JPI Feature Models: Exploring a JPI and FOP Symbiosis for Software Modeling

Looking for a complete modular software development paradigm, this article presents Join Point Interface JPI Feature Models, in the context of a JPI and Feature-Oriented Programming FOP symbiosis paradigm. Therefore, this article describes pros and cons of JPI and FOP approaches for the modular software and software product line production, respective; and highlights the benefits of this mixing proposal; in particular, the JPI Feature Model benefits for a high-level software product line modeling. As an application example, this article applies JPI Features Models on a classic FOP example already modeled using a previous aspect-oriented feature model proposal. Main goals of this application are to visualize traditional feature models preserved components such alternative and optional feature sets and optional and mandatory features as well as special features associations (cross-tree constraints), and differences and advantages with respect to previous research works about extending feature model to support aspect-oriented modeling principles

Aspect-oriented analysis for software product lines requirements engineering

SAC '11 Proceedings of the 2011 ACM 26th Symposium on Applied ComputingRequirements analysis and modeling for Software Product Lines demands the use of feature models, but also requires additional models to help identifying, describing, and specifying features. Traditional approaches usually perform this manually and, in general, the identification and modularization of crosscutting features is ignored, or not handled systematically. This hinders requirements change. We propose an aspect-oriented approach for SPL enriched to automatically derive feature models where crosscutting features are identified and modularized using aspect-oriented concepts and techniques. This is achieved by adapting and extending the AORA (Aspect-Oriented Requirements Analysis) approach. AORA provides templates to specify and organize requirements based on concerns and responsibilities. A set of heuristics is defined to help identifying features and their dependencies in a product line. A tool was developed to automatically generate the feature model from AORA templates

Integrating the common variability language with multilanguage annotations for web engineering

Web applications development involves managing a high diversity of files and resources like code, pages or style sheets, implemented in different languages. To deal with the automatic generation of custom-made configurations of web applications, industry usually adopts annotation-based approaches even though the majority of studies encourage the use of composition-based approaches to implement Software Product Lines. Recent work tries to combine both approaches to get the complementary benefits. However, technological companies are reticent to adopt new development paradigms such as feature-oriented programming or aspect-oriented programming. Moreover, it is extremely difficult, or even impossible, to apply these programming models to web applications, mainly because of their multilingual nature, since their development involves multiple types of source code (Java, Groovy, JavaScript), templates (HTML, Markdown, XML), style sheet files (CSS and its variants, such as SCSS), and other files (JSON, YML, shell scripts). We propose to use the Common Variability Language as a composition-based approach and integrate annotations to manage fine grained variability of a Software Product Line for web applications. In this paper, we (i) show that existing composition and annotation-based approaches, including some well-known combinations, are not appropriate to model and implement the variability of web applications; and (ii) present a combined approach that effectively integrates annotations into a composition-based approach for web applications. We implement our approach and show its applicability with an industrial real-world system.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

