Automated Software Testing (AST) using Model Checking is in this article epistemologically analysed in order to argue in favour of a model-based reasoning paradigm in computer science. Preliminarily, it is shown how both deductive and inductive reasoning are insufficient to determine whether a given piece of software is correct with respect to specified behavioural properties. Models algorithmically checked in Model Checking to select executions to be observed in Software Testing are acknowledged as analogical models (...) which establish isomorphic relations with the target system’s data set. Analogical models developed in AST are presented as abductive models providing hypothetical explanations to observed executions. The model assumption—algorithmic check—software testing process is understood as the abduction—deduction—induction process defining the selective abduction and turned to isolate a set of model-based hypotheses concerning the target system behaviours. A manipulative abduction process is finally recognized in the practice of adapting, abstracting and refining models that do not provide successful predictions. (shrink)

. Software testing is a very important phase in the development of software. Testing includes the generation of test cases which, if done manually, is time consuming. To automate this process and generate optimal test cases, several meta-heuristic techniques have been developed. These approaches include genetic algorithm, cuckoo search, tabu search, intelligent water drop, etc. This paper presents an effective approach for test data generation using the cuckoo search and tabu search algorithms. It combines the cuckoo (...) algorithm's strength of converging to the solution in minimal time along with the tabu mechanism of backtracking from local optima by Lévy flight. The experimental results show that the algorithm is effective in generating test cases optimally and its performance is better than various earlier proposed approaches. (shrink)

Software testing is a complex and critical process for achieving product quality. Its importance has been increasing and well recognized, and there is a growing concern in improving the accomplishm...

This essay describes trends in the organization of work that have laid the groundwork for the adoption of interactive AI-driven instruction tools, and the technological innovations that will make intelligent tutoring systems truly competitive with human teachers. Since the origin of occupational specialization, the collection and transmission of knowledge have been tied to individual careers and job roles, specifically doctors, teachers, clergy, and lawyers, the paradigmatic knowledge professionals. But these roles have also been tied to texts and organizations that can (...) disseminate knowledge independently from professionals. Professionals and organizations turn knowledge into texts and tools that enable lay people to access knowledge without the intermediation of professionals or organizations. In the 21st century, one emerging tool for transmitting knowledge is the intelligent tutoring system. This paper examines how technological, epistemic, and economic trends in education are supporting the routinization, proletarianization, and automation of the occupation of teaching, leading to the increasing substitution of intelligent tutoring systems for human instruction. Some trends, such as standardized curricula and testing, both restrict teachers’ professional autonomy and facilitate the creation of pedagogical tools. Other trends reduce teachers’ ability to resist automation. The growth of adjunct teaching and paraprofessional roles in higher education allows organizations to take over and rationalize parts of the traditional teacher role. Faculty evaluations and learning outcomes assessment weaken professional claims to be the sole arbiters of instructional quality and student learning. The widespread use of intelligent tutoring systems also depends on the sophistication of software capable of performing the social-emotional and cognitive roles that educators perform. Eventually, pedagogical software will be able to interactively individualize curricula to the needs and interests of every learner, more cheaply, quickly, and accurately than any human teacher. Assessment of learning will be continuous, and certification of learning will be for specific skills instead of broad area competencies. Intelligent tutoring systems will help transition education from its medieval and industrial-era model to more accessible and flexible continuing education for employment and life enrichment. (shrink)

This paper takes part in the methodological debate concerning the nature and the justification of hypotheses about computational systems in software engineering by providing an epistemological analysis of Software Testing, the practice of observing the programs’ executions to examine whether they fulfil software requirements. Property specifications articulating such requirements are shown to involve falsifiable hypotheses about software systems that are evaluated by means of tests which are likely to falsify those hypotheses. Software Reliability metrics, (...) used to measure the growth of probability that given failures will occur at specified times as new executions are observed, is shown to involve a Bayesian confirmation of falsifiable hypotheses on programs. Coverage criteria, used to select those input values with which the system under test is to be launched, are understood as theory-laden principles guiding software tests, here compared to scientific experiments. Redundant computations, fault seeding models and formal methods used in software engineering to evaluate test results are taken to be instantiations of some epistemological strategies used in scientific experiments to distinguish between valid and non-valid experimental outcomes. The final part of the paper explores the problem, advanced in the context of the philosophy of technology, of defining the epistemological status of software engineering by conceiving it as a scientifically attested technology. (shrink)

Emotional facial expressions can inform researchers about an individual's emotional state. Recent technological advances open up new avenues to automatic Facial Expression Recognition (FER). Based on machine learning, such technology can tremendously increase the amount of processed data. FER is now easily accessible and has been validated for the classification of standardized prototypical facial expressions. However, applicability to more naturalistic facial expressions still remains uncertain. Hence, we test and compare performance of three different FER systems (Azure Face API, Microsoft; Face++, (...) Megvii Technology; FaceReader, Noldus Information Technology) with human emotion recognition (A) for standardized posed facial expressions (from prototypical inventories) and (B) for non-standardized acted facial expressions (extracted from emotional movie scenes). For the standardized images, all three systems classify basic emotions accurately (FaceReader is most accurate) and they are mostly on par with human raters. For the non-standardized stimuli, performance drops remarkably for all three systems, but Azure still performs similarly to humans. In addition, all systems and humans alike tend to misclassify some of the non-standardized emotional facial expressions as neutral. In sum, emotion recognition by automated facial expression recognition can be an attractive alternative to human emotion recognition for standardized and non-standardized emotional facial expressions. However, we also found limitations in accuracy for specific facial expressions; clearly there is need for thorough empirical evaluation to guide future developments in computer vision of emotional facial expressions. (shrink)

