Scalable Automated Incrementalization for Real-Time Static Analyses

This thesis proposes a framework for easy development of static analyses, whose results are incrementalized to provide instantaneous feedback in an integrated development environment (IDE). Today, IDEs feature many tools that have static analyses as their foundation to assess software quality and catch correctness problems. Yet, these tools often fail to provide instantaneous feedback and are thus restricted to nightly build processes. This precludes developers from fixing issues at their inception time, i.e., when the problem and the developed solution are both still fresh in mind. In order to provide instantaneous feedback, incrementalization is a well-known technique that utilizes the fact that developers make only small changes to the code and, hence, analysis results can be re-computed fast based on these changes. Yet, incrementalization requires carefully crafted static analyses. Thus, a manual approach to incrementalization is unattractive. Automated incrementalization can alleviate these problems and allows analyses writers to formulate their analyses as queries with the full data set in mind, without worrying over the semantics of incremental changes. Existing approaches to automated incrementalization utilize standard technologies, such as deductive databases, that provide declarative query languages, yet also require to materialize the full dataset in main-memory, i.e., the memory is permanently blocked by the data required for the analyses. Other standard technologies such as relational databases offer better scalability due to persistence, yet require large transaction times for data. Both technologies are not a perfect match for integrating static analyses into an IDE, since the underlying data, i.e., the code base, is already persisted and managed by the IDE. Hence, transitioning the data into a database is redundant work. In this thesis a novel approach is proposed that provides a declarative query language and automated incrementalization, yet retains in memory only a necessary minimum of data, i.e., only the data that is required for the incrementalization. The approach allows to declare static analyses as incrementally maintained views, where the underlying formalism for incrementalization is the relational algebra with extensions for object-orientation and recursion. The algebra allows to deduce which data is the necessary minimum for incremental maintenance and indeed shows that many views are self-maintainable, i.e., do not require to materialize memory at all. In addition an optimization for the algebra is proposed that allows to widen the range of self-maintainable views, based on domain knowledge of the underlying data. The optimization works similar to declaring primary keys for databases, i.e., the optimization is declared on the schema of the data, and defines which data is incrementally maintained in the same scope. The scope makes all analyses (views) that correlate only data within the boundaries of the scope self-maintainable. The approach is implemented as an embedded domain specific language in a general-purpose programming language. The implementation can be understood as a database-like engine with an SQL-style query language and the execution semantics of the relational algebra. As such the system is a general purpose database-like query engine and can be used to incrementalize other domains than static analyses. To evaluate the approach a large variety of static analyses were sampled from real-world tools and formulated as incrementally maintained views in the implemented engine

ULTRA - A Logic Transaction Programming Language

Rule-based language for the specification of complex database updates and transactions. Formal treatment of the syntax and the declarative semanticsRegelbasierte Sprache zur Spezifikation komplexer Datenbank-Operationen und Transaktionen. Formle Behandlung von Syntax und deklarativer Semantik

Site Controller: A System for Computer-Aided Civil Engineering and Construction

A revolution\0\0\0 in earthmoving, a $100 billion industry, can be achieved with three components: the GPS location system, sensors and computers in bulldozers, and SITE CONTROLLER, a central computer system that maintains design data and directs operations. The first two components are widely available; I built SITE CONTROLLER to complete the triangle and describe it here. SITE CONTROLLER assists civil engineers in the design, estimation, and construction of earthworks, including hazardous waste site remediation. The core of SITE CONTROLLER is a site modelling system that represents existing and prospective terrain shapes, roads, hydrology, etc. Around this core are analysis, simulation, and vehicle control tools. Integrating these modules into one program enables civil engineers and contractors to use a single interface and database throughout the life of a project

Database system architecture supporting coexisting query languages and data models

SIGLELD:D48239/84 / BLDSC - British Library Document Supply CentreGBUnited Kingdo

An approach to modeling database activity

Results in the field of data modeling currently suffer from many of the same ills which plagued data management systems in the late 1960's. Advanced semantic modeling systems such as the Semantic Data Model and the Relational Model/Tasmania are extremely complex to understand as well as somewhat ad hoc in design. Such systems capture only static snapshots of activity in the world being modeled. On the other hand, behavioral models which do attempt to model system dynamics typically provide less overall modeling power than comprehensive semantic models. Further, the specifications of behavior which can be expressed with such models are themselves static snapshots which are not integrated with other database objects.This work describes one approach for capturing dynamic relationships by distilling the concepts found in semantic and behavioral data models into a small number of flexible constructs. The resulting Prototype Activity Modeling System (PAMS) captures the containment, feedback, operational, and state dependency roles of entities in the world being modeled. Further, these definitions of database activity are captured as database objects (rather than as a schema) so as to allow dynamic manipulation of entity roles.The key concept of the approach is the bundle - a purposefully designed extension of time-proven relational database modeling concepts which includes support for presentation ordering and complex Cartesian aggregations. By applying the basic nested bundle principle, it is possible to obtain complex hierarchies of static structural information. The static templates so constructed, when used with a non-procedural query language and the value nomination principle which reduces relations to scalar values when necessary, provide a conventional database modeling system for applications. By extending these templates with the non-procedural thunk principle which embeds query specifications within object definitions, variations caused by dependencies within the application can cause the apparent contents of the database description to change. When further extended by the activity monitoring principle which records the interaction between the application and its environment, these dynamic templates can account for changes outside the scope of the application

An intelligent Geographic Information System for design

Recent advances in geographic information systems (GIS) and artificial intelligence (AI) techniques have been summarised, concentrating on the theoretical aspects of their construction and use. Existing projects combining AI and GIS have also been discussed, with attention paid to the interfacing methods used and problems uncovered by the approaches. AI and GIS have been combined in this research to create an intelligent GIS for design. This has been applied to off-shore pipeline route design. The system was tested using data from a real pipeline design project. [Continues.

28th International Symposium on Temporal Representation and Reasoning (TIME 2021)

The 28th International Symposium on Temporal Representation and Reasoning (TIME 2021) was planned to take place in Klagenfurt, Austria, but had to move to an online conference due to the insecurities and restrictions caused by the pandemic. Since its frst edition in 1994, TIME Symposium is quite unique in the panorama of the scientifc conferences as its main goal is to bring together researchers from distinct research areas involving the management and representation of temporal data as well as the reasoning about temporal aspects of information. Moreover, TIME Symposium aims to bridge theoretical and applied research, as well as to serve as an interdisciplinary forum for exchange among researchers from the areas of artifcial intelligence, database management, logic and verifcation, and beyond