JWalk: a tool for lazy, systematic testing of java classes by design introspection and user interaction

Popular software testing tools, such as JUnit, allow frequent retesting of modified code; yet the manually created test scripts are often seriously incomplete. A unit-testing tool called JWalk has therefore been developed to address the need for systematic unit testing within the context of agile methods. The tool operates directly on the compiled code for Java classes and uses a new lazy method for inducing the changing design of a class on the fly. This is achieved partly through introspection, using Java’s reflection capability, and partly through interaction with the user, constructing and saving test oracles on the fly. Predictive rules reduce the number of oracle values that must be confirmed by the tester. Without human intervention, JWalk performs bounded exhaustive exploration of the class’s method protocols and may be directed to explore the space of algebraic constructions, or the intended design state-space of the tested class. With some human interaction, JWalk performs up to the equivalent of fully automated state-based testing, from a specification that was acquired incrementally

Live Access Control Policy Error Detection Through Hardware

Access Control (AC) is a widely used security measure designed to protect resources and infrastructure in an information system. The integrity of the AC policy is crucial to the protection of the system. Errors within an AC policy may cause many vulnerabilities such as information leaks, information loss, and malicious activities. Thus, such errors must be detected and promptly fixed. However, current AC error detection models do not allow for real-time error detection, nor do they provide the source of errors. This thesis presents a live error detection model called LogicDetect which utilizes emulated Boolean digital logic circuits to provide continual feedback and error source identification. The outcome is a new error detection model allowing policy creators to identify the source of errors quickly and accurately at any stage during policy creation

Behavior models for software architecture

Monterey Phoenix (MP) is an approach to formal software system architecture specification based on behavior models. Architecture modeling focuses not only on the activities and interactions within the system, but also on the interactions between the system and its environment, providing an abstraction for interaction specification. The behavior of the system is defined as a set of events (event trace) with two basic relations: precedence and inclusion. The structure of possible event traces is specified using event grammars and other constraints organized into schemas. The separation of the interaction description from the components behavior is an essential MP feature. The schema framework is amenable to stepwise architecture refinement, reuse, composition, visualization, and multiple view extraction. The approach yields a basis for executable architecture specification supporting early testing and verification, systematic use case generation, and performance estimates with automated tools.Consortium for Robotics and Unmanned Systems Education and Research (CRUSER)Consortium for Robotics and Unmanned Systems Education and Research (CRUSER)Approved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

Designing IS service strategy: an information acceleration approach

Information technology-based innovation involves considerable risk that requires insight and foresight. Yet, our understanding of how managers develop the insight to support new breakthrough applications is limited and remains obscured by high levels of technical and market uncertainty. This paper applies a new experimental method based on “discrete choice analysis” and “information acceleration” to directly examine how decisions are made in a way that is behaviourally sound. The method is highly applicable to information systems researchers because it provides relative importance measures on a common scale, greater control over alternate explanations and stronger evidence of causality. The practical implications are that information acceleration reduces the levels of uncertainty and generates a more accurate rationale for IS service strategy decisions

Praspel: Contract-Driven Testing for PHP using Realistic Domains

We present an integrated contract-based testing framework for PHP. It relies on a behavioral interface specification language called Praspel, for "PHP Realistic Annotation and Specification Language". Using Praspel developers can easily annotate their PHP scripts with formal contracts, namely class invariants, and method pre- and postconditions. These contracts describe assertions either by predicates or by assigning realistic domains to data. Realistic domains introduce types in PHP and describe complex structures frequently encountered in applications, such as email addresses or SQL queries. Realistic domains display two properties: predicability, which allows to check if a data belongs to a given realistic domain, and samplability, which allows to generate valid data. This paper introduces coverage criteria dedicated to contracts, designed to exhibit relevant behaviors of the annotated methods. Test data are then computed to satisfy these coverage criteria, by using dedicated data generators for complex realistic domains, such as arrays or strings. This framework has been implemented and disseminated within the PHP community, which gave us feedback on their usage of the tool and the relevance of this integrated process with respect to their practice of manual testing

International conference on software engineering and knowledge engineering: Session chair

The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing. The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome

Characterization of Single Cycle CA and its Application in Pattern Classification