Computer multistage adaptive test combines the advantages of paper and pencil-based test and computer-adaptive test. As CAT, MST is adaptive based on modules; as P&P, MST can meet the need of test developers to manage test forms and keep test forms parallel. Cognitive diagnosis can accurately measure students’ knowledge states and provide diagnostic information, which is conducive to student’s self-learning and teacher’s targeted teaching. Although MST and CD have a lot of advantages, many factors prevent MST from applying to CD. (...) In this study, we first attempt to employ automated test assembly to achieve the objectives of MST in the application of CD via heuristic algorithms. The mean correct response probability of all KSs for each item is used to describe the item difficulty of CD. The attribute reliability in CD is defined as the test quantitative target. A simulation study with the G-DINA model was carried out to investigate the proposed CD-MST, and the results showed that the assembled panels of CD-MST satisfied the statistical and the non-statistical constraints. (shrink)

Fully automated vehicles (AVs) hold promise toward providing numerous societal benefits including reducing road fatalities. However, we are uncertain about how individuals’ perceptions will influence their ability to accept and adopt AVs. The 28-item Automated Vehicle User Perception Survey (AVUPS) is a visual analog scale that was previously constructed, with established face and content validity, to assess individuals’ perceptions of AVs. In this study, we examined construct validity, via exploratory factor analysis and subsequent Mokken scale analyses. Next, internal (...) consistency was assessed via Cronbach’s alpha (α) and 2-week test–retest reliability was assessed via Spearman’s rho (ρ) and intraclass correlation coefficient (ICC). The Mokken scale analyses resulted in a refined 20-item AVUPS and three Mokken subscales assessing specific domains of adults’ perceptions of AVs: (a)Intention to use; (b)perceived barriers; and (c)well-being. The Mokken scale analysis showed that all item-coefficients of homogeneity (H) exceeded 0.3, indicating that the items reflect a single latent variable. The AVUPS indicated a strong Mokken scale (Hscale= 0.51) with excellent internal consistency (α = 0.95) and test–retest reliability (ρ = 0.76, ICC = 0.95). Similarly, the three Mokken subscales ranged from moderate to strong (rangeHscale= 0.47–0.66) and had excellent internal consistency (range α = 0.84–0.94) and test–retest reliability (range ICC = 0.84–0.93). The AVUPS and three Mokken subscales of AV acceptance were validated in a moderate sample size (N= 312) of adults living in the United States. Two-week test–retest reliability was established using a subset of Amazon Mechanical Turk participants (N= 84). The AVUPS, or any combination of the three subscales, can be used to validly and reliably assess adults’ perceptions before and after being exposed to AVs. The AVUPS can be used to quantify adults’ acceptance of fully AVs. (shrink)

Healthcare data warehousing test automation is becoming a success through the help of AI-based technology that results in accuracy, efficiency, and data integrity on the automated test. The one central to personalized patient data that forms the core of traditional data warehousing solutions frequently faces problems of complexity and dissatisfaction. Deep learning with test automation solutions makes data ingestion, processing, and testing conversant through machine learning algorithms [1]. These systems encompass separate acts such as testing for data (...) integration, testing the quality of data as well as performance testing removing the factors of time and human error. In healthcare organizations, this approach delivers the message of enhancing quality, compliance and organizational efficiency in value-based care and precision medicine initiatives. As such, artificial intelligence tools can be used to address the essential issues regarding data warehousing, and this can in turn enhance decision-making, and thus, enhance the health of patient and the overall population. (shrink)

Fiction is an important tool in an artist/designer/developer’s vocabulary, but its usage is polyvalent. Speculative research in this article introduces the ‘rudiment’ to embrace the undeveloped and the improvisory phases of research practice. Fiction is used to reflect on the ways practicing designers and developers might already engage in misanthropic thinking – involving automated technologies. Tracing the misanthropic agencies in relation to automated technologies contributes to expanding the ways designers and developers reflect on the technical potential of their (...) designs, with whom they are designing (and for) and the way they understand their reflexive self. Bringing together Colson Whitehead’s novel The Intuitionist (1999) and its account of an elevator crash, their design and maintenance, with a narrative account of software agents enables an investigation into the promises made through a design-for-the-prevention-of-failure imperative. These examples highlight the relation between physical and non-physical failures such as failures to connect or to create intimacy. Those who contribute to designing in this article get caught up in configuring misanthropic agencies involving themselves, the designed artefact and the spaces they both inhabit be that an elevator in a housing block, or a sexbot in an online chat room. I will argue that the misanthropic agencies of automated technologies can have a confining impact on our emergent modes of design. Automated software operating in virtual spaces are confining in as much as they attempt to connect things to exploit the de-personalized aspects of automated, misanthropic agency. (shrink)

