Teaching Tip: Teaching Expert Systems in a Postgraduate Accounting Degree Program

Teaching the concepts of expert systems to accounting students is often challenging, not only because these students are not equipped with the necessary technical knowledge to comprehend the concepts taught, but also due to the other various constraints (e.g., limited teaching hours and a diverse background of the students’ undergraduate disciplines) imposed on teaching and learning. A further difficulty is how to design a hands-on project so that, on the one hand, learning can be reinforced and, on the other hand, students are able to complete the projects with their limited technical knowledge and background. This article shares our experience in teaching an expert system component and designing a corresponding project in one of the first information technology courses for accounting students at the master’s level. A subsequent student feedback evaluation exercise was performed, showing that students were able to understand the expert system concepts and that they considered the project interesting and useful

How do environmental enterprise systems contribute to sustainability value? A practitioner-oriented framework

Environmental enterprise systems (EES) are integrated software services that offer a platform to automate and manage environmental sustainability processes, data, risk and reporting. EES are widely used in organisations, but their return depends on nurturing value creating mechanisms and pathways. Since the organisational value of EES has not been well researched and documented in the information systems literature, we have undertaken an exploratory practitioner literature analysis. The findings indicate that EES investment spurs the development of EES competence and EES-enabled capability which are associated with environmental efficiency and competitive values. Based on these findings and drawing from the dynamic capability theory, we contribute an EES value framework. This paper also illustrates to business organisations how to leverage EES’s potential to improve environmental sustainability without trading off economic outcome

Factors Influencing the Adoption of Environmental Enterprise Systems

An increasing number of organizations are shifting from spreadsheet-based tools to enterprise-grade software platforms, which we refer as environmental enterprise systems (EES), to manage environmental data, processes, resources, footprints, and commitments. Despite this trend, and in view of differences in EES modules, form and functions, why organizations choose EES software have not been researched. This is an important issue as it reflects, albeit indirectly, organizations’ commitment to environmental sustainability. Under the technology-organization-environment (TOE) framework and ecological sustainability context, this study investigated the factors that influence the adoption of EES in four Australian service organizations. The findings indicate limitations of precursor systems, relative advantages and perceived benefits of EES, and software experience of sustainability managers affect the decision to adopt an EES software. Additionally, IT-dependent environmental strategies, the complexity of environmental portfolio management, and commitments to voluntary sustainability reporting requirements influence both the adoption decision as well as the selection of the specific EES module. These findings contribute more nuanced insights to the body of knowledge on Enterprise Systems and Green Information Systems adoption

An Exploratory Study Into the Use and Value of Environmental Enterprise Systems

In the Information Systems discipline, there is growing recognition of the importance of enterprise systems’ (ES) users. ES users have traditionally been categorized into operational, managerial, and strategic groups. However, organizational structures are beginning to transform, potentially resulting in changes to the demarcations between user groups. This research applies the case study approach to explore users in a contemporary ES environment. The preliminary analysis provides support to indicate that the boundaries between user groups are changing. In addition a preliminary typology was created, which resulted in the identification of eight different types of operational users. Therefore this research challenges the current theoretical treatment of operational users

METTLE: a METamorphic testing approach to assessing and validating unsupervised machine LEarning systems

Unsupervised machine learning is the training of an artificial intelligence system using information that is neither classified nor labeled, with a view to modeling the underlying structure or distribution in a dataset. Since unsupervised machine learning systems are widely used in many real-world applications, assessing the appropriateness of these systems and validating their implementations with respect to individual users' requirements and specific application scenarios$\,/\,$contexts are indisputably two important tasks. Such assessment and validation tasks, however, are fairly challenging due to the absence of a priori knowledge of the data. In view of this challenge, we develop a $\textbf{MET}$amorphic $\textbf{T}$esting approach to assessing and validating unsupervised machine $\textbf{LE}$arning systems, abbreviated as METTLE. Our approach provides a new way to unveil the (possibly latent) characteristics of various machine learning systems, by explicitly considering the specific expectations and requirements of these systems from individual users' perspectives. To support METTLE, we have further formulated 11 generic metamorphic relations (MRs), covering users' generally expected characteristics that should be possessed by machine learning systems. To demonstrate the viability and effectiveness of METTLE we have performed an experiment involving six commonly used clustering systems. Our experiment has shown that, guided by user-defined MR-based adequacy criteria, end users are able to assess, validate, and select appropriate clustering systems in accordance with their own specific needs. Our investigation has also yielded insightful understanding and interpretation of the behavior of the machine learning systems from an end-user software engineering's perspective, rather than a designer's or implementor's perspective, who normally adopts a theoretical approach