AbstractThe special class of irreversible cellular automaton (CA) with multiple attractors is of immense interest to the CA researchers. Characterization of such a CA is the necessity to devise CA based solutions for diverse applications. This work explores the essential properties of CA attractors towards characterization of the 1-dimensional cellular automata with point states (single length cycle attractors). The concept of Reachability Tree is introduced for such characterization. It enables identification of the pseudo-exhaustive bits (PE bits) of a CA defining its point states. A theoretical framework has been developed to devise schemes for synthesizing a single length cycle multiple attractor CA with the specific set of PE bits. It also results in a linear time solution while synthesizing a CA for the given set of attractors and its PE bits. The experimentation establishes that the proposed CA synthesis scheme is most effective in designing the efficient pattern classifiers for wide range of applications

An investigation of the role of context in retrieval of information from semantic memory

The research reported here examines how a person' s knowledge of the world is used in language recognition and production. Essentially it is concerned with the importance of a word's meaning as a factor in its recognition by a listener or reader and is its production by a speaker or writer. This area of research overlays with a great many areas in psychology, drawing upon research in attention, pattern recognition, memory, psycholinguistics and thought . It is necessary to give some working definitions of the terms used. The definition of semantic memory used here is that supplied by Tulving (1972, p 386): "Semantic memory is the memory necessary for the use of a language. It is a mental thesaurus, the organized knowledge a person possesses about words and other verbal symbols, their meanings and referents, about relations among them and about rules, formulas and algorithms for the manipulation of these symbols, concepts and relations." The contents of semantic memory are typically what a person would say that he "knows" rather than what he "remembers". e . g. a person might say "I know canaries are yellow" whereas "I remember canaries are yellow" would not "sound right" to most native English speakers. This also illustrates an important property of semantic memory. The knowledge it contains is to a large extent common to members of a given culture. There will of course be individual differences but a sufficient body of knowledge will be shared in order to allow communication between persons. Retrieval from semantic memory is used here to refer to any process that involves making use of such stored knowledge. This may range from simply deciding that a particular sound pattern has occurred in speech before to verifying complex propositions. Context is restricted here to linguistic context. The question asked is how information provided by previous linguistic input affects processing of later input or output of language. The view of language comprehension taken here is similar to Goodman's (1967) approach to reading. This approach is described as follows: " ... Reading is a psycholinguistic guessing game. It involves an interaction between thought and language. Efficient reading does not result from precise perceptions and identification of all elements but from skill in selecting the fewest, most productive cues necessary to produce guesses which are right first time. The ability to anticipate that which has not been seen, of course, is vital in reading, just as the ability to anticipate what has not yet been heard is vital in listening." (p 260) It is assumed here that a person's ability to anticipate is dependent upon the knowledge stored in semantic memory. The way this knowledge is used will in turn depend upon how it is organized. Since the Ancient Greeks the importance of organization in memory has been recognized but it is only relatively recently that psychologists have attempted to determine the principles underlying this organization. Since Quillian (1966) a number of models of how semantic memory is organized have been proposed. These will be discussed in the following sections. Many of the experiments reported here are concerned with what might be called "micro-context", that is how individual words, phrases and sentences affect recognition of incoming stimuli. Of course, the use of context goes far beyond the immediately preceding input but as yet there are no satisfactory theories, linguistic or psychological, that can deal with these wider aspects of language use. In fact there is still considerable disagreement over the processes involved in the recognition of single words, (see, for example, Rubenstein, Lewis and Rubenstein, 1971; Baron, 1973) . The approach taken to word recognition here is similar to Norman (1968) and Morton (1969). The notion which is central to both these authors and Goodman (see above) is the realization that no process can be analysed in isolation. The language system cannot decode the incoming sensory information without reference to stored knowledge. As Norman (1969, p 3) describes the role of memory, "it provides the information about the past necessary for proper understanding of the present". Thus context indicates to the memory system what knowledge is relevant to the analysis of the current input. To summarize this approach the information provided by context (immediate past) is referred to semantic memory (past) which in turn helps to produce the best guess as to the nature of the current sensory input (present) or even the nature of input which has not yet arrived (future) . The problem examined in this research is how the organizational structure of knowledge in semantic memory influences this guessing process . Whether such guessing is an active process as suggested by some investigators (e . g. Liberman, Stevens and Halle) or a passive process suggested by others (e . g. Morton, Treisman) will be discussed in a later section