複数バージョンのあるソフトウェアの自動検証・検査 : 複数バージョン管理時代のソフトウェアの品質向上

学位の種別: 課程博士審査委員会委員 : (主査)東京大学准教授 佐藤 周行, 東京大学教授 相田 仁, 東京大学教授 峯松 信明, 東京大学准教授 小川 剛史, 東京大学准教授 鶴岡 慶雅, 東京大学准教授 近山 隆, 日本IBMシニアリサーチャー 河内谷 清久仁University of Tokyo(東京大学

Towards Model Checking of Network Applications for IoT System Development

With the expansion of the Internet, Internet of Things (IoT) gains lots of interest from industries and academia. IoT applications enable human-to-device and device-to-device interactions. For a successful deployment of IoT systems and services, software reliability is a very important requirement for IoT to ensure that data/messages have been received and performed properly in a timely manner. The concurrent connections of embedded sensors and actuators are nondeterministic in nature which makes testing insufficient to guarantee program correctness. In contrast, model checking techniques explore the entire behavior of a system under test (SUT) in brute-force and systematic manner. It investigates each reachable state for different thread schedules. Recent model checking techniques have been applied directly to networked programs. This paper reviews model checking techniques for networked applications and presents their strengths and limitations. A preliminary proposal for model checking of networked applications that addresses the identified gap is presented

Prototipo telemático de visión artificial para el reconocimiento de características en personas y vehículos

In a world increasingly connected with technology and with the growing need for security in all aspects of life, this project arises where the problem of security in educational establishments will be addressed, but it can be used in many areas, such as in hospitals, parking lots, securities transporters, airports, etc. This prototype aims to recognize patterns (Vehicle Plates) and characteristics (Facial Patterns), one of the main premises of the current project was the use of free software, to create a successful and easy-to-use solution.En un mundo cada vez más conectado con la tecnología y con la creciente necesidad de seguridad en todos los aspectos de la vida, surge este proyecto donde se abordará el problema de seguridad en los establecimientos educativos, pero que puede ser utilizado en muchos ámbitos, como en hospitales, parqueaderos, transportadoras de valores, aeropuertos, entidades militares, etc. Este prototipo tiene como objetivo el reconocimiento de patrones (Placas Vehiculares) y de características (Patrones Faciales), una de las premisas principales del actual proyecto fue la utilización de software libre, para crear una solución acertada y de fácil utilización

Detecting Coordination Problems in Collaborative Software Development Environments

Software development is rarely an individual effort and generally involves teams of developers collaborating to generate good reliable code. Among the software code there exist technical dependencies that arise from software components using services from other components. The different ways of assigning the design, development, and testing of these software modules to people can cause various coordination problems among them. We claim\ud that the collaboration of the developers, designers and testers must be related to and governed by the technical task structure. These collaboration practices are handled in what we call Socio-Technical Patterns.\ud The TESNA project (Technical Social Network Analysis) we report on in this paper addresses this issue. We propose a method and a tool that a project manager can use in order to detect the socio-technical coordination problems. We test the method and tool in a case study of a small and innovative software product company

Intuitionistic Partition based Conceptual Granulation Topic-Term Modeling

Document Analysis represented in vector space model is often used in information retrieval, topic analysis, and automatic classification. However, it hardly deals with fuzzy information and decision-making problems. To account this, Intuitionistic partition based cosine similarity measure between topic/terms and correlation between document/topic are proposed for evaluation. Conceptual granulation is emphasized in the decision matrix expressed conventionally as tf-idf. A local clustering of topic-terms and document-topics results in comparing dependent terms with membership degree using cosine similarity measure and correlation. A preprocessing of documents with intuitionistic fuzzy sets results in efficient classification of large corpus. But it depends on the datasets chosen. The proposed method effectively works well with large sized categorized corpus

Model Checking of Distributed Multi-Threaded Java Applications

In this dissertation, we focus on the verification of distributed Java applications composed of communicating multithreaded processes. We choose model checking as the verification technique. We propose an instance of the so-called centralization approach which allows for model checking multiple communicating processes. The main challenge of applying centralization is keeping data separated between different processes. In our approach, this issue is addressed through a new class-loading model. As one of our contributions, we implement our approach within an existing model checker, Java PathFinder (JPF). To account for interactions between processes, our approach provides the model checker with a model of interprocess communication. Moreover, our model allows for systematically exploring potential exceptional control flows caused by network failures. We also apply a partial order reduction (POR) algorithm to reduce the state space of distributed applications, and we prove that our POR algorithm preserves deadlocks. Furthermore, we propose an automatic approach to capture interactions between the system being verified and external resources, such as cloud computing services. The dissertation also discusses how our approach is superior to existing approaches. Our approach exhibits better performance which is mainly due to the POR technique. Furthermore, our approach allows for verifying a considerably larger class of applications without the need for any manual modeling, and it has been successfully used to detect bugs that cannot be found using previous work