Gray-box combinatorial interaction testing

The enourmous size of configuration spaces in highly configurable softwares pose challenges to testing. Typically exhaustive testing is neither an option nor a way. Combinatorial interaction techiques are a systematic way to test such enourmous configuration spaces by a systematic way of sampling the space, employed through covering arrays. A t-way covering array is a sampled subset of configurations which contains all t-way option setting combinations. Testing through t-way covering arrays is proven to be highly e ective at revealing failures caused by interaction of t or fewer options. Although, traditional covering arrays are e ective however, we’ve observed that they su er in the presence of complex interactions among configuration options, referred as tangled options. A tangled configuration option is described as either a configuration option with complex structure and/or nested in hierarchy of configuration options. In this thesis, we conjecture the e ectiveness of CIT in the presence of tangled options can greatly be improved, by analyzing the system’s source code. The analysis of source code reveals the interaction of configuration options with each other, this information can be used to determine which additional option setting combinations and the conditions under which these combinations must be tested. Gray-box testing methods rely on partial structural information of the system during testing. We’ve statically analyzed the source code of subject applications to extract the structure and hierachy of configuration options. Each configuration option has been structurally tested according to a test criterion against a t-way covering array and subsequently their t-way interactions. The criterion revealed the missing coverage of options which were employed to drive the additional testcase generation phase to acheive complete coverage. We present a number of novel CIT coverage criteria for t-wise interaction testing of configuration options. In this thesis, we’ve conducted a series of large scale experiments on 18 di erent real-world highly configurable software applications from di erent application domains to evaluate the proposed approach. We’ve observed that traditional t-way CAs can provide above 80% coverage for configuration options testing. However, they significantly su er to provide interaction coverage under high t and tangling e ects where coverage is dropped to less than 50%. Our work address these issues and propose a technique to acheive complete coverage

Enumerator: an efficient approach for enumerating all valid t-tuples

In this paper, we present an efficient approach for enumerating all valid t-tuples for a given configuration space model, which is an important task in computing covering arrays. The results of our experiments suggest that the proposed approach scales better than existing approaches

Input Modeling Prioritization Using Statistically User Profile for Pairwise Test Case Generation with Constraints Handling

Pairwise testing is a widely used technique for software testing with reduce size of the test suite and able to detect interactions that trigger the system’s faults. In addition, pairwise testing test suites must be able to deal with constraints between input parameters and values. In current practice, selecting input parameters and values usually depends on tester skills that might not be sufficient. Input parameters and values modeling and tools for easily guiding and prioritizing the selection of optimal input parameters and values for the SUT is also required. In this work, we present an approach for prioritizing input parameters and values modeling using statistical user profile. Our approach is implemented in a tool called UPPTCT which provides ability to handle constraints on input parameters and values for pairwise testing in order to generate test cases. We conduct experiments to evaluate test case effectiveness and compare our tool with other renowned pairwise test generation and constraints handling tools. The experimental results show that the effectiveness of our approach is significantly more efficient and effective than random testing as large portion of reported defects with regard to statically user profile were caught by our approach. Furthermore, our tool performs better in some cases and performs comparable results for generating test cases upon input parameters and values for both with constraints handling and without constraints handling.Pairwise testing is a widely used technique for software testing with the reduced size of the test suite and able to detect interactions that trigger the system’s faults. In addition, pairwise testing test suites must be able to take constraints between input parameters and parameter values into account. In current practice, identifying and selecting input parameters and parameter values usually depends on tester skills that might not be sufficient. Input parameters and parameter values modeling and tools for easily guiding and prioritizing the selection of optimal input parameters and parameter values for the SUT is also required. In this work, we present an approach for prioritizing input parameters and parameter values modeling using statistical user profile. Our approach is implemented in a tool called UPPTCT which provides the ability to handle constraints on input parameters and parameter values for pairwise testing in order to generate test cases. We conduct experiments to evaluate test case effectiveness and compare our tool with other renowned pairwise test generation and constraints handling tools. The experimental results show that the effectiveness of our approach is significantly more efficient and effective than random testing as a large portion of reported defects with regard to statically user profile were caught by our approach. Furthermore, our tool performs better in some cases and performs comparable results for generating test cases upon input parameters and parameter values for both with constraints handling and without constraints handling

