Silva Robak

Employing fuzzy logic in feature diagrams to model variability in software product-lines

The possible features of software product line members may vary according to the needs of particular market segments or purposes. The assessment of what will be common and what will be variable may, e.g., result from market strategies. Customer profiles may be used to model an otherwise anonymous market, each requiring in turn a specific sets of variant features. Identical feature sets may be prioritized in different ways for specific customer groups. The paper proposes a system description based on a feature diagram tree, annotated with weighted variant features in the product line context. The principle how some variant features may be described on the basis of fuzzy logic is introduced and discussed. As the proposed description also integrates the external cross-tree constraints, it leads to an improved homogeneity of the descriptive logic. This opens the opportunity to integrate additional tools into the scenario, e.g., generators or support for constraint based reasoning. The use of the proposed approach is demonstrated by the example of a simple car description.

Features with fuzzy probability

This paper proposes an expert system description based on a feature diagram tree, annotated with weighted variant features in the software family context. The principle of how some variant features may be described on the basis of fuzzy logic is presented and fuzzy probability of market conditions is introduced. The proposed description integrates the external cross-tree constraints, and the resulting homogeneity of the logic then allows its usage to further applications, e.g., generators, or to the purposes of constraint based reasoning itself. The appliance of the proposed approach is demonstrated by the example of a mobile phone tariff description. In the example descriptions of the decision tree for customers have been prepared.

Application of fuzzy weighted feature diagrams to model variability in software families

In the paper the employment of fuzzy logic in feature models for software system families is presented. The fuzzy weights of some variable features are introduced. The approach is demonstrated on the example of the feature model describing car properties. The formulas resulting from the description of the feature tree and its constraints can be used as input for an expert system validating possible feature combinations.

Adjusting software-intensive systems developed by using software factories and fuzzy features

Growing expectations for low priced software-intensive applications tailored to the individual customers needs require the usage of techniques aimed at the individual development of application systems, which could be attained at the costs of standard software and easily adapted. In the paper the concepts associated with assembling the applications by means of software factories in conjunction with the fuzzy description of the variable product parts are introduced. The approach is demonstrated in the example of a part of an order process.

Research Problems Associated with Big Data Utilization in Logistics and Supply Chains Design and Management.

One of contemporary big challenges in information systems are the issues associated with coping with and utilization of the vast amounts of data. In this position paper we present few research problems emerging in association with occurrence of big data, with focus on domain of logistics and supply chains. We also reveal a number of influence factors on supply chains design and management which are related to big data. We show that the association of data science and predictive analysis with domain knowledge can build an important improvement for logistics and supply chain design and management. We point out how the domain problems in the key managerial business components could be solved better with big data applications for the stakeholders involved in the supply chains. We also highlight open problems in this domain and chances for the future.

Assessing the Non-technical Service Aspects by Using Fuzzy Methods

The growing expectations for service-oriented applications tailored to the customers needs comprise a definition of the service contract documents, for both, technical and non-technical service elements. The usage of the fuzzy methods and techniques allows for the customized prearrangement of such application systems, which could be developed at the costs of the standard software. In the paper the concepts associated with a service-oriented design of non-technical service aspects especially appropriate for the fuzzy description of them as the requirements destined for Service Level Agreements SLAs, are introduced. The proposed approach is demonstrated on the example of a service accessibility requirement, an important component of a contracted SLA.

Business process optimization with big data analytics under consideration of privacy

One of the contemporary problems, and at the same time a big opportunity, in business networks of supply chains are the issues associated with the vast amounts of data arising there. The data may be utilized by the decision support systems in supply chains; nevertheless, often there are information privacy problems. The supply chains in cloud will need appropriate administration for support of privacy aspects of cooperating business units existing in big data ecosystems. In this paper we analyze the possibility of utilizing the big data technology for supporting business processes optimization with respect of the privacy regulations in supply chains under the usage of the big data analytics lifecycle. We present our approach on an example of a business process in logistics.