The Introduction of Clerp 9 Audit Regulation and its Impact on the Auditing Profession

This study examines the introduction of legally enforceable Australian Auditing Standards (ASAs) and the impact on the audit profession after their first year of implementation. This study is informed by regulation theories and potential costs, benefits and other impacts of the new regulatory regime identified by the Australian government’s April 2006 Regulation Impact Statement (RIS). This study collected relevant data through semi-structured in-depth interviews with the same key stakeholders as RIS (accounting firms, professional bodies and regulatory bodies). The results indicate significant differences to the government’s pre-implementation RIS expectations, as well as differences between stakeholder groups. Overall the accounting profession does not consider that the extra burden of demonstrating compliance with the legally enforceable ASAs has changed the audit process or audit outcomes. The auditing profession does not consider the extra burden of the new regime justifiable as it has not increased audit quality or public confidence, which were the main aims of the government’s regulatory intervention

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

Using informative behavior to increase engagement while learning from human reward

In this work, we address a relatively unexplored aspect of designing agents that learn from human reward. We investigate how an agent’s non-task behavior can affect a human trainer’s training and agent learning. We use the TAMER framework, which facilitates the training of agents by human-generated reward signals, i.e., judgements of the quality of the agent’s actions, as the foundation for our investigation. Then, starting from the premise that the interaction between the agent and the trainer should be bi-directional, we propose two new training interfaces to increase a human trainer’s active involvement in the training process and thereby improve the agent’s task performance. One provides information on the agent’s uncertainty which is a metric calculated as data coverage, the other on its performance. Our results from a 51-subject user study show that these interfaces can induce the trainers to train longer and give more feedback. The agent’s performance, however, increases only in response to the addition of performance-oriented information, not by sharing uncertainty levels. These results suggest that the organizational maxim about human behavior, “you get what you measure”—i.e., sharing metrics with people causes them to focus on optimizing those metrics while de-emphasizing other objectives—also applies to the training of agents. Using principle component analysis, we show how trainers in the two conditions train agents differently. In addition, by simulating the influence of the agent’s uncertainty–informative behavior on a human’s training behavior, we show that trainers could be distracted by the agent sharing its uncertainty levels about its actions, giving poor feedback for the sake of reducing the agent’s uncertainty without improving the agent’s performance

Evaluating usefulness of software metrics: an industrial experience report

Contains fulltext : 116980.pdf (publisher's version ) (Open Access)ICSE'13: 35 International Conference on Software Engineering, May 18th-26th, 2013, San Francisco, C

Getting what you measure

Contains fulltext : 103392.pdf (preprint version ) (Open Access

Real-space study of the growth of magnesium on ruthenium

The growth of magnesium on ruthenium has been studied by low-energy electron microscopy (LEEM) and scanning tunneling microscopy (STM). In LEEM, a layer-by-layer growth is observed except in the first monolayer, where the completion of the first layer in inferred by a clear peak in electron reflectivity. Desorption from the films is readily observable at 400 K. Real-space STM and low-energy electron diffraction confirm that sub-monolayer coverage presents a moiré pattern with a 12 Å periodicity, which evolves with further Mg deposition by compressing the Mg layer to a 22 Å periodicity. Layer-by-layer growth is followed in LEEM up to 10 ML. On films several ML thick a substantial density of stacking faults are observed by dark-field imaging on large terraces of the substrate, while screw dislocations appear in the stepped areas. The latter are suggested to result from the mismatch in heights of the Mg and Ru steps. Quantum size effect oscillations in the reflected LEEM intensity are observed as a function of thickness, indicating an abrupt Mg/Ru interface