Conceptual models are descriptions of our ideas about a problem, used to shape the implementation of a solution to it. Everyone who builds complex information systems uses such models - be they requirements analysts, knowledge modellers or software designers - but understanding of the pragmatics of model design tends to be informal and parochial. Lightweight uses of logic can add precision without destroying the intuitions we use to interpret our descriptions. Computing with logic allows us to make use of (...) this precision in providing automated support tools. Modern information scientists need to know what these methods are for and may need to build their own. This book gives you a place to begin. Where do you start when building models in a precise language like logic? One way is by following standard paradigms for design and adapting these to your needs. Some of these come from an analysis of existing informal notations. Others are from within logic itself. We take you through a sample of these, from more commonplace styles of formal modelling to non-standard methods such as techniques editing and argumentation. Each of these provides a window onto broader areas of applied logic and gives you a basis for adapting the method to your own needs. (shrink)

The possible relationship between widespread unauthorized copying of microcomputer software (also known as software piracy) and level of moral judgment is examined through analysis of over 350 survey questionnaires that included the Defining Issues Test as a measure of moral development. It is hypothesized that the higher one''s level of moral judgment, the less likely that one will approve of or engage in unauthorized copying. Analysis of the data indicate a high level of tolerance toward unauthorized copying and (...) limited support for the hypothesis. The most plausible explanation for these findings is that software copying is perceived as an issue of low moral intensity. This study calls into question the software industry''s strategy of concentrating exclusively on institutional compliance with copyright rules, rather than working to raise the perceived moral intensity about software piracy at the individual level. As long as the issue remains low in moral intensity, the industry cannot expect significant shifts in copying behaviors. Individuals must become more aware of and concerned about the nature and magnitude of harm to society and to the rightful copyright owners from unauthorized copying before their attitudes and behaviors come to reflect higher levels of moral judgment. (shrink)

Connected devices, such as smartphones and tablets, are exposed to a large variety of attacks. Their protection is often challenged by their resource constraints in terms of CPU, memory and energy. Security chains, composed of security functions such as firewalls, intrusion detection systems and data leakage prevention mechanisms, offer new perspectives to protect these devices using software-defined networking and network function virtualization. However, the complexity and dynamics of these chains require new automation techniques to orchestrate them. This chapter describes (...) an automated orchestration methodology for security chains in order to secure connected devices and their applications. This methodology exploits process learning to establish behavioral models and infer security constraints represented as logical predicates. It then generates and merges a set of chains of security functions on the basis of these predicates. These chains are finally compiled into low-level configuration rules and deployed into the network, optimizing for the underlying topology. The benefits and limits of such a methodology combining machine learning and verification techniques are evaluated by a set of experimental results. (shrink)

Online privacy policies or terms and conditions ideally provide users with information about how their personal data are being used. The reality is that very few users read them: they are long, often hard to understand, and ubiquitous. The average internet user cannot realistically read and understand all aspects that apply to them and thus give informed consent to the companies who use their personal data. In this article, we provide a basic overview of a solution to the problem. We (...) suggest that software could allow users to delegate the consent process and consent could thus be automated. The article investigates the practical feasibility of this idea. After suggesting that it is feasible, we develop some normative issues that we believe should be addressed before automated consent is implemented. (shrink)

The basis of science is the hypothetico-deductive method and the recording of experiments in sufficient detail to enable reproducibility. We report the development of Robot Scientist "Adam," which advances the automation of both. Adam has autonomously generated functional genomics hypotheses about the yeast Saccharomyces cerevisiae and experimentally tested these hypotheses by using laboratory automation. We have confirmed Adam's conclusions through manual experiments. To describe Adam's research, we have developed an ontology and logical language. The resulting formalization involves over 10,000 different (...) research units in a nested treelike structure, 10 levels deep, that relates the 6.6 million biomass measurements to their logical description. This formalization describes how a machine contributed to scientific knowledge. (shrink)

Purpose This research aims to develop a conceptual framework that explores the influence of open-source software (OSS) on the sustainability of library services within the context of academic libraries in Bangladesh. Design/methodology/approach The study uses a comprehensive research methodology that includes literature review and analysis to construct a robust conceptual framework. This study investigates the various dimensions of OSS adoption and its impact on library service sustainability. Findings The research findings reveal the critical factors and mechanisms through which OSS (...) can positively affect the sustainability of library services. This study identifies key drivers and challenges associated with the adoption of open-source solutions in the context of Bangladesh academic libraries. Practical implications The framework developed in this research offers practical insights for academic libraries in Bangladesh seeking to adopt OSS solutions. This study guides how to leverage these technologies to enhance the sustainability of library services in a cost-effective and efficient manner. Originality/value This study contributes to the academic literature by presenting a novel conceptual framework tailored to the unique context of Bangladesh academic libraries. This study adds value by addressing the specific challenges and opportunities related to OSS adoption and its implications for library service sustainability in this region. (shrink)

Software piracy, the illegal and unauthorized duplication, sale, or distribution of software, is a widespread and costly phenomenon. According to Business Software Alliance, over 41% of the PC software packages installed worldwide were unauthorized copies. Software piracy behavior has been investigated for more than 30 years. However, after a review of the relevant literature, there appears to be two voids in this literature: a lack of studies in non-Western countries and a scarcity of process studies. (...) This study contributes to literature by developing a software piracy model to better understand the decision-making process that underlies this unethical behavior. The model was tested using data collected from a sample of 323 undergraduate business students. Consistent with the Theory of Reasoned Action, attitudes toward software piracy and subjective norms were significant predictors of intention to pirate software. Also, the results suggested that ethical ideology, public self-consciousness, and low self-control moderated the effect of these variables on intention to pirate software. The results have important practical implications for the software industry and governments hoping to curtail software piracy. Limitations of the study and recommendations for future studies are discussed as well. (shrink)