트랜스포머를 이용한 키워드 반영 추출 요약에 대한 연구

학위논문(석사) -- 서울대학교대학원 : 공과대학 협동과정 바이오엔지니어링전공, 2023. 2. 최진욱.Text summarization is well-known as a representative task in natural language processing. Text summarization methods generate brief written summaries of documents such as journal articles. In recent years, the performance of text summarization methods has improved significantly with the development of pretrained language models based on Transformer architectures such as BERT and GPT 3. Recently, the development of language models designed to generate controllable output based on user preferences has attracted considerable attention as a topic of active research. Controllable summarization methods such as query-focused or aspect-oriented summarization techniques have also emerged as promising approaches. In particular, aspect-oriented summarization generates a summary in terms of specific aspects provided as user input. In this study, we propose a method to improve the performance of an aspect-oriented extractive summarization model presented in a previous work. The proposed method helps the model to generate aspect-oriented summaries by reflecting the relevance between sentence features and keyword features representing the aspect. To evaluate the performance of the proposed method, we constructed a new dataset consisting of articles on COVID-19 labeled in terms of two aspects: Trend and Action. The results showed that our proposed method outperformed a baseline model on the new dataset. The proposed method exhibited higher performance than the baseline by roughly 3.6–4.3% in terms of Trend, and showed a relatively low impact with an improvement of less than 1% in terms of Action. However, in both aspects, we observed that even incorrect sentences included in a generated summary tended to be related to the defined aspect. Thus, we demonstrate that the proposed method generated more aspect-oriented summaries with content relevant to the defined aspect.텍스트 요약(Text Summarization)은 자연어 처리 분야의 대표적인 작업 중 하나이다. 텍스트 요약의 목적은 신문 기사와 같은 문서를 간결하지만, 핵심적인 내용을 중심으로 요약하는 것이다. BERT, GPT-3와 같은 트랜스포머 기반의 사전학습 모델들이 개발됨에 따라, 요약 모델의 성능이 크게 향상되었다. 최근에는 사용자의 목적 혹은 선호도를 반영하여 출력을 생성하는 언어 모델을 개발하기 위해 많은 연구들이 진행되고 있다. 텍스트 요약 분야에서도 이러한 흐름에 따라 쿼리 중심(Query focused) 혹은 측면 중심(Aspect oriented) 요약과 같이 제어 가능한 요약문 생성에 대한 연구들이 등장하고 있다. 측면 중심 요약(Aspect oriented)은 사용자가 알고 싶은 특정 측면에 대해서 요약문을 생성하는 것을 목표로 한다. 본 논문에서는 선행 연구에서 제안한 측면 중심 요약 모델의 성능 향상을 위한 방법을 제안한다. 제안된 방법은 문장의 표현 벡터와 측면을 대표하는 키워드 표현 벡터들 사이의 연관성을 기존의 문장 표현 벡터에 반영함으로써 모델이 측면과 관련된 요약문을 생성하도록 했다. 평가를 위해서, 발생 현황과 관련 대응이라는 두 가지 측면을 가지는 COVID-19 관련 기사로 구성된 새로운 데이터셋을 구축하였다. 제안된 방법들은 새로운 데이터셋에 대하여 기존 모델보다 더 좋은 성능을 보여주었다. 제안된 방법은 발생 현황 측면에서는 3.6~4.3%로 높은 성능 향상을 가져왔으며, 관련 대응 측면에서는 1%미만의 향상으로, 비교적 낮은 효과를 보여주었다. 하지만 두 측면 모두에서 오답이라 하더라도 측면과 관련된 문장을 선택하는 것을 관찰했다. 이를 통해, 제안된 방법이 모델의 측면 지향 요약에 도움을 주었음을 확인할 수 있었다.1. Introduction 1 1.1. Background 1 1.2. Task Description 3 1.2.1. Text Summarization 3 1.2.2. Aspect Oriented Summarization 4 2. Related Works 7 2.1. Extractive Summarization 7 2.2. Aspect Oriented Summarization 10 2.3. AOSUMM 11 3. Materials and Method 13 3.1. Dataset for Training 13 3.2. Dataset for Evaluation 13 3.2.1. Aspect Definition 14 3.2.2. Annotation 15 3.3. Evaluation Metric 17 3.4. Keyword Selection 19 3.5. Method 21 3.5.1. Extraction of keywords feature 23 3.5.2. Relevance Score 25 3.5.3. Proposed Method 27 4. Results and Discussion 29 4.1. Experiment Settings 29 4.2. Results 30 4.2.1. Automatic Evaluation 30 4.2.2. Qualitative Evaluation 35 4.3. Discussion 38 5. Conclusion 41 Bibliography 43 Appendix 45 Abstract in Korean 51석

Aspect-based approach to modeling access control policies, An

Department Head: L. Darrell Whitley.2007 Spring.Includes bibliographical references (pages 119-126).Access control policies determine how sensitive information and computing resources are to be protected. Enforcing these policies in a system design typically results in access control features that crosscut the dominant structure of the design (that is, features that are spread across and intertwined with other features in the design). The spreading and intertwining of access control features make it difficult to understand, analyze, and change them and thus complicate the task of ensuring that an evolving design continues to enforce access control policies. Researchers have advocated the use of aspect-oriented modeling (AOM) techniques for addressing the problem of evolving crosscutting features. This dissertation proposes an approach to modeling and analyzing crosscutting access control features. The approach utilizes AOM techniques to isolate crosscutting access control features as patterns described by aspect models. Incorporating an access control feature into a design involves embedding instantiated forms of the access control pattern into the design model. When composing instantiated access control patterns with a design model, one needs to ensure that the resulting composed model enforces access control policies. The approach includes a technique to verify that specified policies are enforced in the composed model. The approach is illustrated using two well-known access control models: the Role- Based Access Control (RBAC) model and the Bell-LaPadula (BLP) model. Features that enforce RBAC and BLP models are described by aspect models. We show how the aspect models can be composed to create a new hybrid access control aspect model. We also show how one can verify that composition of a base (primary) design model and an aspect model that enforces specified policies produces a composed model in which the policies are still enforced

Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed

Early aspects: aspect-oriented requirements engineering and architecture design

This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

A taxonomy of asymmetric requirements aspects

The early aspects community has received increasing attention among researchers and practitioners, and has grown a set of meaningful terminology and concepts in recent years, including the notion of requirements aspects. Aspects at the requirements level present stakeholder concerns that crosscut the problem domain, with the potential for a broad impact on questions of scoping, prioritization, and architectural design. Although many existing requirements engineering approaches advocate and advertise an integral support of early aspects analysis, one challenge is that the notion of a requirements aspect is not yet well established to efficaciously serve the community. Instead of defining the term once and for all in a normally arduous and unproductive conceptual unification stage, we present a preliminary taxonomy based on the literature survey to show the different features of an asymmetric requirements aspect. Existing approaches that handle requirements aspects are compared and classified according to the proposed taxonomy. In addition,we study crosscutting security requirements to exemplify the taxonomy's use, substantiate its value, and explore its future directions