engineering lifecycle

Software product line engineering is a paradigm that advocates the reusability of software engineering assets and the rapid development of new applications for a target domain. These objectives are achieved by capturing the commonalities and variabilities between the applications of the target domain and through the development of comprehensive and variability-covering feature models. The feature models developed within the software product line development process need to cover the relevant features and aspects of the target domain. In other words, the feature models should be elaborate representations of the feature space of that domain. Given that feature models, i.e., software product line feature models, are developed mostly by domain analysts by sifting through domain documentation, corporate records and transcribed interviews, the process is a cumbersome and error-prone one. In this paper, we propose a decision support platform that assists domain analysts throughout the domain engineering lifecycle by: (1) automatically performing natural language processing tasks over domain documents and identifying important information for the domain analysts such as the features and integrity constraints that exist in the domain documents; (2) providing a collaboration platform around the domain documents such that multiple domain analysts can collaborate with each other during the process using a Wiki; (3) formulating semantic links between domain terminology with external widely used ontologies such as WordNet in order to disambiguate the terms used in domain documents; and (4) developing traceability links between the unstructured information available in the domain documents and their formal counterparts within the formal feature model representations. Results obtained from our controlled experimentations show that the decision support platform is effective in increasing the performance of the domain analysts during the domain engineering lifecycle in terms of both the coverage and accuracy measures.     

An experiment in tool integration: The DDBG parallel and distributed debugger

This paper discusses the development of a debugging tool for parallel programs showing how the requirements posed by high-level tools for parallel program development have influenced the design of the debugging system since its early stages of development. We concentrate our attention upon the interfacing of the debugger with other tools of a parallel software engineering environment, namely a graphical programming language and a testing and debugging tool. This is illustrated with the results of our experimentation with the design and implementation of DDBG, a debugger for the PVM environment.     

A goal-driven and agent-based requirements engineering framework*

The paper presents a requirements engineering framework (REF), where advanced requirements engineering techniques are combined with software quality modelling approaches to provide an environment within which the stakeholders and the analysts can easily cooperate to discover, organise, reconcile and validate the requirements for a new system. By adopting a basic and essential graphical notation, and a clear top-down methodology, REF allows for an effective involvement of the stakeholders, assisting and driving them to an early definition of the desired system's functionalities and quality attributes, while supporting the redesign of the encompassing organisational context to better exploit the new system's capabilities. As a case study, REF is applied to support the requirements engineering process for a complex software-intensive simulation system. Results demonstrate the feasibility of REF and the benefits it offers to the requirements engineering process, but also to the subsequent system development phases. As illustrated through the case study REF can, in fact, be usefully applied as a forerunner for unified modelling language (UML)-based approaches.*Part of this work was completed while the author was Senior Research Fellow with the Computing Information Systems Engineering Group, at the Royal Military College of Science, Cranfield University (UK)