As software piracy continues to be a threat to the growth of national and global economies, understanding why people continue to use pirated software and learning how to discourage the use of pirated software are urgent and important issues. In addition to applying the theory of planned behavior (TPB) perspective to capture behavioral intention to use pirated software, this paper considers perceived risk as a salient belief influencing attitude and intention toward using pirated software. Four (...) perceived risk components related to the use of pirated software (performance, social, prosecution and psychological risks) have been identified, measured and tested. Data were collected through an online survey of 305 participants. The results indicate that perceived prosecution risk has an impact on intention to use pirated software, and perceived psychological risk is a strong predictor of attitude toward using pirated software. In addition, attitude and perceived behavior control contribute significantly to the intended use of pirated software. However, the proposed direct relationship between subjective norm and intention to use pirated software is not supported. Implications for research and practice are discussed. (shrink)

Organisations increasingly use automated decision-making systems (ADMS) to inform decisions that affect humans and their environment. While the use of ADMS can improve the accuracy and efficiency of decision-making processes, it is also coupled with ethical challenges. Unfortunately, the governance mechanisms currently used to oversee human decision-making often fail when applied to ADMS. In previous work, we proposed that ethics-based auditing (EBA)—that is, a structured process by which ADMS are assessed for consistency with relevant principles or norms—can (a) help (...) organisations verify claims about their ADMS and (b) provide decision-subjects with justifications for the outputs produced by ADMS. In this article, we outline the conditions under which EBA procedures can be feasible and effective in practice. First, we argue that EBA is best understood as a ‘soft’ yet ‘formal’ governance mechanism. This implies that the main responsibility of auditors should be to spark ethical deliberation at key intervention points throughout the software development process and ensure that there is sufficient documentation to respond to potential inquiries. Second, we frame AMDS as parts of larger sociotechnical systems to demonstrate that to be feasible and effective, EBA procedures must link to intervention points that span all levels of organisational governance and all phases of the software lifecycle. The main function of EBA should, therefore, be to inform, formalise, assess, and interlink existing governance structures. Finally, we discuss the policy implications of our findings. To support the emergence of feasible and effective EBA procedures, policymakers and regulators could provide standardised reporting formats, facilitate knowledge exchange, provide guidance on how to resolve normative tensions, and create an independent body to oversee EBA of ADMS. (shrink)

What role can technology play in cultivating a disciplinary stance — raising questions, planning investigations, interpreting data and constructing explanations in a way that reflects disciplinary values and principles? How can overt and tacit expert scientific knowledge be captured, represented and used to design software that enables novices to assume a disciplinary stance in their investigations? We present The Galapagos Finches software designed to foster a biological and evolutionary stance. Our approach, Discipline-Specific Strategic Support , translates the main (...) variable types, comparison types and relationships in a discipline into manipulable objects in the interface. Pre/post-tests show how DSSS helps achieve a balance between content and process goals. A contrastive-case microanalysis of high, medium and low-achieving students' inquiry shows progress toward a disciplinary stance. Our study shows how software representations carry multiple levels of meaning, and that the efficacy of learning technologies hinges on reflection at both the navigation and disciplinary-signification levels. (shrink)

Modern software is infested with flaws having information security aspects. Pervasive computing has made us and our society vulnerable. However, software developers do not fully comprehend what is at stake when faulty software is produced and flaws causing security vulnerabilites are discovered. To address this problem, the main actors involved with software vulnerability processes and the relevant roles inside these groups are identified. This categorisation is illustrated through a fictional case study, which is scrutinised in the (...) light of ethical codes of professional software engineers and common principles of responsibility attribution. The focus of our analysis is on the acute handling of discovered vulnerabilities in software, including reporting, correcting and disclosing these vulnerabilities. We recognise a need for guidelines and mechanisms to facilitate further improvement in resolving processes leading to and in handling software vulnerabilities. In the spirit of disclosive ethics we call for further studies of the complex issues involved. (shrink)

Automated classification of legal documents has been the subject of extensive research in recent years. However, this is still a challenging task for long documents, since it is difficult for a model to identify the most relevant information for classification. In this paper, we propose a two-stage supervised learning approach for the classification of petitions, a type of legal document that requests a court order. The proposed approach is based on a word-level encoder–decoder Seq2Seq deep neural network, such as (...) a Bidirectional Long Short-Term Memory (BiLSTM) or a Bidirectional Encoder Representations from Transformers (BERT) model, and a document-level Support Vector Machine classifier. To address the challenges posed by the lengthy legal documents, the approach introduces a human-in-the-loop approach, whose task is to localize and tag relevant segments of text in the word-level training part, which dramatically reduces the dimension of the document classifier input vector. We performed experiments to validate our approach using a real-world dataset comprised of 270 intermediate petitions, which were carefully annotated by specialists from the 15th civil unit of the State of Alagoas, Brazil. Our results revealed that both BiLSTM and BERT-Convolutional Neural Networks variants achieved an accuracy of up to 95.49%, and also outperformed baseline classifiers based on the Term Frequency–Inverse Document Frequency test vectorizer. The proposed approach is currently being utilized to automate the aforementioned justice unit, thereby increasing its efficiency in handling repetitive tasks. (shrink)

