Content-based Video Retrieval by Integrating Spatio-Temporal and Stochastic Recognition of Events

As amounts of publicly available video data grow the need to query this data efficiently becomes significant. Consequently content-based retrieval of video data turns out to be a challenging and important problem. We address the specific aspect of inferring semantics automatically from raw video data. In particular, we introduce a new video data model that supports the integrated use of two different approaches for mapping low-level features to high-level concepts. Firstly, the model is extended with a rule-based approach that supports spatio-temporal formalization of high-level concepts, and then with a stochastic approach. Furthermore, results on real tennis video data are presented, demonstrating the validity of both approaches, as well us advantages of their integrated us

Automatically Leveraging MapReduce Frameworks for Data-Intensive Applications

MapReduce is a popular programming paradigm for developing large-scale, data-intensive computation. Many frameworks that implement this paradigm have recently been developed. To leverage these frameworks, however, developers must become familiar with their APIs and rewrite existing code. Casper is a new tool that automatically translates sequential Java programs into the MapReduce paradigm. Casper identifies potential code fragments to rewrite and translates them in two steps: (1) Casper uses program synthesis to search for a program summary (i.e., a functional specification) of each code fragment. The summary is expressed using a high-level intermediate language resembling the MapReduce paradigm and verified to be semantically equivalent to the original using a theorem prover. (2) Casper generates executable code from the summary, using either the Hadoop, Spark, or Flink API. We evaluated Casper by automatically converting real-world, sequential Java benchmarks to MapReduce. The resulting benchmarks perform up to 48.2x faster compared to the original.Comment: 12 pages, additional 4 pages of references and appendi

Recovering Grammar Relationships for the Java Language Specification

Grammar convergence is a method that helps discovering relationships between different grammars of the same language or different language versions. The key element of the method is the operational, transformation-based representation of those relationships. Given input grammars for convergence, they are transformed until they are structurally equal. The transformations are composed from primitive operators; properties of these operators and the composed chains provide quantitative and qualitative insight into the relationships between the grammars at hand. We describe a refined method for grammar convergence, and we use it in a major study, where we recover the relationships between all the grammars that occur in the different versions of the Java Language Specification (JLS). The relationships are represented as grammar transformation chains that capture all accidental or intended differences between the JLS grammars. This method is mechanized and driven by nominal and structural differences between pairs of grammars that are subject to asymmetric, binary convergence steps. We present the underlying operator suite for grammar transformation in detail, and we illustrate the suite with many examples of transformations on the JLS grammars. We also describe the extraction effort, which was needed to make the JLS grammars amenable to automated processing. We include substantial metadata about the convergence process for the JLS so that the effort becomes reproducible and transparent

Parsing for agile modeling

Agile modeling refers to a set of methods that allow for a quick initial development of an importer and its further refinement. These requirements are not met simultaneously by the current parsing technology. Problems with parsing became a bottleneck in our research of agile modeling. In this thesis we introduce a novel approach to specify and build parsers. Our approach allows for expressive, tolerant and composable parsers without sacrificing performance. The approach is based on a context-sensitive extension of parsing expression grammars that allows a grammar engineer to specify complex language restrictions. To insure high parsing performance we automatically analyze a grammar definition and choose different parsing strategies for different parts of the grammar. We show that context-sensitive parsing expression grammars allow for highly composable, tolerant and variable-grained parsers that can be easily refined. Different parsing strategies significantly insure high-performance of parsers without sacrificing expressiveness of the underlying grammars

APRT – Another Pattern Recognition Tool

Understanding and using Design Patterns improves software quality through better comprehension of programs for both experienced developers and relative novices. Often design patterns are learned through simplified “toy” programs and exemplars that foreground the structure of the pattern. In production code the objects and methods that comprise the pattern can be hidden within a complex mesh of intra-code relationships. This paper introduces APRT, an ANTLR-based tool that recovers the structure of both static and dynamic patterns from large codebases so that they can be studied in context

