Identifying requirements in requests for proposal

Abstract. [Context & motivation] Bidding processes are a usual requirement elicitation instrument for large IT or infrastructure projects. An organization or agency issues a Request for Proposal (RFP) and interested companies may submit compliant offers. [Problem] Such RFPs comprise natural language documents of several hundreds of pages with requirements of various kinds mixed with other information. The analysis of that huge amount of information is very time consuming and cumbersome because bidding companies should not disregard any requirement stated in the RFP. [Principal ideas/results] This research preview paper presents a first version of a classification component, OpenReq Classification Service (ORCS), which extracts requirements from RFP documents while discarding irrelevant text. ORCS is based on the use of Naïve Bayes classifiers. We have trained ORCS with 6 RFPs and then tested the component with 4 other RFPs, all of them from the railway safety domain. [Contribution] ORCS paves the way to improved productivity by reducing the manual effort needed to identify requirements from natural language RFPsPeer ReviewedPostprint (author's final draft

(Re)configuration based on model generation

Reconfiguration is an important activity for companies selling configurable products or services which have a long life time. However, identification of a set of required changes in a legacy configuration is a hard problem, since even small changes in the requirements might imply significant modifications. In this paper we show a solution based on answer set programming, which is a logic-based knowledge representation formalism well suited for a compact description of (re)configuration problems. Its applicability is demonstrated on simple abstractions of several real-world scenarios. The evaluation of our solution on a set of benchmark instances derived from commercial (re)configuration problems shows its practical applicability.Comment: In Proceedings LoCoCo 2011, arXiv:1108.609

A Heuristic, Replay-based Approach for Reconfiguration

Abstract. Reconfiguration is an important aspect of industrial product configuration. Once an industrial artefact has been built according to an initial configuration, constant reconfigurations are necessary during its lifetime due to changed requirements or a changed product specification. This reconfigurations should affect as few parts of the running system as possible. Due to the large number of involved components, approaches based on optimization are often not usable in practice. This paper introduces a novel approach for reconfiguration based on a replay heuristic (the product is rebuilt from scratch while trying to use as many decisions from the legacy configuration as possible) and describes its realisation using the standard solving technologies Constraint Satisfaction and Answer Set Programming

Solving Object-oriented Configuration Scenarios with ASP

The main configuration scenarios occurring in the domain of technical products and systems are consistency checking, completing a partial configuration, reconfiguration of an inconsistent configuration and finding the best knowledge base for future reconfigurations. This paper presents OOASP- a framework for the description of object-oriented product configurators using answer set programming and shows that it is able to solve the different (re)configuration scenarios occurring in practice. Thus, it is a step forward to close the conceptual gap between logic-based and object-oriented approaches for product configuration

Using Symmetries to Lift Satisfiability Checking

We analyze how symmetries can be used to compress structures (also known as interpretations) onto a smaller domain without loss of information. This analysis suggests the possibility to solve satisfiability problems in the compressed domain for better performance. Thus, we propose a 2-step novel method: (i) the sentence to be satisfied is automatically translated into an equisatisfiable sentence over a ``lifted'' vocabulary that allows domain compression; (ii) satisfiability of the lifted sentence is checked by growing the (initially unknown) compressed domain until a satisfying structure is found. The key issue is to ensure that this satisfying structure can always be expanded into an uncompressed structure that satisfies the original sentence to be satisfied. We present an adequate translation for sentences in typed first-order logic extended with aggregates. Our experimental evaluation shows large speedups for generative configuration problems. The method also has applications in the verification of software operating on complex data structures. Our results justify further research in automatic translation of sentences for symmetry reduction

Solver Requirements for Interactive Configuration

Interactive configuration includes the user as an essential factor in the configuration process. The two main components of an interactive configurator are a user interface at the front-end and a knowledge representation and reasoning (KRR) framework at the back-end. In this paper we discuss important requirements for the underlying KRR system to support an interactive configuration process. Representative of many reasoning systems and tools used for implementing product configurators, we selected MiniZinc, Choco, Potassco, Picat, CP-SAT solver, and Z3 for evaluation and reviewed them against the identified requirements. We observe that many of those requirements are not well supported by existing stand-alone solvers

Identifying requirements in requests for proposal

Abstract. [Context & motivation] Bidding processes are a usual requirement elicitation instrument for large IT or infrastructure projects. An organization or agency issues a Request for Proposal (RFP) and interested companies may submit compliant offers. [Problem] Such RFPs comprise natural language documents of several hundreds of pages with requirements of various kinds mixed with other information. The analysis of that huge amount of information is very time consuming and cumbersome because bidding companies should not disregard any requirement stated in the RFP. [Principal ideas/results] This research preview paper presents a first version of a classification component, OpenReq Classification Service (ORCS), which extracts requirements from RFP documents while discarding irrelevant text. ORCS is based on the use of Naïve Bayes classifiers. We have trained ORCS with 6 RFPs and then tested the component with 4 other RFPs, all of them from the railway safety domain. [Contribution] ORCS paves the way to improved productivity by reducing the manual effort needed to identify requirements from natural language RFPsPeer Reviewe