Density And Strength Of Ties In Innovation Networks: A Competence And Governance View

This article studies density and strength of ties in innovation networks. It combines issues of ‘competence’ with issues of ‘governance’. It argues that in networks for exploration there are good reasons, counter to the thesis of the ‘strength of weak ties’, for a dense structure of ties that are strong in most dimensions. In exploitation, there are good reasons for structures that are non-dense, with ties that are strong in other dimensions than in networks for exploration. Evidence is presented from two longitudinal empirical studies of the emergence and development of networks in the multimedia and pharmaceutical biotechnology industries.governance;innovation;networks;biotechnology;multi-media;strength of ties

Density and strength of ties in innovation networks: a competence and governance view.

innovation, networks

Angles and devices for quantum approximate optimization

A potential application of emerging Noisy Intermediate-Scale Quantum (NISQ) devices is that of approximately solving combinatorial optimization problems. This thesis investigates a gate-based algorithm for this purpose, the Quantum Approximate Optimization Algorithm (QAOA), in two major themes. First, we examine how the QAOA resolves the problems it is designed to solve. We take a statistical view of the algorithm applied to ensembles of problems, first, considering a highly symmetric version of the algorithm, using Grover drivers. In this highly symmetric context, we find a simple dependence of the QAOA state’s expected value on how values of the cost function are distributed. Furthering this theme, we demonstrate that, generally, QAOA performance depends on problem statistics with respect to a metric induced by a chosen driver Hamiltonian. We obtain a method for evaluating QAOA performance on worst-case problems, those of random costs, for differing driver choices. Second, we investigate a QAOA context with device control occurring only via single-qubit gates, rather than using individually programmable one- and two-qubit gates. In this reduced control overhead scheme---the digital-analog scheme---the complexity of devices running QAOA circuits is decreased at the cost of errors which are shown to be non-harmful in certain regimes. We then explore hypothetical device designs one could use for this purpose.Eine mögliche Anwendung für “Noisy Intermediate-Scale Quantum devices” (NISQ devices) ist die näherungsweise Lösung von kombinatorischen Optimierungsproblemen. Die vorliegende Arbeit untersucht anhand zweier Hauptthemen einen gatterbasierten Algorithmus, den sogenannten “Quantum Approximate Optimization Algorithm” (QAOA). Zuerst prüfen wir, wie der QAOA jene Probleme löst, für die er entwickelt wurde. Wir betrachten den Algorithmus in einer Kombination mit hochsymmetrischen Grover-Treibern für statistische Ensembles von Probleminstanzen. In diesem Kontext finden wir eine einfache Abhängigkeit von der Verteilung der Kostenfunktionswerte. Weiterführend zeigen wir, dass die QAOA-Leistung generell von der Problemstatistik in Bezug auf eine durch den gewählten Treiber-Hamiltonian induzierte Metrik abhängt. Wir erhalten eine Methode zur Bewertung der QAOA-Leistung bei schwersten Problemen (solche zufälliger Kosten) für unterschiedliche Treiberauswahlen. Zweitens untersuchen wir eine QAOA-Variante, bei der sich die Hardware- Kontrolle nur auf Ein-Qubit-Gatter anstatt individuell programmierbare Ein- und Zwei-Qubit-Gatter erstreckt. In diesem reduzierten Kontrollaufwandsschema—dem digital-analogen Schema—sinkt die Komplexität der Hardware, welche die QAOASchaltungen ausführt, auf Kosten von Fehlern, die in bestimmten Bereichen als ungefährlich nachgewiesen werden. Danach erkunden wir hypothetische Hardware- Konzepte, die für diesen Zweck genutzt werden könnten

Density And Strength Of Ties In Innovation Networks: A Competence And Governance View

This article studies density and strength of ties in innovation networks. It combines issues of ‘competence’ with issues of ‘governance’. It argues that in networks for exploration there are good reasons, counter to the thesis of the ‘strength of weak ties’, for a dense structure of ties that are strong in most dimensions. In exploitation, there are good reasons for structures that are non-dense, with ties that are strong in other dimensions than in networks for exploration. Evidence is presented from two longitudinal empirical studies of the emergence and development of networks in the multimedia and pharmaceutical biotechnology industries