Software-Architecture Recovery from Machine Code

In this paper, we present a tool, called Lego, which recovers object-oriented software architecture from stripped binaries. Lego takes a stripped binary as input, and uses information obtained from dynamic analysis to (i) group the functions in the binary into classes, and (ii) identify inheritance and composition relationships between the inferred classes. The information obtained by Lego can be used for reengineering legacy software, and for understanding the architecture of software systems that lack documentation and source code. Our experiments show that the class hierarchies recovered by Lego have a high degree of agreement---measured in terms of precision and recall---with the hierarchy defined in the source code

Proximal Methods for Hierarchical Sparse Coding

Sparse coding consists in representing signals as sparse linear combinations of atoms selected from a dictionary. We consider an extension of this framework where the atoms are further assumed to be embedded in a tree. This is achieved using a recently introduced tree-structured sparse regularization norm, which has proven useful in several applications. This norm leads to regularized problems that are difficult to optimize, and we propose in this paper efficient algorithms for solving them. More precisely, we show that the proximal operator associated with this norm is computable exactly via a dual approach that can be viewed as the composition of elementary proximal operators. Our procedure has a complexity linear, or close to linear, in the number of atoms, and allows the use of accelerated gradient techniques to solve the tree-structured sparse approximation problem at the same computational cost as traditional ones using the L1-norm. Our method is efficient and scales gracefully to millions of variables, which we illustrate in two types of applications: first, we consider fixed hierarchical dictionaries of wavelets to denoise natural images. Then, we apply our optimization tools in the context of dictionary learning, where learned dictionary elements naturally organize in a prespecified arborescent structure, leading to a better performance in reconstruction of natural image patches. When applied to text documents, our method learns hierarchies of topics, thus providing a competitive alternative to probabilistic topic models

Adaptive object management for distributed systems

This thesis describes an architecture supporting the management of pluggable software components and evaluates it against the requirement for an enterprise integration platform for the manufacturing and petrochemical industries. In a distributed environment, we need mechanisms to manage objects and their interactions. At the least, we must be able to create objects in different processes on different nodes; we must be able to link them together so that they can pass messages to each other across the network; and we must deliver their messages in a timely and reliable manner. Object based environments which support these services already exist, for example ANSAware(ANSA, 1989), DEC's Objectbroker(ACA,1992), Iona's Orbix(Orbix,1994)Yet such environments provide limited support for composing applications from pluggable components. Pluggability is the ability to install and configure a component into an environment dynamically when the component is used, without specifying static dependencies between components when they are produced. Pluggability is supported to a degree by dynamic binding. Components may be programmed to import references to other components and to explore their interfaces at runtime, without using static type dependencies. Yet thus overloads the component with the responsibility to explore bindings. What is still generally missing is an efficient general-purpose binding model for managing bindings between independently produced components. In addition, existing environments provide no clear strategy for dealing with fine grained objects. The overhead of runtime binding and remote messaging will severely reduce performance where there are a lot of objects with complex patterns of interaction. We need an adaptive approach to managing configurations of pluggable components according to the needs and constraints of the environment. Management is made difficult by embedding bindings in component implementations and by relying on strong typing as the only means of verifying and validating bindings. To solve these problems we have built a set of configuration tools on top of an existing distributed support environment. Specification tools facilitate the construction of independent pluggable components. Visual composition tools facilitate the configuration of components into applications and the verification of composite behaviours. A configuration model is constructed which maintains the environmental state. Adaptive management is made possible by changing the management policy according to this state. Such policy changes affect the location of objects, their bindings, and the choice of messaging system

TARGET: Rapid Capture of Process Knowledge

TARGET (Task Analysis/Rule Generation Tool) represents a new breed of tool that blends graphical process flow modeling capabilities with the function of a top-down reporting facility. Since NASA personnel frequently perform tasks that are primarily procedural in nature, TARGET models mission or task procedures and generates hierarchical reports as part of the process capture and analysis effort. Historically, capturing knowledge has proven to be one of the greatest barriers to the development of intelligent systems. Current practice generally requires lengthy interactions between the expert whose knowledge is to be captured and the knowledge engineer whose responsibility is to acquire and represent the expert's knowledge in a useful form. Although much research has been devoted to the development of methodologies and computer software to aid in the capture and representation of some types of knowledge, procedural knowledge has received relatively little attention. In essence, TARGET is one of the first tools of its kind, commercial or institutional, that is designed to support this type of knowledge capture undertaking. This paper will describe the design and development of TARGET for the acquisition and representation of procedural knowledge. The strategies employed by TARGET to support use by knowledge engineers, subject matter experts, programmers and managers will be discussed. This discussion includes the method by which the tool employs its graphical user interface to generate a task hierarchy report. Next, the approach to generate production rules for incorporation in and development of a CLIPS based expert system will be elaborated. TARGET also permits experts to visually describe procedural tasks as a common medium for knowledge refinement by the expert community and knowledge engineer making knowledge consensus possible. The paper briefly touches on the verification and validation issues facing the CLIPS rule generation aspects of TARGET. A description of efforts to support TARGET's interoperability issues on PCs, Macintoshes and UNIX workstations concludes the paper

Activity Report 2012. Project-Team RMOD. Analyses and Languages Constructs for Object-Oriented Application Evolution

Activity Report 2012 Project-Team RMOD Analyses and Languages Constructs for Object-Oriented Application Evolutio

Structuring fault-tolerant object-oriented systems using inheritance and delegation

