On Formal Methods for Large-Scale Product Configuration

<p>In product development companies mass customization is widely used to achieve better customer satisfaction while keeping costs down. To efficiently implement mass customization, product platforms are often used. A product platform allows building a wide range of products from a set of predefined components. The process of matching these components to customers' needs is called product configuration. Not all components can be combined with each other due to restrictions of various kinds, for example, geometrical, marketing and legal reasons. Product design engineers develop configuration constraints to describe such restrictions. The number of constraints and the complexity of the relations between them are immense for complex product like a vehicle. Thus, it is both error-prone and time consuming to analyze, author and verify the constraints manually. Software tools based on formal methods can help engineers to avoid making errors when working with configuration constraints, thus design a correct product faster.</p> <p>This thesis introduces a number of formal methods to help engineers maintain, verify and analyze product configuration constraints. These methods provide automatic verification of constraints and computational support for analyzing and refactoring constraints. The methods also allow verifying the correctness of one specific type of constraints, item usage rules, for sets of mutually-exclusive required items, and automatic verification of equivalence of different formulations of the constraints. The thesis also introduces three methods for efficient enumeration of valid partial configurations, with benchmarking of the methods on an industrial dataset.</p> <p>Handling large-scale industrial product configuration problems demands high efficiency from the software methods. This thesis investigates a number of search-based and knowledge-compilation-based methods for working with large product configuration instances, including Boolean satisfiability solvers, binary decision diagrams and decomposable negation normal form. This thesis also proposes a novel method based on supervisory control theory for efficient reasoning about product configuration data. The methods were implemented in a tool, to investigate the applicability of the methods for handling large product configuration problems. It was found that search-based Boolean satisfiability solvers with incremental capabilities are well suited for industrial configuration problems.</p> <p>The methods proposed in this thesis exhibit good performance on practical configuration problems, and have a potential to be implemented in industry to support product design engineers in creating and maintaining configuration constraints, and speed up the development of product platforms and new products.</p

SAT-based Analysis, (Re-)Configuration & Optimization in the Context of Automotive Product documentation

Es gibt einen steigenden Trend hin zu kundenindividueller Massenproduktion (mass customization), insbesondere im Bereich der Automobilkonfiguration. Kundenindividuelle Massenproduktion führt zu einem enormen Anstieg der Komplexität. Es gibt Hunderte von Ausstattungsoptionen aus denen ein Kunde wählen kann um sich sein persönliches Auto zusammenzustellen. Die Anzahl der unterschiedlichen konfigurierbaren Autos eines deutschen Premium-Herstellers liegt für ein Fahrzeugmodell bei bis zu 10^80. SAT-basierte Methoden haben sich zur Verifikation der Stückliste (bill of materials) von Automobilkonfigurationen etabliert. Carsten Sinz hat Mitte der 90er im Bereich der SAT-basierten Verifikationsmethoden für die Daimler AG Pionierarbeit geleistet. Darauf aufbauend wurde nach 2005 ein produktives Software System bei der Daimler AG installiert. Später folgten weitere deutsche Automobilhersteller und installierten ebenfalls SAT-basierte Systeme zur Verifikation ihrer Stücklisten. Die vorliegende Arbeit besteht aus zwei Hauptteilen. Der erste Teil beschäftigt sich mit der Entwicklung weiterer SAT-basierter Methoden für Automobilkonfigurationen. Wir zeigen, dass sich SAT-basierte Methoden für interaktive Automobilkonfiguration eignen. Wir behandeln unterschiedliche Aspekte der interaktiven Konfiguration. Darunter Konsistenzprüfung, Generierung von Beispielen, Erklärungen und die Vermeidung von Fehlkonfigurationen. Außerdem entwickeln wir SAT-basierte Methoden zur Verifikation von dynamischen Zusammenbauten. Ein dynamischer Zusammenbau repräsentiert die chronologische Zusammenbau-Reihenfolge komplexer Teile. Der zweite Teil beschäftigt sich mit der Optimierung von Automobilkonfigurationen. Wir erläutern und vergleichen unterschiedliche Optimierungsprobleme der Aussagenlogik sowie deren algorithmische Lösungsansätze. Wir beschreiben Anwendungsfälle aus der Automobilkonfiguration und zeigen wie diese als aussagenlogisches Optimierungsproblem formalisiert werden können. Beispielsweise möchte man zu einer Menge an Ausstattungswünschen ein Test-Fahrzeug mit minimaler Ergänzung weiterer Ausstattungen berechnen um Kosten zu sparen. DesWeiteren beschäftigen wir uns mit der Problemstellung eine kleinste Menge an Fahrzeugen zu berechnen um eine Testmenge abzudecken. Im Rahmen dieser Arbeit haben wir einen Prototypen eines (Re-)Konfigurators, genannt AutoConfig, entwickelt. Unser (Re-)Konfigurator verwendet im Kern SAT-basierte Methoden und besitzt eine grafische Benutzeroberfläche, welche interaktive Konfiguration erlaubt. AutoConfig kann mit Instanzen von drei großen deutschen Automobilherstellern umgehen, aber ist nicht alleine darauf beschränkt. Mit Hilfe dieses Prototyps wollen wir die Anwendbarkeit unserer Methoden demonstrieren