Most experimental studies of facial expression processing have used static stimuli (photographs), yet facial expressions in daily life are generally dynamic. In its original photographic format, the Karolinska Directed Emotional Faces (KDEF) has been frequently utilized. In the current study, we validate a dynamic version of this database, the KDEF-dyn. To this end, we applied animation between neutral and emotional expressions (happy, sad, angry, fearful, disgusted, and surprised; 1,033-ms unfolding) to 40 KDEF models, with morphing software. Ninety-six human observers (...) categorized the expressions of the resulting 240 video-clip stimuli, and automated face analysis assessed the evidence for 6 expressions and 20 facial action units (AUs) at 31 intensities. Low-level image properties (luminance, signal-to-noise ratio, etc.) and other purely perceptual factors (e.g., size, unfolding speed) were controlled. Human recognition performance (accuracy, efficiency, and confusions) patterns were consistent with prior research using static and other dynamic expressions. Automated assessment of expressions and AUs was sensitive to intensity manipulations. Significant correlations emerged between human observers’ categorization and automated classification. The KDEF-dyn database aims to provide a balance between experimental control and ecological validity for research on emotional facial expression processing. The stimuli and the validation data are available to the scientific community. (shrink)

As software developers design artificial agents , they often have to wrestle with complex issues, issues that have philosophical and ethical importance. This paper addresses two key questions at the intersection of philosophy and technology: What is deception? And when is it permissible for the developer of a computer artifact to be deceptive in the artifact’s development? While exploring these questions from the perspective of a software developer, we examine the relationship of deception and trust. Are developers using (...) deception to gain our trust? Is trust generated through technological “enchantment” warranted? Next, we investigate more complex questions of how deception that involves AAs differs from deception that only involves humans. Finally, we analyze the role and responsibility of developers in trust situations that involve both humans and AAs. (shrink)

The article explores the problem of preferable technological changes in the context of work. To this end, it addresses the ‘why’ (motives and values) and the ‘how’ (organizational forms) of automation from a normative perspective. Concerning the ‘why,’ automation processes are currently mostly driven by values of economic efficiency. Yet, since automation processes are part of the basic structure of society, as is the division of labor, considerations of justice apply to them. As for the ‘how,’ the article suggests ‘fair (...) hybrid cooperation’ as an alternative ideal to guide automation priorities. It is achieved when the division of labor between humans and machines does not hinder, and preferably enables, workers’ experience of certain primary qualities in their work activity. By analogy with Rawls’ primary goods, these are qualities that it is necessary for every worker to experience in order to pursue their life plans: security, self-direction, self-development, dignity, and recognition. According to this criterion, the tasks to automate first are those hindering these contributive primary qualities. This provides us with a normative vocabulary and a standard to orient automation decisions but also to assess existing organizational forms and envisage alternative cooperative imaginaries. To illustrate how the ideal may play out in the real world, the article concludes with a ‘fair hybrid cooperation test’ and a nurse bots case for meaningful work. (shrink)

The use of advanced AI and data-driven automation in the public sector poses several organisational, practical, and ethical challenges. One that is easy to underestimate is automation bias, which, in turn, has underappreciated legal consequences. Automation bias is an attitude in which the operator of an autonomous system will defer to its outputs to the point where the operator overlooks or ignores evidence that the system is failing. The legal problem arises when statutory office-holders (or their employees) either fetter their (...) discretion to in-house algorithms or improperly delegate their discretion to third-party software developers—something automation bias may facilitate. A synthesis of previous research suggests an easy way to mitigate the risks of automation bias and its potential legal ramifications is for those responsible for procurement decisions to adhere to a simple checklist that ensures that the pitfalls of automation are avoided as much as possible. (shrink)

Paper-based privacy policies fail to resolve the new changes posed by electronic healthcare. Protecting patient privacy through electronic systems has become a serious concern and is the subject of several recent studies. The shift towards an electronic privacy policy introduces new ethical challenges that cannot be solved merely by technical measures. Structured Patient Privacy Policy (S3P) is a software tool assuming an automated electronic privacy policy in an electronic healthcare setting. It is designed to simulate different access levels (...) and rights of various professionals involved in healthcare in order to assess the emerging ethical problems. The authors discuss ethical issues concerning electronic patient privacy policies that have become apparent during the development and application of S3P. (shrink)

Accompanying the explosive growth of information technology is the increasing frequency of antisocial and criminal behavior on the Internet. Online software piracy is one such behavior, and this study approaches the phenomenon through the theoretical framework of neutralization theory. The suitability and applicability of nine techniques of neutralization in determining the act is tested via logistic regression analyses on cross-sectional data collected from a sample of university students in the United States. Generally speaking, neutralization was found to be weakly (...) related to experience with online software piracy; other elements which appear more salient are suggested and discussed in conclusion. (shrink)

A brain emulation would be a one‐to‐one simulation where every causal process in the brain is represented, behaving in the same way as the original. Opponents of animal testing often argue that much of it is unnecessary and could be replaced with simulations. Personal identity is going to be a major issue with brain emulations, both because of the transition from an original unproblematic single human identity to successor identity/identities that might or might not be the same, and because (...) software minds can potentially have multiple realizability. The process might produce distressed minds that have rights yet have an existence not worth living, or that lack the capacity to form or express their wishes. Emulations will experience and behave on a timescale set by the speed of their software. Brain emulations would not be self‐contained, and their survival would depend upon hardware over which they might not have any control. (shrink)

