1,720,985 research outputs found
Goal-Based Requirement Engineering for Fault Tolerant Security-Critical Systems
No full textLarge amount of security faults existing in software systems could be complex and hard to identify during the fault analysis. Therefore, it is not always possible to fully mitigate the internal or external security faults (vulnerabilities or threats) within the system. On the other hand, existence of faults in the system may eventually lead to a security failure. To avoid security failure of the target system it is required to make the system flexible and tolerant in the presence of security faults. This paper proposes a goal-based modeling approach to develop security requirements of Security-Critical Systems (SCSs) through explicitly factoring the faults into the requirement engineering process. Our approach establishes the Security Requirement Model (SRM) of the system based on its respective Security Fault Model (SFM). We incorporate fault tolerance into the SRM through considering the partial satisfaction of security goals. The proposed approach factors this partiality into the goals by using proper mitigation techniques during the refinement process. This approach eventually contributes to a fault tolerant model for security requirements of the target system ©2013 SERSC
Engineering Human Values in Software through Value Programming
No full textIgnoring human values in software development may disadvantage users by breaching their values and introducing biases in software. This can be mitigated by informing developers about the value implications of their choices and taking initiatives to account for human values in software. To this end, we propose the notion of Value Programming with three principles: (P1) annotating source code and related artifacts with respect to values; (P2) inspecting source code to detect conditions that lead to biases and value breaches in software, i.e., Value Smells; and (P3) making recommendations to mitigate biases and value breaches. To facilitate value programming, we propose a framework that allows for automated annotation of software code with respect to human values. The proposed framework lays a solid foundation for inspecting human values in code and making recommendations to overcome biases and value breaches in software
Factoring requirement dependencies in software requirement selection using graphs and integer programming
No full textSoftware requirement selection is to find a subset of requirements (so-called optimal set) that gives the highest customer value for a release of software while keeping the cost within the budget. Several industrial studies however, have demonstrated that requirements of software projects are intricately interdependent and these interdependencies impact the values of requirements. Furthermore, the strengths of dependency relations among requirements vary in the context of real-world projects. For instance, requirements can be strongly or weakly interdependent. Therefore, it is important to consider both the existence and the strengths of dependency relations during requirement selection. The existing selection models however, have ignored either requirement dependencies altogether or the strengths of those dependencies. This research proposes an Integer programming model for requirement selection which considers both the existence and strengths of requirement dependencies. We further contribute a graph-based dependency modeling technique for capturing requirement dependencies and the their corresponding strengths. Automated/semi-automated techniques will also be devised to identify requirement dependencies and the strengths of those dependencies
What Can Artificial Intelligence Do for Refugee Status Determination? A Proposal for Removing Subjective Fear
No full textThe drive for innovation, efficiency, and cost-effectiveness has seen governments increasingly turn to artificial intelligence (AI) to enhance their operations. The significant growth in the use of AI mechanisms in the areas of migration and border control makes the potential for its application to the process of refugee status determination (RSD), which is burdened by delay and heavy caseloads, a very real possibility. AI may have a role to play in supporting decision makers to assess the credibility of asylum seekers, as long as it is understood as a component of the humanitarian context. This article argues that AI will only benefit refugees if it does not replicate the problems of the current system. Credibility assessments, a central element of RSD, are flawed because the bipartite standard of a ‘well-founded fear of being persecuted’ involves consideration of a claimant’s subjective fearfulness and the objective validation of that fear. Subjective fear imposes an additional burden on the refugee, and the ‘objective’ language of credibility indicators does not prevent the challenges decision makers face in assessing the credibility of other humans when external, but largely unseen, factors such as memory, trauma, and bias, are present.
Viewing the use of AI in RSD as part of the digital transformation of the refugee regime forces us to consider how it may affect decision-making efficiencies, as well as its impact(s) on refugees. Assessments of harm and benefit cannot be disentangled from the challenges AI is being tasked to address. Through an analysis of algorithmic decision making, predictive analysis, biometrics, automated credibility assessments, and digital forensics, this article reveals the risks and opportunities involved in the application of AI in RSD. On the one hand, AI’s potential to produce greater standardization, to mine and parse large amounts of data, and to address bias, holds significant possibility for increased consistency, improved fact-finding, and corroboration. On the other hand, machines may end up replicating and manifesting the unconscious biases and assumptions of their human developers, and AI has a limited ability to read emotions and process impacts on memory. The prospective nature of a well-founded fear is counter-intuitive if algorithms learn based on training data that is historical, and an increased ability to corroborate facts may shift the burden of proof to the asylum seeker. Breaches of data protection regulations and human rights loom large. The potential application of AI to RSD reveals flaws in refugee credibility assessments that stem from the need to assess subjective fear. If the use of AI in RSD is to become an effective and ethical form of humanitarian tech, the ‘well-founded fear of being persecuted’ standard should be based on objective risk only
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Dependency-aware software requirements selection using fuzzy graphs and integer programming
No full textOne of the critical activities in software development is Requirements Selection, which is to find an optimal subset of the software requirements (features) with the highest value for a given budget. The values of the requirements, however, may depend on one another. Such Value Dependencies have not been considered by the existing requirements selection methods, leading to user dissatisfaction and loss of value and reputation in software projects. To mitigate this, we propose Dependency-Aware Requirements Selection (DARS) as an expert system, which explicitly accounts for value dependencies in software projects. At the heart of DARS is an Integer Linear Programming (ILP) model that reduces the risk of value loss by considering value dependencies among the requirements. These value dependencies are identified from the preferences of the users for the requirements. The validly of DARS is verified by studying a real-world software project as well as carrying out simulations. Our results demonstrate a significant reduction in value loss when DARS is employed. Also, the ILP model of DARS proved scalable to large requirement sets (experimented for up to 3000). The results of our study can be extrapolated to a wide range of expert systems that concern selecting value-dependent items
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Visibility Requirements Engineering for Commercial Websites
No full textVisibility in search engines is a competitive advantage of commercial websites. In this context, Search Engine Optimization (SEO) techniques are devised to enhance the ranking of websites in search engine results. The existing approaches toward SEO are primarily modifying the content or the structure of websites during the post-development activities. These modifications can introduce new defects to the websites. To tackle this problem, we have proposed caring for visibility in the requirements of commercial websites. We further contribute a goal-based framework for modeling and description of visibility in requirement engineering phase. The framework lays a foundation for automated analysis of visibility in commercial websites. © 2014 SERSC
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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