We may not be able to make you love reading, but production workflow concepts and techniques will lead you to love reading starting from now. Book is the window to open the new world. The world that you want is in the better stage and level. World will always guide you to even the prestige stage of the life. You know, this is some of how reading will give you the kindness. In this case, more books you read more knowledge you know, but it can mean also the bore is full.

Production workflow: concepts and techniques

10 years of software architecture knowledge management

Entity Resolution (ER), a core task of Data Integration, detects different entity profiles that correspond to the same real-world object. Due to its inherently quadratic complexity, a series of techniques accelerate it so that it scales to voluminous data. In this survey, we review a large number of relevant works under two different but related frameworks: Blocking and Filtering. The former restricts comparisons to entity pairs that are more likely to match, while the latter identifies quickly entity pairs that are likely to satisfy predetermined similarity thresholds. We also elaborate on hybrid approaches that combine different characteristics. For each framework we provide a comprehensive list of the relevant works, discussing them in the greater context. We conclude with the most promising directions for future work in the field.

/pdf/blocking-and-filtering-techniques-for-entity-resolution-a-1b03a2we84.pdf

Blocking and Filtering Techniques for Entity Resolution: A Survey

Cloud migration process-A survey, evaluation framework, and open challenges

Context The software architecture of a system is the result of a set of architectural decisions. The topic of architectural decisions in software engineering has received significant attention in recent years. However, no systematic overview exists on the state of research on architectural decisions. Objective The goal of this study is to provide a systematic overview of the state of research on architectural decisions. Such an overview helps researchers reflect on previous research and plan future research. Furthermore, such an overview helps practitioners understand the state of research, and how research results can help practitioners in their architectural decision-making. Method We conducted a systematic mapping study, covering studies published between January 2002 and January 2012. We defined six research questions. We queried six reference databases and obtained an initial result set of 28,895 papers. We followed a search and filtering process that resulted in 144 relevant papers. Results After classifying the 144 relevant papers for each research question, we found that current research focuses on documenting architectural decisions. We found that only several studies describe architectural decisions from the industry. We identified potential future research topics: domain-specific architectural decisions (such as mobile), achieving specific quality attributes (such as reliability or scalability), uncertainty in decision-making, and group architectural decisions. Regarding empirical evaluations of the papers, around half of the papers use systematic empirical evaluation approaches (such as surveys, or case studies). Still, few papers on architectural decisions use experiments. Conclusion Our study confirms the increasing interest in the topic of architectural decisions. This study helps the community reflect on the past ten years of research on architectural decisions. Researchers are offered a number of promising future research directions, while practitioners learn what existing papers offer.

/pdf/past-and-future-of-software-architectural-decisions-a-3askkl0h6a.pdf

Past and future of software architectural decisions - A systematic mapping study

https://www.ifs.hsr.ch/uploads/tx_icscrm/sda-jss-specialissuewicsa2011v16finalauthorsversion.pdf

Reference architecture, metamodel, and modeling principles for architectural knowledge management in information technology services

Capturing and sharing design knowledge such as architectural decisions is becoming increasingly important in professional Information Technology (IT) services firms. Methods, models, and tools supporting explicit knowledge management strategies have been proposed in recent years. In this paper, we extend previous work in the architectural knowledge management community to satisfy the requirements of an additional user group: the designers of IT infrastructure solutions that are outsourced from one company to another. Such strategic outsourcing solutions require complex, contractually relevant design decisions concerning many different resources such as IT infrastructures, people, and real estate. In this paper, we present a reference architecture and a decision process-oriented knowledge metamodel that we synthesized from the domain-specific functional requirements and quality attributes. We also present a tool implementation of these decision modeling concepts and discuss user feedback.

/pdf/architecturally-significant-requirements-reference-2hqxzxytrr.pdf

Architecturally Significant Requirements, Reference Architecture, and Metamodel for Knowledge Management in Information Technology Services

Attention-based Interpretability with Concept Transformers

Decisions Required vs. Decisions Made: Connecting Enterprise Architects and Solution Architects via Guidance Models

Record linkage is an essential part of nearly all real-world systems that consume structured and unstructured data coming from different sources. Typically no common key is available for connecting records. Massive data integration processes often have to be completed before any data analytics and further processing can be performed. In this work we focus on company entity matching, where company name, location and industry are taken into account. Our contribution is a highly scalable, enterprise-grade end-to-end system that uses rule-based linkage algorithms in combination with a machine learning approach to account for short company names. Linkage time is greatly reduced by an efficient decomposition of the search space using MinHash. Based on real-world ground truth datasets, we show that our approach reaches a recall of 91% compared to 73% for baseline approaches, while scaling linearly with the number of nodes used in the system.

Christoph Miksovic

Papers

Reference architecture, metamodel, and modeling principles for architectural knowledge management in information technology services

Architecturally Significant Requirements, Reference Architecture, and Metamodel for Knowledge Management in Information Technology Services

Attention-based Interpretability with Concept Transformers

Decisions Required vs. Decisions Made: Connecting Enterprise Architects and Solution Architects via Guidance Models

Fast Record Linkage for Company Entities