Preventing Atomicity Violations with Contracts

Software developers are expected to protect concurrent accesses to shared regions of memory with some mutual exclusion primitive that ensures atomicity properties to a sequence of program statements. This approach prevents data races but may fail to provide all necessary correctness properties.The composition of correlated atomic operations without further synchronization may cause atomicity violations. Atomic violations may be avoided by grouping the correlated atomic regions in a single larger atomic scope. Concurrent programs are particularly prone to atomicity violations when they use services provided by third party packages or modules, since the programmer may fail to identify which services are correlated. In this paper we propose to use contracts for concurrency, where the developer of a module writes a set of contract terms that specify which methods are correlated and must be executed in the same atomic scope. These contracts are then used to verify the correctness of the main program with respect to the usage of the module(s). If a contract is well defined and complete, and the main program respects it, then the program is safe from atomicity violations with respect to that module. We also propose a static analysis based methodology to verify contracts for concurrency that we applied to some real-world software packages. The bug we found in Tomcat 6.0 was immediately acknowledged and corrected by its development team

Extracting Models from Source Code in Software Modernization

International audienceModel-driven software modernization is a discipline in which model-driven development (MDD) techniques are used in the modernization of legacy systems. When existing software artifacts are evolved, they must be transformed into models to apply MDD techniques such as model transformations. Since most modernization scenarios (e.g., application migration) involve dealing with code in general-purpose programming languages (GPL), the extraction of models from GPL code is an essential task in a model-based modernization process. This activity could be performed by tools to bridge grammarware and MDD technical spaces, which is normally carried out by dedicated parsers. Grammar-to-Model Transformation Language (Gra2MoL) is a domain-specific language (DSL) tailored to the extraction of models from GPL code. This DSL is actually a text-to-model transformation language which can be applied to any code conforming to a grammar. Gra2MoL aims to reduce the effort needed to implement grammarware-MDD bridges, since building dedicated parsers is a complex and time-consuming task. Like ATL and RubyTL languages, Gra2MoL incorporates the binding concept needed to write mappings between grammar elements and metamodel elements in a simple declarative style. The language also provides a powerful query language which eases the retrieval of scattered information in syntax trees. Moreover, it incorporates extensibility and grammar reuse mechanisms. This paper describes Gra2MoL in detail and includes a case study based on the application of the language in the extraction of models from Delphi code

A Syntactical Reverse Engineering Approach to Fourth Generation Programming Languages Using Formal Methods

Fourth-generation programming languages (4GLs) feature rapid development with minimum configuration required by developers. However, 4GLs can suffer from limitations such as high maintenance cost and legacy software practices. Reverse engineering an existing large legacy 4GL system into a currently maintainable programming language can be a cheaper and more effective solution than rewriting from scratch. Tools do not exist so far, for reverse engineering proprietary XML-like and model-driven 4GLs where the full language specification is not in the public domain. This research has developed a novel method of reverse engineering some of the syntax of such 4GLs (with Uniface as an exemplar) derived from a particular system, with a view to providing a reliable method to translate/transpile that system's code and data structures into a modern object-oriented language (such as C\#). The method was also applied, although only to a limited extent, to some other 4GLs, Informix and Apex, to show that it was in principle more broadly applicable. A novel testing method that the syntax had been successfully translated was provided using 'abstract syntax trees'. The novel method took manually crafted grammar rules, together with Encapsulated Document Object Model based data from the source language and then used parsers to produce syntactically valid and equivalent code in the target/output language. This proof of concept research has provided a methodology plus sample code to automate part of the process. The methodology comprised a set of manual or semi-automated steps. Further automation is left for future research. In principle, the author's method could be extended to allow the reverse engineering recovery of the syntax of systems developed in other proprietary 4GLs. This would reduce time and cost for the ongoing maintenance of such systems by enabling their software engineers to work using modern object-oriented languages, methodologies, tools and techniques

Towards using concurrent Java API correctly

Concurrent Programs are hard to analyze or debug due to the complex program logic and unpredictable execution environment. In practice, ordinary programmers often adopt existing well-designed concurrency related API (e.g., those in java.util.concurrent) so as to avoid dealing with these issues. These API can however often be used incorrectly, which results in hardto-debug concurrent bugs. In this work, we propose an approach for enforcing the correct usage of concurrency-related Java API. Our idea is to annotate concurrency-related Java classes with annotations related to misuse of these API and develop lightweight type checker to detect concurrent API misuse based on the annotations. To automate this process, we need to solve two problems: (1) how do we obtain annotations of the relevant API; and (2) how do we systematically detect concurrent API misuse based on the annotations? We solve the first problem by extracting annotations from the API documentation using natural language processing techniques. We solve the second problem by implementing our type checkers in the Checker Framework to detect concurrent API misuse. We apply our approach to extract annotations for all classes in the Java standard library and use them to detect concurrent API misuse in open source projects on GitHub. We confirm that concurrent API misuse is common and often results in bugs or inefficiency.No Full Tex