This book constitutes the proceedings of the 17th International Conference, TAP 2023, as part of STAF 2023, a federation of conferences on Software Technologies, Applications and Foundations, which includes two more conferences besides TAP: ICGT (International Conference on Graph Transformations), and ECMFA (European Conference on Modelling Foundations and Applications) in Leicester, UK, in July 2023. The 8 full papers together with 2 short papers included in this volume were carefully reviewed and selected from 14 submissions. They were organized in (...) topical sections on Low-level Code Verification, Formal Models, Model-based test generation, and Abstraction and Refinement. (shrink)

As multinational firms explore new and promising national markets two of the most crucial elements in the strategic decision regarding market-entry are the level of corruption and existing trade barriers. One form of corruption that is crucially important to firms is the theft of intellectual property. In particular, software piracy has become a hotly debated topic due to the deep costs and vast levels of piracy around the world. The purpose of this paper is to assess how laissez-faire trade (...) policies and corruption affect national software piracy rates. Using invisible hand theory, as well as literature from the fields of international strategy and ethics, formal research hypotheses are posited and tested. Results suggest that corruption mediates the relationship between economic freedom and software piracy. Implications for multinational managers and researchers are also addressed. (shrink)

A “post-work world” can mean a couple of things. First, it can mean a world where we attach less importance to work, restructure work so that tasks and authority are distributed more equitably, and otherwise decenter and reform the world of work. Second, it can mean a world where people are no longer working because robots, artificial intelligence, and other forms of automation have replaced humans and there are no longer enough jobs for everyone. This paper is about the second (...) kind of world, and how to support the workers it leaves behind. -/- Automation has always eliminated jobs, but in the past new jobs have appeared to replace them. This may be changing. Thanks to recent advances in automation, machines and software can now do an increasingly large percentage of the tasks that humans do. “Technological unemployment” is what happens when automation can do so many different tasks that new jobs do not appear in sufficient numbers to employ everyone (Keynes 1932). In short, automation may soon leave a very large part of the potential workforce permanently unemployed, leading to a social, political, economic, and humanitarian crisis. For ease of reference, I refer to the technologically unemployed as being displaced from the economy. -/- The displaced need incomes. One obvious source of funds is the money saved through technological unemployment. On the scale of an entire economy, technological unemployment increases the labor savings from automation, for in addition to the usual labor savings from automation, there is less of a need to pay new workers, for there are fewer new jobs. I call this money the displacement gain. This is money that becomes available precisely because technological unemployment has occurred. It is important to understand that the displacement gain is not the same thing as the profit that results from gains in productivity. Automation does not necessarily produce displacement but it does produce gains in productivity, and the profits from gains in productivity occur even when no one is displaced. A productivity gain does not become a displacement gain until technological unemployment occurs. -/- The core of this paper is a set of arguments that the displacement gain is not the private property of businesses or those who have ownership interests in businesses (I refer to both groups as “capitalists”), nor is it the private property of those lucky enough to still have jobs. For these and additional reasons, the displacement gain is collective property in which every person has an equal interest. Moreover, it is a kind of collective property that has been largely overlooked. (Better-known forms of collective property include the natural world and “social capital.” ) As far back as Thomas Paine (1796), many thinkers have argued that, because we all have equal interests in collective property, it should be distributed to everyone, working or not, rich or poor, as equal and unconditional basic incomes. The displacement gain is a new kind of collective property which can fund basic incomes, and those incomes can support the displaced. That’s how to pay for a post-work world. -/- However, I will argue, in order to distribute those funds equally we must pay unequal basic incomes, for those who are technologically unemployed bear a larger share of the burden involved in creating that collective property, and therefore deserve larger basic incomes to offset their larger burdens. My discussion of this leads to a possible solution to a problem that bedevils basic income proposals: how to prevent businesses from, in effect, appropriating basic incomes from their employees by simply paying them less, using basic incomes as a payroll subsidy . (shrink)

According to the early futurist Julian Huxley, human life as we know it is ‘a wretched makeshift, rooted in ignorance’. With modern science, however, ‘the present limitations and miserable frustrations of our existence could be in large measure surmounted’ and human life could be ‘transcended by a state of existence based on the illumination of knowledge’ (1957b, p. 16).

Automated decision making for sentencing is the use of a software algorithm to analyse a convicted offender’s case and deliver a sentence. This chapter reviews the moral arguments for and against employing automated decision making for sentencing and finds that its use is in principle morally permissible. Specifically, it argues that well-designed automated decision making for sentencing will better approximate the just sentence than human sentencers. Moreover, it dismisses common concerns about transparency, privacy and bias as (...) unpersuasive or inapplicable. The chapter also notes that moral disagreement about theories of just sentencing are plausibly resolved by applying the principle of maximising expected moral choiceworthiness, and that automated decision making is better suited to the resulting ensemble model. Finally, the chapter considers the challenge posed by penal populism. The dispiriting conclusion is that although it is in theory morally desirable to use automated decision-making for criminal sentencing, it may well be the case that we ought not to try. (shrink)

