How to Do Things With Words

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5分で分かる!? 有名論文ナナメ読み：Jacob Devlin et al. : BERT : Pre-training of Deep Bidirectional Transformers for Language Understanding

The Theory of Incentives I: The Principal-Agent Model

Software engineering is concerned with the development and evolution of high-quality software systems in a systematic, controlled, and efficient manner. Software engineers are concerned with safety and reliability of the product as well as the cost and schedule of the development process. The lectures and the group projects will cover all aspects of the software life cycle, from development team management, problem specification and analysis, system design techniques, implementation and documentation practices, testing, to maintenance and evaluation of the final product.

Uml Distilled A Brief Guide To The Standard Object Modeling Language

We understand a socio-technical system (STS) as a cyber-physical system in which two or more autonomous parties interact via or about technical elements, including the parties’ resources and actions. As information technology begins to pervade every corner of human life, STSs are becoming ever more common, and the challenge of governing STSs is becoming increasingly important. We advocate a normative basis for governance, wherein norms represent the standards of correct behaviour that each party in an STS expects from others. A major benefit of focussing on norms is that they provide a socially realistic view of interaction among autonomous parties that abstracts low-level implementation details. Overlaid on norms is the notion of a sanction as a negative or positive reaction to potentially any violation of or compliance with an expectation. Although norms have been well studied as regards governance for STSs, sanctions have not. Our understanding and usage of norms is inadequate for the purposes of governance unless we incorporate a comprehensive representation of sanctions.We address the aforementioned gap by proposing (i) a sanction typology that reflects the relevant features of sanctions, and (ii) a conceptual sanctioning process model providing a functional structure for sanctioning in STS. We demonstrate our contributions via a motivating scenario from the domain of renewable energy trading.

Classifying sanctions and designing a conceptual sanctioning process model for socio-technical systems

A stakeholder's beliefs influence his or her goals. However, a stakeholder's beliefs may not be consistent with the goals of all stakeholders of a system being constructed. Such belief-goal inconsistencies could manifest themselves as conflicting goals of the system to be. We propose Arg-ACH, a novel approach for capturing inconsistencies between stakeholders' goals and beliefs, and resolving goal conflicts. Arg-ACH employs a hybrid of (1) the analysis of competing hypotheses (ACH), a structured analytic technique, for systematically eliciting stakeholders' goals and beliefs, and (2) rational argumentation for determining belief-goal inconsistencies to resolve conflicts. Arg-ACH treats conflicting goals as hypotheses that compete with each other and the winning hypothesis as a goal of the system to be. Arg-ACH systematically captures the trail of a requirements engineer's thought process in resolving conflicts. We evaluated Arg-ACH via a study in which 20 subjects applied Arg-ACH or ACH to resolve goal conflicts in a sociotechnical system concerning national security. We found that Arg-ACH is superior to ACH with respect to completeness and coverage of belief search; length of belief chaining; ease of use; explicitness of the assumptions made; and repeatability of conclusions across subjects. Not surprisingly, Arg-ACH required more time than ACH: although this is justified by improvements in quality, the gap could be reduced through better tooling.

/pdf/resolving-goal-conflicts-via-argumentation-based-analysis-of-10ssqdygdi.pdf

Resolving goal conflicts via argumentation-based analysis of competing hypotheses

Mono2Micro is an AI-based toolchain that provides recommendations for decomposing legacy web applications into microservice partitions. Mono2Micro consists of a set of tools that collect static and runtime information from a monolithic application and process the information using an AI-based technique to generate recommendations for partitioning the application classes. Each partition represents a candidate microservice or a grouping of classes with similar business functionalities. Mono2Micro takes a temporo-spatial clustering approach to compute meaningful and explainable partitions. It generates two types of partition recommendations. First, it computes business-logic-seams-based partitions that represent a desired encapsulation of business functionalities. However, such a recommendation may cut across data dependencies between classes, accommodating which could require significant application updates. To address this, Mono2Micro computes natural-seams-based partitions, which respect data dependencies. We describe the set of tools that comprise Mono2Micro and illustrate them using a well-known open-source JEE application.

Mono2Micro: an AI-based toolchain for evolving monolithic enterprise applications to a microservice architecture

Service selection, where some of the services are accessed indirectly as constituents of composite services, is difficult for the following reasons: (1) the interpretation of service qualities is subjective; (2) evidence must be combined from multiple sources; (3) service profiles change dynamically; and (4) constituent services may be only partially observable behind composite services. We propose an approach where we map service qualities to a common probabilistic trust metric. Whereas current trust approaches estimate the trustworthiness of a composite service based on a fully observable and static setting, we propose a statistical approach built on expectation maximized over a finite mixture model. Our experiments show that our approach can dynamically punish or reward the constituents of composite services while making only partial observations.

/pdf/behind-the-curtain-service-selection-via-trust-in-composite-2bavsknmo7.pdf

Behind the Curtain: Service Selection via Trust in Composite Services

People-driven service engagements involve communication over channels such as chat and email. Such engagements should be understood at the level of the commitments that the participants create and manipulate. Doing so provides a grounding for the communications and yields a business-level accounting of the progress of a service engagement. Existing work on commitment-based service engagements is limited to design-time model creation and verification. In contrast, we present a novel approach for capturing commitment-based engagements that are created dynamically in conversations. We monitor commitments identifying their creation, delegation, completion, or cancellation in the conversations. We have developed a prototype and evaluated it on real-world chat and email datasets. Our prototype captures commitments with a high F-measure of 90% in emails (Enron email corpus) and 80% in chats (HP IT support chat dataset) and provides promising results for capturing additional commitment operations.

/pdf/monitoring-commitments-in-people-driven-service-engagements-34jdnblbyo.pdf

Anup K. Kalia

Papers

Classifying sanctions and designing a conceptual sanctioning process model for socio-technical systems

Resolving goal conflicts via argumentation-based analysis of competing hypotheses

Mono2Micro: an AI-based toolchain for evolving monolithic enterprise applications to a microservice architecture

Behind the Curtain: Service Selection via Trust in Composite Services

Monitoring Commitments in People-Driven Service Engagements