Metamorphic testing: a review of challenges and opportunities

Metamorphic testing is an approach to both test case generation and test result verification. A central element is a set of metamorphic relations, which are necessary properties of the target function or algorithm in relation to multiple inputs and their expected outputs. Since its first publication, we have witnessed a rapidly increasing body of work examining metamorphic testing from various perspectives, including metamorphic relation identification, test case generation, integration with other software engineering techniques, and the validation and evaluation of software systems. In this paper, we review the current research of metamorphic testing and discuss the challenges yet to be addressed. We also present visions for further improvement of metamorphic testing and highlight opportunities for new research

How do environmental enterprise systems contribute to substainability value? A practitioner-oriented framework

Abstract: Environmental enterprise systems (EES) are integrated software services that offer a platform to automate and manage environmental sustainability processes, data, risk and reporting. EES are widely used in organisations, but their benefits depend on nurturing value creating mechanisms and pathways. Since the organisational value of EES has not been well researched and documented in the information systems literature, we have undertaken an exploratory practitioner literature analysis. The findings indicate that EES investment spurs the development of EES competence and EES-enabled capability which lead to environmental efficiency and competitive values. Based on these findings and drawing from the dynamic capability theory, we contribute an EES value framework. This paper also illustrates to business organisations how to leverage EES’s potential to improve environmental sustainability without trading off economic outcome

Introduction to the Special Issue on Test Oracles

Software testing is the de facto technique for correctness verification. Although there are different motivations and approaches to testing, fundamentally, it involves the running of test cases against the software under test. An important aspect is the ability to tell whether the execution results agree with the expected outcomes. The mechanism to determine the correctness of the results is called a test oracle. Unfortunately, such a mechanism does not always exist or may exist but cannot be feasibly used, which is known as the oracle problem. This is a major challenge to software testers, severely curtailing the application of testing approaches and methods to practical situations. In spite of the vast amount of interest in software testing, studies on test oracles drew much less attention than other aspects of software testing until quite recently. The increasing number of research activities surrounding the oracle problem reflects a growing interest in the area. This special issue documents some of the new contributions in software test oracles. We received a total of 19 submissions. Each submission has been reviewed by at least three reviewers. Six papers have been accepted for publication. In general, test oracle issues may involve identifying the expected program properties, test case generation, test sequencing and concurrency, test output verification, and fault localization. To deal with the identification of expected program properties, paper 1 titled “Automated Inference of Likely Metamorphic Relations for Model Transformations” by Troya et al. proposes a method of automatically inferring likely metamorphic relations, in the context of metamorphic testing, for the verification of model transformations. To handle test case generation and conduct run-time assertion checking, paper 2 titled “Contract-Based Testing for PHP with Praspel” by Dadeau et al. makes use of contracts, which enable the automation of these processes. To tackle the test sequencing question, paper 3 titled “Temporal Algebraic Query of Test Sequences” by Prasetya studies the question of test sequences using formalism based on algebraic relations and linear temporal logic. Paper 4 titled “Stateless Techniques for Generating Global and Local Test Oracles for Message-Passing Concurrent Programs” by Carver and Lei considers the state explosion problem of test sequences and proposes a stateless method to generate test oracles for concurrent programs. To address the test output verification problem, paper 5 titled “VISOR: A Fast Image Processing Pipeline with Scaling and Translation Invariance for Test Oracle Automation of Visual Output Systems” by Kıraç et al. focuses on the verification of visual output and introduces an automated test oracle that avoids false positives in image comparison caused by scaling and translation. To investigate software fault localization in the face of the oracle problem, paper 6 titled “Exploring the Usefulness of Unlabelled Test Cases in Software Fault Localization” by Zhang et al. develops an approach based on a core idea of test classification. We would like to thank the authors for their contributions, and the reviewers for their invaluable comments