Huilin Ye

Quality attribute modeling and quality aware product configuration in software product lines

In software product line engineering, the customers mostly concentrate on the functionalities of the target product during product configuration. The quality attributes of a target product, such as security and performance, are often assessed until the final product is generated. However, it might be very costly to fix the problem if it is found that the generated product cannot satisfy the customers’ quality requirements. Although the quality of a generated product will be affected by all the life cycles of product development, feature-based product configuration is the first stage where the estimation or prediction of the quality attributes should be considered. As we know, the key issue of predicting the quality attributes for a product configured from feature models is to measure the interdependencies between functional features and quality attributes. The current existing approaches have several limitations on this issue, such as requiring real products for the measurement or involving domain experts’ efforts. To overcome these limitations, we propose a systematic approach of modeling quality attributes in feature models based on domain experts’ judgments using the analytic hierarchical process (AHP) and conducting quality aware product configuration based on the captured quality knowledge. Domain experts’ judgments are adapted to avoid generating the real products for quality evaluation, and AHP is used to reduce domain experts’ efforts involved in the judgments. A prototype tool is developed to implement the concepts of the proposed approach, and a formal evaluation is carried out based on a large-scale case study.

Quality Attributes Assessment for Feature-Based Product Configuration in Software Product Line

Product configuration based on a feature model in software product lines is the process of selecting the desired features based on customers’ requirements. In most cases, application engineers focus on the functionalities of the target product during product configuration process whereas the quality attributes are handled until the final product is produced. However, it is costly to fix the problem if the quality attributes have not been considered in the product configuration stage. The key issue of assessing a quality attribute of a product configuration is to measure the impact on a quality attribute made by the set of functional variable features selected in a configuration. Current existing approaches have several limitations, such as no quantitative measurements provided or requiring existing valid products and heavy human effort for the assessment. To overcome theses limitations, we propose an Analytic Hierarchical Process (AHP) based approach to estimate the relative importance of each functional variable feature on a quality attribute. Based on the relative importance value of each functional variable feature on a quality attribute, the level of quality attributes of a product configuration in software product lines can be assessed. An illustrative example based on the Computer Aided Dispatch (CAD) software product line is presented to demonstrate how the proposed approach works.

An Approach for Modelling Software Product Line Architecture

One of the challenges of the Software Product Line Architecture design is how to model and present the differences of the member products. Many approaches have been introduced, such as FORM, FODA, KobrA etc. In this paper, we propose an approach to transform feature models into architecture models. This iterative approach explicitly models the variability presented in the feature model into architectural artifacts and transfers the feature dependencies into the interactions between the architectural artifacts in the architecture model. The approach improves the traceability between the feature models and architecture models, thus provide better guidance for the architecture development of the member product in Software Product Lines.

An approach to efficient product configuration in software product lines

Feature modeling has been widely used in software product line engineering to represent commonality and variabilities among products in a product family. When developing a new software product belonging to a product line, a feature model representing the product line will be used to configure products. The product configuration process is a decision making process, various kinds of constraints and complex relationships among configurable features make the decision making a time consuming and error prone task. In this paper, we present an approach which will improve the efficiency and quality of product configuration.

Modeling Quality Attributes in Software Product Line Architecture

The main task of the software product line architecture design is to develop the reference architecture which represent the base structure of the member products. Quality driven Architecture Design and quality Analysis (QADA) is the architecture design method, which has attracted many attentions since it emphasizes on addressing quality issues of the member products at early stage of the system development. In this paper, we introduce two additional views (the quality view and the tradeoff view) to the QADA framework. These extra views will improve the requirements traceability, i.e. it is easier to understand how the requirements on software quality are mapped onto the system architecture, thus will help in developing the concrete architecture for the member products. We have also included a case study to illustrate our approach in details.

Input Data Representation for Self-Organizing Map in Software Classification

A self-organizing map (SOM) is used to classify software documents and the associated software components with the aim to facilitate software reuse. SOM learns from input stimuli rather than training data, therefore the quality of input data representation is crucial to the success of SOM. In this paper, we use automatic indexing method to represent a document collection as the input data to train a SOM. The automatic indexing uses a phrase formation method to promote precision and a domain dependent relational thesaurus to enhance recall. A retrieval experiment based on a document collection containing 97 Unix manual pages was conducted to evaluate the effectiveness of this input data representation scheme. Promising retrieval results were observed.

Measurement of the Complexity of Variation Points in Software Product Lines

Feature models are used in member product configuration in software product lines. A valid product configuration must satisfy two kinds of constraints, multiplicity of each variation point and dependencies among the variants in a product line. The combined impact of the two kinds of constrains on product configuration should be well understood. In this paper we propose a measurement, called V ariationRank, that combines the two kinds of constraints to assess the complexity of variation points in software product lines. Based on the measurement wean identify those variation points with the highest impact on product configurations in a product line. This information could be used as guidance in product configuration as well as for feature model optimization in software product lines. A case study is presented and discussed in this paper as well.

A New Parameter for Product Configuration in Software Product Lines

Software product line development is a new software engineering method. It promotes the predictive software reuse by developing similar software systems together. One of the key artifacts of a software product line is the feature model, which represents the commonality and variability of all the products in the product family. When developing a member product from the product line, based on the requirement of the final product, features from the feature model will be selected and configured to form the final product. As the requirement could be incomplete or vague, the software engineer might need additional information in assisting with the feature selection. In this paper, we propose a new parameter, called the Instantiation Space, which measures the relative impact on the rest of the system for a selection. We believe that such information will be very helpful in the process of product configuration.