There are many internationally developed text-matching software systems that help successfully identify potentially plagiarized content in English texts using both their internal databases and web resources. However, many other languages are not so widely spread but they are used daily to communicate, conduct research and acquire education. Each language has its peculiarities, so, in the context of finding content similarities, it is necessary to determine what systems are more suitable for a document set written in a specific language. The (...) research focuses on testing the existent text-matching software systems on a set of documents prepared in the Latvian language. The corpus includes documents containing verbatim plagiarism, paraphrasing, translation plagiarism and original text to test both false positive and false negative cases. In total, 16 different text-matching software systems are compared on the plagiarism coverage using the prepared document corpus. The research presented is a part of an international initiative “Testing of Support Tools for Plagiarism Detection ” established under the European Network for Academic Integrity. (shrink)

This commentary on John Symons’ and Jack Horner’s paper, besides sharing its main argument, challenges the authors’ statement that there is no effective method to evaluate software-intensive systems as a distinguishing feature of software intensive science. It is underlined here how analogous methodological limitations characterise the evaluations of empirical systems in non-software intensive sciences. The authors’ claim that formal methods establish the correctness of computational models rather than of the represented programme is here compared with the empirical (...) adequacy problem typifying the model-based reasoning approach in physics, and the remark that testing all the paths of a software-intensive system is unfeasible is related to the enumerative induction problem in the justification of empirical law-like hypotheses in non-software intensive sciences. (shrink)

The authors present their experience and practices of introducing cloud services, as a means to simplify the adoption of ICT in education, using Free/Open Source Software. The solution creates a hybrid cloud infrastructure, in order to provide a pre-installed virtual machine, acting as a server inside the school, providing desktop environment based on the Software as a Service cloud model, where legacy PCs act as stateless devices. Classroom management is accomplished using the application “Epoptes.” To minimize administration tasks, (...) educational software is provided accordingly, either on-line or through repositories to automate software installation. The advantages of the hybrid cloud implementation, include services that are not completely dependent on broadband connections’ state, minimal cost, reusability of obsolete equipment, ease of administration, centralized management, patches and educational software provisioning and, above all, facilitation of the educational procedure. (shrink)

The automated identification of national implementations of European directives by text similarity techniques has shown promising preliminary results. Previous works have proposed and utilized unsupervised lexical and semantic similarity techniques based on vector space models, latent semantic analysis and topic models. However, these techniques were evaluated on a small multilingual corpus of directives and NIMs. In this paper, we utilize word and paragraph embedding models learned by shallow neural networks from a multilingual legal corpus of European directives and national (...) legislation to develop unsupervised semantic similarity systems to identify transpositions. We evaluate these models and compare their results with the previous unsupervised methods on a multilingual test corpus of 43 Directives and their corresponding NIMs. We also develop supervised machine learning models to identify transpositions and compare their performance with different feature sets. (shrink)

The distinction between the modeling of information and the modeling of data in the creation of automated systems has historically been important because the development tools available to programmers have been wedded to machine oriented data types and processes. However, advances in software engineering, particularly the move toward data abstraction in software design, allow activities reasonably described as information modeling to be performed in the software creation process. An examination of the evolution of programming languages and (...) development of general programming paradigms, including object-oriented design and implementation, suggests that while data modeling will necessarily continue to be a programmer's concern, more and more of the programming process itself is coming to be characterized by information modeling activities. (shrink)

Diffusion MRI is widely used to investigate neuronal and structural development of brain. dMRI data is often contaminated with various types of artifacts. Hence, artifact type identification in dMRI volumes is an essential pre-processing step prior to carrying out any further analysis. Manual artifact identification amongst a large pool of dMRI data is a highly labor-intensive task. Previous attempts at automating this process are often limited to a binary classification of the dMRI volumes or focus on detecting a single type (...) of artifact. In this work, we propose a deep learning-based automated multiclass artifact classifier for dMRI volumes. Our proposed framework operates in 2 steps. In the first step, the model predicts labels associated with 3D mutually exclusive collectively exhaustive sub-volumes or “slabs” extracted from whole dMRI volumes. In the second step, through a voting process, the model outputs the artifact class present in the whole volume under investigation. We used two different datasets for training and evaluating our model. Specifically, we utilized 2,494 poor-quality dMRI volumes from the Adolescent Brain Cognitive Development and 4,226 from the Healthy Brain Network dataset. Our results demonstrate accurate multiclass volume-level main artifact type prediction with 96.61 and 97.52% average accuracies on the ABCD and HBN test sets, respectively. Finally, in order to demonstrate the effectiveness of the proposed framework in dMRI pre-processing pipelines, we conducted a proof-of-concept dMRI analysis exploring the relationship between whole-brain fractional anisotropy and participant age, to test whether the use of our model improves the brain-age association. (shrink)

Certain characteristics make machine learning a powerful tool for processing large amounts of data, and also particularly unsuitable for explanatory purposes. There are worries that its increasing use in science may sideline the explanatory goals of research. We analyze the key characteristics of ML that might have implications for the future directions in scientific research: epistemic opacity and the ‘theory-agnostic’ modeling. These characteristics are further analyzed in a comparison of ML with the traditional statistical methods, in order to demonstrate what (...) it is specifically that makes ML methodology substantially unsuitable for reaching explanations. The analysis is given broader philosophical context by connecting it with the views on the role of prediction and explanation in science, their relationship, and the value of explanation. We proceed to show, first, that ML disrupts the relationship between prediction and explanation commonly understood as a functional relationship. Then we show that the value of explanation is not exhausted in purely predictive functions, but rather has a ubiquitously recognized value for both science and everyday life. We then invoke two hypothetical scenarios with different degrees of automatization of science, which help test our intuitions on the role of explanation in science. The main question we address is whether ML will reorient or otherwise impact our standard explanatory practice. We conclude with a prognosis that ML would diversify science into purely predictively oriented research based on ML-like techniques and, on the other hand, remaining faithful to anthropocentric research focused on the search for explanation. (shrink)