PhD ThesisMany entities in the real world that a software system has to interact with, e.g., for controlling or monitoring purposes, exhibit different behaviour phases in their lifetime, in particular depending on whether or not they are functioning correctly. That is, these entities exhibit not only a normal behaviour phase but also one or more abnormal behaviour phases associated with the various faults which occur in the environment. These faults are referred to as environmental faults. In the object-oriented software, real-world entities are modeled as objects. In a classbased object-oriented language, such as C++, all objects of a given class must follow the same external behaviour, i.e., they have the same interface and associated implementation. However this requires that each object permanently belong to a particular class, imposing constraints on the mutability of the behaviour for an individual object. This thesis proposes solutions to the problem of finding means whereby objects representing real-world entities which exhibit various behaviour phases can make corresponding changes in their own behaviour in a clear and explicit way, rather than through status-checking code which is normally embedded in the implementation of various methods. Our proposed solution is (i) to define a hierarchy of different subclasses related to an object which corresponds to an external entity, each subclass implementing a different behaviour phase that the external entity can exhibit, and (ii) to arrange that each object forward the execution of its operations to the currently appropriate instance of this hierarchy of subclasses. We thus propose an object-oriented approach for the provision of environmental fault tolerance, which encapsulates the abnormal behaviour of "faulty" entities as objects (instances of the above mentioned subclasses). These abnormal behaviour variants are defined statically, and runtime access to them is implemented through a delegation mechanism which depends on the current phase of behaviour. Thus specific reconfiguration changes at the level of objects can be easily incorporated to a software system for tolerating environmental faults

Analysis of Random Fragment Profiles for the Detection of Structure-Activity Relationships

Substructure- or fragment-type descriptors are effective and widely used tools for chemical similarity searching and other applications in chemoinformatics and computer-aided drug discovery. Therefore, a large number of well-defined computational fragmentation schemes has been devised including hierarchical fragmentation of molecules for the analysis of core structures in drugs or retrosynthetic fragmentation of compounds for de novo ligand design. Furthermore, the generation of dictionaries of structural key-type descriptors that are important tools in pharmaceutical research involves knowledge-based fragment design. Currently more than 5 000 standard descriptors are available for the representation of molecular structures, and therefore the selection of suitable combinations of descriptors for specific chemoinformatic applications is a crucial task. This thesis departs from well-defined substructure design approaches. Randomly generated fragment populations are generated and mined for substructures associated with different compound classes. A novel method termed MolBlaster is introduced for the evaluation of molecular similarity relationships on the basis of randomly generated fragment populations. Fragment profiles of molecules are generated by random deletion of bonds in connectivity tables and quantitatively compared using entropy-based metrics. In test calculations, MolBlaster accurately reproduced a structural key-based similarity ranking of druglike molecules. To adapt the generation and comparison of random fragment populations for largescale compound screening, different fragmentation schemes are compared and a novel entropic similarity metric termed PSE is introduced for compound ranking. The approach is extensively tested on different compound activity classes with varying degrees of intra-class structural diversity and produces promising results in these calculations, comparable to similarity searching using state-of-the-art fingerprints. These results demonstrate the potential of randomly generated fragments for the detection of structure-activity relationships. Furthermore, a methodology to analyze random fragment populations at the molecular level of detail is introduced. It determines conditional probability relationships between fragments. Random fragment profiles are generated for an arbitrary set of molecules, and a frequency vector is assigned for each observed fragment. An algorithm is designed to compare frequency vectors and derive dependencies of fragment occurrence. Using calculated dependency values, random fragment populations can be organized in graphs that capture their relationships and make it possible to map fragment pathways of biologically active molecules. For sets of molecules having similar activity, unique fragment signatures, so-called Activity Class Characteristic Substructures (ACCS), are identified. Random fragment profiles are found to contain compound class-specific information and activity-specific fragment hierarchies. In virtual screening trials, short ACCS fingerprints perform well on many compound classes when compared to more complex state-of-the-art 2D fingerprints. In order to elucidate potential reasons for the high predictive utility of ACCS a thorough systematic analysis of their distribution in active and database compounds have been carried out. This reveals that the discriminatory power of ACCS results from the rare occurrence of individual and combinations of ACCS in screening databases. Furthermore, it is shown that ACCS sets isolated from random populations are typically found to form coherent molecular cores in active compounds. Characteristic core regions are already formed by small numbers of substructures and remain stable when more fragments are added. Thus, classspecific random fragment hierarchies encode meaningful structural information, providing a structural rationale for the signature character of activity-specific fragment hierarchies. It follows that compound-class-directed structural descriptors that do not depend on the application of predefined fragmentation or design schemes can be isolated from random fragment populations

An ontology to standardize research output of nutritional epidemiology : from paper-based standards to linked content

Background: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiology. Methods: Firstly, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Secondly, existing data standards and reporting guidelines for nutritional epidemiology were converted into an ontology. The terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Thirdly, the ontologies of the nutritional epidemiologic standards, reporting guidelines, and the core concepts were gathered in ONE. Three case studies were included to illustrate potential applications: (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts. Results: Ontologies for food and nutrition (n = 37), disease and specific population (n = 100), data description (n = 21), research description (n = 35), and supplementary (meta) data description (n = 44) were reviewed and listed. ONE consists of 339 classes: 79 new classes to describe data and 24 new classes to describe the content of manuscripts. Conclusion: ONE is a resource to automate data integration, searching, and browsing, and can be used to assess reporting completeness in nutritional epidemiology

Grifon: a graphical interface to an object oriented database

The aim of the research outlined in this thesis is to establish what type of interface would be most suitable for object oriented databases. In particular it examines how graphical interface technologies might be used to present the database in a clearer form. In support of the research, a prototype interface system has also been developed to a commercial database to illustrate the practicality of the development of such an interface, and the increased effectiveness of the resultant system. The thesis outlines the features provided by the interface, the benefits accrued from such a system, and the problems associated with its development. Finally, it examines how such a system fits into the current work being carried out in the area of user interaction with databases