Feature and Feature Interaction Modeling with Feature-Solution Graphs

نویسندگان

  • Hans de Bruin
  • Hans van Vliet
چکیده

The architecture of a software system captures early design decisions. These early design decisions reflect major quality concerns, including functionality. We would obviously like to design our systems such that they fulfill the quality requirements set for them. Unfortunately, we in general do not succeed in doing so in a straightforward way. This is especially true for product lines that must evolve and/or must support variations with slightly different features. What we need is an approach that on the one hand can assess the impact of feature interactions and on the other hand can be used to generate different versions of a system dependent on the required features in such a way that all quality requirements are satisfied. This position paper1 is concerned with techniques to support this approach. In particular, we propose to use a rich featuresolution graph to capture the evolving knowledge about quality requirements and solution fragments. This graph is next used to pinpoint feature interactions and to guide an iterative architecture development and evaluation process. The structure of this feature-solution graph resembles that of the goal-hierarchy in goal-oriented requirements engineering [2, 3]. The solution fragments included in this graph have much in common with Attribute-Based Architectural Styles (ABASs) [1]. In principle, any kind of solution description will do. The approach to generating and evaluating architectures from a feature-solution graph is depicted in Figure 1.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Modeling and design of a diagnostic and screening algorithm based on hybrid feature selection-enabled linear support vector machine classification

Background: In the current study, a hybrid feature selection approach involving filter and wrapper methods is applied to some bioscience databases with various records, attributes and classes; hence, this strategy enjoys the advantages of both methods such as fast execution, generality, and accuracy. The purpose is diagnosing of the disease status and estimating of the patient survival. Method...

متن کامل

Supervised Feature Extraction of Face Images for Improvement of Recognition Accuracy

Dimensionality reduction methods transform or select a low dimensional feature space to efficiently represent the original high dimensional feature space of data. Feature reduction techniques are an important step in many pattern recognition problems in different fields especially in analyzing of high dimensional data. Hyperspectral images are acquired by remote sensors and human face images ar...

متن کامل

Fuzzy-rough Information Gain Ratio Approach to Filter-wrapper Feature Selection

Feature selection for various applications has been carried out for many years in many different research areas. However, there is a trade-off between finding feature subsets with minimum length and increasing the classification accuracy. In this paper, a filter-wrapper feature selection approach based on fuzzy-rough gain ratio is proposed to tackle this problem. As a search strategy, a modifie...

متن کامل

Anomaly Detection Using SVM as Classifier and Decision Tree for Optimizing Feature Vectors

Abstract- With the advancement and development of computer network technologies, the way for intruders has become smoother; therefore, to detect threats and attacks, the importance of intrusion detection systems (IDS) as one of the key elements of security is increasing. One of the challenges of intrusion detection systems is managing of the large amount of network traffic features. Removing un...

متن کامل

Feature selection using genetic algorithm for breast cancer diagnosis: experiment on three different datasets

Objective(s): This study addresses feature selection for breast cancer diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin breast cancer datasets. Materials and Methods: To evaluate effectiveness of proposed feature selection method, we ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2001