On Uniformly Sampling Traces of a Transition System (Extended Version)

A key problem in constrained random verification (CRV) concerns generation of input stimuli that result in good coverage of the system's runs in targeted corners of its behavior space. Existing CRV solutions however provide no formal guarantees on the distribution of the system's runs. In this paper, we take a first step towards solving this problem. We present an algorithm based on Algebraic Decision Diagrams for sampling bounded traces (i.e. sequences of states) of a sequential circuit with provable uniformity (or bias) guarantees, while satisfying given constraints. We have implemented our algorithm in a tool called TraceSampler. Extensive experiments show that TraceSampler outperforms alternative approaches that provide similar uniformity guarantees.Comment: Extended version of paper that will appear in proceedings of International Conference on Computer-Aided Design (ICCAD '20); changed wrong text color in sec 7; added 'extended version

Programming with Specifications

This thesis explores the use of specifications for the construction of correct programs. We go beyond their standard use as run-time assertions, and present algorithms, techniques and implementations for the tasks of 1) program verification, 2) declarative programming and 3) software synthesis. These results are made possible by our advances in the domains of decision procedure design and implementation. In the first part of this thesis, we present a decidability result for a class of logics that support user-defined recursive function definitions. Constraints in this class can encode expressive properties of recursive data structures, such as sortedness of a list, or balancing of a search tree. As a result, complex verification conditions can be stated concisely and solved entirely automatically. We also present a new decision procedure for a logic to reason about sets and constraints over their cardinalities. The key insight lies in a technique to decompose con- straints according to mutual dependencies. Compared to previous techniques, our algorithm brings significant improvements in running times, and for the first time integrates reasoning about cardinalities within the popular DPLL(T ) setting. We integrated our algorithmic ad- vances into Leon, a static analyzer for functional programs. Leon can reason about constraints involving arbitrary recursive function definitions, and has the desirable theoretical property that it will always find counter-examples to assertions that do not hold. We illustrate the flexibility and efficiency of Leon through experimental evaluation, where we used it to prove detailed correctness properties of data structure implementations. We then illustrate how program specifications can be used as a high-level programming construct ; we present Kaplan, an extension of Scala with first-class logical constraints. Kaplan allows programmers to create, manipulate and combine constraints as they would any other data structure. Our implementation of Kaplan illustrates how declarative programming can be incorporated into an existing mainstream programming language. Moreover, we examine techniques to transform, at compile-time, program specifications into efficient executable code. This approach of software synthesis combines the correctness benefits of declarative programming with the efficiency of imperative or functional programming

Computer Aided Verification

The open access two-volume set LNCS 11561 and 11562 constitutes the refereed proceedings of the 31st International Conference on Computer Aided Verification, CAV 2019, held in New York City, USA, in July 2019. The 52 full papers presented together with 13 tool papers and 2 case studies, were carefully reviewed and selected from 258 submissions. The papers were organized in the following topical sections: Part I: automata and timed systems; security and hyperproperties; synthesis; model checking; cyber-physical systems and machine learning; probabilistic systems, runtime techniques; dynamical, hybrid, and reactive systems; Part II: logics, decision procedures; and solvers; numerical programs; verification; distributed systems and networks; verification and invariants; and concurrency