Timo Soininen

Extending and implementing the stable model semantics

A novel logic program like language, weight constraint rules, is developed for answer set programming purposes. It generalizes normal logic programs by allowing weight constraints in place of literals to represent, e.g., cardinality and resource constraints and by providing optimization capabilities. A declarative semantics is developed which extends the stable model semantics of normal programs. The computational complexity of the language is shown to be similar to that of normal programs under the stable model semantics. A simple embedding of general weight constraint rules to a small subclass of the language called basic constraint rules is devised. An implementation of the language, the SMODELS system, is developed based on this embedding. It uses a two level architecture consisting of a front-end and a kernel language implementation. The front-end allows restricted use of variables and functions and compiles general weight constraint rules to basic constraint rules. A major part of the work is the development of an efficient search procedure for computing stable models for this kernel language. The procedure is compared with and empirically tested against satisfiability checkers and an implementation of the stable model semantics. It offers a competitive implementation of the stable model semantics for normal programs and attractive performance for problems where the new types of rules provide a compact representation.

Towards a general ontology of configuration

This article presents a generalized ontology of product configuration as a step towards a general ontology of configuration, which is needed to reuse and share configuration knowledge. The ontology presented consists of a set of concepts for representing the knowledge on a configuration and the restrictions on possible configurations. The ontology is based on a synthesis of the main approaches to configuration. Earlier approaches are extended with new concepts arising from our practical experience on configurable products. The concepts include components, attributes, resources, ports, contexts, functions, constraints, and relations between these. The main contributions of this work are in the detailed conceptualization of knowledge on product structures and in extending the resource concept with contexts for limiting the availability and use of resources. In addition, constraint sets representing different views on the product are introduced. The ontology is compared with the previous work on configuration. It covers all the principal approaches, that is, connection-based, structure-based, resource-based, and function-based approaches to configuration. The dependencies between the concepts arising from different conceptualizations are briefly analyzed. Several ways in which the ontology could be extended are pointed out.

Developing a Declarative Rule Language for Applications in Product Configuration

A rule-based language is proposed for product configuration applications. It is equipped with a declarative semantics providing formal definitions for main concepts in product configuration, including configuration models, requirements and valid configurations. The semantics uses Horn clause derivability to guarantee that each element in a configuration has a justification. This leads to favorable computational properties. For example, the validity of a configuration can be decided in linear time and other computational tasks remain in NP. It is shown that CSP and dynamic CSP can be embedded in the proposed language which seems to be more suitable for representing configuration knowledge. The rule language is closely related to normal logic programs with the stable model semantics. This connection is exploited in the first implementation which is based on a translator from rules to normal programs and on an existing high performance implementation of the stable model semantics, the Smodels system.

Stable Model Semantics of Weight Constraint Rules

A generalization of logic program rules is proposed where rules are built from weight constraints with type information for each predicate instead of simple literals. These kinds of constraints are useful for concisely representing different kinds of choices as well as cardinality, cost and resource constraints in combinatorial problems such as product configuration. A declarative semantics for the rules is presented which generalizes the stable model semantics of normal logic programs. It is shown that for ground rules the complexity of the relevant decision problems stays in NP. The first implementation of the language handles a decidable subset where function symbols are not allowed. It is based on a new procedure for computing stable models for ground rules extending normal programs with choice and weight constructs and a compilation technique where a weight rule with variables is transformed to a set of such simpler ground rules.

Kumbang: A domain ontology for modelling variability in software product families

Variability is the ability of a system to be efficiently extended, changed, customised or configured for use in a particular context. There is an ever-growing demand for variability of software. Software product families are an important means for implementing software variability. We present a domain ontology called Kumbang for modelling the variability in software product families. Kumbang synthesises previous approaches to modelling variability in software product families. In addition, it incorporates modelling constructs developed in the product configuration domain for modelling the variability in non-software products. The modelling concepts include components and features with compositional structure and attributes, the interfaces of components and connections between them, and constraints. The semantics of Kumbang is rigorously described using natural language and a UML profile. We provide preliminary proof of concept for Kumbang: the domain ontology has been provided with a formal semantics by implementing a translation into a general-purpose knowledge representation language with formal semantics and inference support. A prototype tool for resolving variability has been implemented.

State-of-the-practice in product configuration — a survey of 10 cases in the Finnish industry

The design and production of goods that satisfy the special needs of individual customers are of central interest to the European industry. A major trend is to improve customer specific adaptation with configurable products. We are interested in the methods, practices and tools that support product configuration tasks. The research described in this paper is meant to guide our future work. We have 1) established a framework for understanding the problem area of product configuration in a fairly wide sense by identifying a number of factors and 2) carried out ten actual case studies using the proposed framework.

A unified conceptual foundation for feature modelling

Feature modelling has become perhaps the most popular method for representing variabilities and commonalities in software product families. A large number of feature modelling methods and supporting tools have been reported. The conceptual foundation of feature models remains vague, a fact that severely undermines the usability of feature models. Therefore, we introduce Forfamel, a rigorous conceptual foundation for feature modelling. Forfamel synthesises existing feature modelling methods in the sense that it covers most concepts and constructs found in existing feature modelling methods. In addition, Forfamel includes a few additional constructs that may prove to be useful. We show the novel contribution of Forfamel by reflecting it against previous feature modelling methods and arguing for its underlying design decisions.

Multiple abstraction levels in modelling product structures

Abstract The need for product customisation is driving industrial companies towards a very large product variety, which affects many functions of a company, including the after-sales. Systematic maintenance records of very different product individuals cannot be kept without an abstract view to the population of delivered products. However, the older the product individual, the less systematically recorded information there usually is about it. We defined a novel mechanism based on generic models of product individuals organised into a specialisation hierarchy to support multiple abstraction levels. For creating such hierarchies, we defined a set of transformation operations on models.

A Koala-Based Approach for Modelling and Deploying Configurable Software Product Families

An approach for modelling configurable software product families (CSPFs) and for automated configuring of product individuals using the models is presented. It is based on a similar approach for configuring physical products. The conceptual foundation and syntax of the Koalish modelling language used for this purpose are defined. The language extends Koala, a component model and architecture description language, with explicit variation modelling mechanisms. Koalish is further provided a formal semantics by defining a translation from it to Weight Constraint Rule Language (WCRL), a form of logic programs. This allows using an existing inference tool for WCRL, smodels, to implement the reasoning needed in the configurator. The configurator is able to construct all valid product individuals, with respect to a Koalish model of a CSPF, that satisfy a given set of requirements. The implemented functionality of the configurator has been tested using small-scale toy examples, for which it performs adequately.

A Fixpoint Definition of Dynamic Constraint Satisfaction

Many combinatorial problems can be represented naturally as constraint satisfaction problems (CSP). However, in some domains the set of variables in a solution should change dynamically on the basis of assignments of values to variables. In this paper we argue that such dynamic constraint satisfaction problems (DCSP), introduced by Mittal and Falkenhainer, are more expressive than CSP in a knowledge representation sense. We then study the problem of generalizing the original DCSP with disjunctive activity constraints and default negation which are useful in, e.g., product configuration problems. The generalization is based on a novel definition of a solution to DCSP. It uses a fixpoint condition instead of the subset minimality condition in the original formulation. Our approach coincides with the original definition when disjunctions and default negations are not allowed. However, it leads to lower computational complexity than if the original definition were generalized similarly. In fact we show that the generalized DCSP is NP-complete. As a proof of concept, we briefly describe two novel implementations of the original DCSP and give test results for them.