Software testing is a very important technique to design the faultless software and takes approximately 60% of resources for the software development. It is the process of executing a program or application to detect the software bugs. In software development life cycle, the testing phase takes around 60% of cost and time. Test case generation is a method to identify the test data and satisfy the software testing criteria. Test case generation (...) is a vital concept used in software testing, that can be derived from the user requirements specification. An automatic test case technique determines automatically where the test cases or test data generates utilizing search based optimization method. In this paper, Cuckoo Search and Bee Colony Algorithm (CSBCA) method is used for optimization of test cases and generation of path convergence within minimal execution time. The performance of the proposed CSBCA was compared with the performance of existing methods such as Particle Swarm Optimization (PSO), Cuckoo Search (CS), Bee Colony Algorithm (BCA), and Firefly Algorithm (FA). (shrink)

Automated neuropsychiatric batteries have been used in research and clinical practice, including for chronic diseases, such as Systemic Lupus Erythematosus. The Pediatric Automated Neuropsychological Assessment Metrics battery, originally developed for use in American-English speaking individuals, allows tracking of cognitive functions. It can be applied to people over 9 years old. The aim of this study was to translate and present initial validation data from the Ped-ANAM into Brazilian-Portuguese. We translated the battery according to Beaton’s guidelines. Psychometric properties were (...) tested, internal consistency was analyzed by Cronbach’s alpha coefficient, test-retest reliability by the intraclass correlation coefficient. Further, we measured the test execution speed at both times as a temporal stability. Principal component analysis was used for structural validity. Evidence of construct validity was assessed through assessment of the relationships with the Wechsler Intelligence Scales. All participants prior to the start of study related activities signed an informed consent form approved by the local ethics committee. A sample of 230 individuals [mean of age: 23 years; 65% females] was included; a subset of 51 individuals [mean of age: 18 years, 59% female] completed the Ped-ANAM twice to assess test-retest reliability, and another subset of 54 individuals [mean of age: 20.4 years; 67% female] completed the Wechsler Intelligence Scales for Children and Adult for assessment of the Ped-ANAM’s construct validity. Our results suggest that the internal consistency of the Ped-ANAM and its subtest test-retest reliability were excellent. There was no clustering in the Principal Components Analysis, suggestive of non-grouping of the evaluated variables. Construct validity assessment to the Wechsler Scales showed expected ranges of low to strong correlations. We concluded that, based on the results of this study, a cross-culturally validated Brazilian-Portuguese version of the Ped-ANAM has been developed and it is a reliable tool for the screening cognitive function. (shrink)

Background Noninvasive prenatal testing (NIPT) designed to screen for fetal genetic conditions, is increasingly being implemented as a part of routine prenatal care screening in the United States (US). However, these advances in reproductive genetic technology necessitate empirical research on the ethical and social implications of NIPT among populations underrepresented in genetic research, particularly Black women with sickle cell disease (SCD).Methods Forty (N = 40) semi-structured interviews were conducted virtually with Black women in the US (19 participants with SCD; (...) 21 participants without SCD) from June 2021 to January 2022. We employed a qualitative approach to examine the study participants’ perceptions of the potential advancement of NIPT for screening SCD in the fetus. Data were analyzed using NVivo 12 qualitative software.Results The themes revealed the complexities involving the intersectional lived experiences of SCD, prenatal care, lack of synergy among health providers, and NIPT decision-making. The results further revealed that even when Black women have shared commonalities in their lived experiences while navigating SCD and motherhood, their perceptions of NIPT screening technologies are divergent.Conclusion Expanding the ethical discourse on the social implications of NIPT is critical to fully elucidate how Black women perceive NIPT’s utility, particularly as NIPT advances to screen for SCD in the fetus. Neglecting to include Black women with genetic conditions in empirical studies on NIPT may contribute to ongoing health inequities and limit and constrain reproductive choices among Black women with and without SCD. (shrink)

Various due process provisions designed for use by civil servants in administrative decision-making may become redundant when automated decision-making is taken into use in public administration. Problems with mechanisms of good government, responsibility and liability for automated decisions and the rule of law require attention of the law-maker in adapting legal provisions to this new form of decision-making. Although the general data protection regulation of the European Union is important in acknowledging automated decision-making, most of the legal (...) safeguards within administrative due process have to be provided for by the national law-maker. It is suggested that all countries have a need to review their rules of administrative due process with a view to bringing them up to date regarding the requirements of automated decision-making. In whichever way the legislation is framed, the key issues are that persons who develop the algorithm and the code as well as persons who run or deal with the software within public authorities are aware of the preventive safeguards of legality in the context of automated decision-making, not only of the reactive safeguards constituted by the complaint procedures, and that legal mechanisms exist under which these persons can be held accountable and liable for decisions produced by automated decision-making. It is also argued that only rule-based systems of automatized decision-making are compatible with the rule of law and that there is a general interest in preventing a development into a rule of algorithm. (shrink)