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Author(s): Mildred K. Cho [sup.1] Author Affiliations: (1) Stanford Center for Biomedical Ethics, Stanford University, Stanford, USA In artificial intelligence (AI)-based predictive models, bias--defined as unfair systematic error--is a growing [...], AI-based models may amplify pre-existing human bias within datasets; addressing this problem will require a fundamental realignment of the culture of software development.

Abstract Chapter 7 of Library Technology Reports (vol 49, no. 8), 'Streamlining Information Services Using Chatbots, ' discusses how to use the data generated by chatbots. Reviewing conversation logs is [...]

Abstract Chapter 3 of Library Technology Reports (vol 49, no. 8), 'Streamlining Information Services Using Chatbots,' describes elements in AIML The basic structure of AIML is simple; one can create [...]

Abstract Chapter 2 of Library Technology Reports (vol. 49, no. 8), 'Streamlining Information Services Using Chatbots,' introduces AIML and ChatScript, the two most viable languages for creating a chatbot While [...]

By studying the behavior of several programs that crash due to memory errors, we observed that locating the errors can be challenging because significant propagation of corrupt memory values can occur prior to the point of the crash. In this article, we present an automated approach for locating memory errors in the presence of memory corruption propagation. Our approach leverages the information revealed by a program crash: when a crash occurs, this reveals a subset of the memory corruption that exists in the execution. By suppressing (nullifying) the effect of this known corruption during execution, the crash is avoided and any remaining (hidden) corruption may then be exposed by subsequent crashes. The newly exposed corruption can then be suppressed in turn. By iterating this process until no further crashes occur, the first point of memory corruption--and the likely root cause of the program failure--can be identified. However, this iterative approach may terminate prematurely, since programs may not crash even when memory corruption is present during execution. To address this, we show how crashes can be exposed in an execution by manipulating the relative ordering of particular variables within memory. By revealing crashes through this variable re-ordering, the effectiveness and applicability of the execution suppression approach can be improved. We describe a set of experiments illustrating the effectiveness of our approach in consistently and precisely identifying the first points of memory corruption in executions that fail due to memory errors. We also discuss a baseline software implementation of execution suppression that incurs an average overhead of 7.2x, and describe how to reduce this overhead to 1.8x through hardware support. Categories and Subject Descriptors: D.2.4 [Software Engineering]: Software/Program Verification--Reliability; D.2.5 [Software Engineering]: Testing and Debugging--Debugging aids; D.3.4 [Programming Languages]: Processors--Debuggers General Terms: Algorithms, Experimentation, Performance, Reliability, Verification Additional Key Words and Phrases: Execution suppression, fault localization, hardware support, memory corruption propagation, memory errors, variable re-ordering DOI = 10.1145/1745312.1745314

This article addresses the verification of properties of imperative programs with recursive procedure calls, heap-allocated storage, and destructive updating of pointer-valued fields, that is, interprocedural shape analysis. The article makes three contributions. --It introduces a new method for abstracting relations over memory configurations for use in abstract interpretation. --It shows how this method furnishes the elements needed for a compositional approach to shape analysis. In particular, abstracted relations are used to represent the shape transformation performed by a sequence of operations, and an overapproximation to relational composition can be performed using the meet operation of the domain of abstracted relations. --It applies these ideas in a new algorithm for context-sensitive interprocedural shape analysis. The algorithm creates procedure summaries using abstracted relations over memory configurations, and the meet-based composition operation provides a way to apply the summary transformer for a procedure P at each call site from which P is called. The algorithm has been applied successfully to establish properties of both (i) recursive programs that manipulate lists and (ii) recursive programs that manipulate binary trees. Categories and Subject Descriptors: D.2.4 [Software Engineering]: Software/Program Verification Assertion checkers; D.2.5 [Software Engineering]: Testing and Debugging--Symbolic execution; D.3.3 [Programming Languages]: Language Constructs and Features--Data types and structures; dynamic storage management, procedures, functions and subroutines; recursion; E.1 [Data]: Data Structures--Lists, stacks and queues, trees; E.2 [Data]: Data Storage Representations--Composite structures; linked representations; F.3.1 [Logics and Meanings of Programs]: Specifying and Verifying and Reasoning about Programs--Assertions; invariants General Terms: Algorithms, Languages, Theory, Verification Additional Key Words and Phrases: Abstract interpretation, context-sensitive analysis, interprocedural dataflow analysis, destructive updating, pointer analysis, shape analysis, static analysis, 3-valued logic DOI = 10.1145/1667048.1667050

Pluggable types enable users to enforce multiple type systems in one programming language. We have developed a suite of tools, called the JAvACOP framework, that allows developers to create pluggable type systems for Java. JAvACOP provides a simple declarative language in which program constraints are defined over a program's abstract syntax tree. The JAvACOP compiler automatically enforces these constraints on programs during compilation. The JAvACOP framework also includes a dataflow analysis API in order to support type systems which depend on flow-sensitive information. Finally, JAvACOP includes a novel test framework which helps users gain confidence in the correctness of their pluggable type systems. We demonstrate the framework by discussing a number of pluggable type systems which have been implemented in JAvACOP in order to detect errors and enforce strong invariants in programs. These type systems range from general-purpose checkers, such as a type system for nonnull references, to domain-specific ones, such as a checker for conformance to a library's usage rules. Categories and Subject Descriptors: D.1.5 [Programming Techniques]: Object-oriented Programming; D.2.1 [Software Engineering]: Requirements/Specifications--Tools General Terms: Design, Languages, Reliability Additional Key Words and Phrases: JAvACOP, ,pluggable type systems DOI = 10.1145/1667048.1667049