Computer Engineering / Bilgisayar Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/10
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Conference Object Citation - WoS: 37Graph Theoretic Clustering Algorithms in Mobile Ad Hoc Networks and Wireless Sensor Networks (survey)(Azerbaijan National Academy of Sciences, 2007) Erciyeş, Kayhan; Dağdeviren, Orhan; Çokuslu, Deniz; Özsoyeller, DenizClustering in mobile ad hoc networks (MANETs) and wireless sensor networks (WSNs) is an important method to ease topology management and routing in such networks. Once the clusters are formed, the leaders (coordinators) of the clusters may be used to form a backbone for efficient routing and communication purposes. A set of clusters may also provide the underlying physical structure for multicast communication for a higher level group communication module which may effectively be used for fault tolerance and key management for security purposes. We survey graph theoretic approaches for clustering in MANETs and WSNS and show that although there is a wide range of such algorithms, each may be suitable for a different cross-layer design objective.Article Citation - WoS: 58Citation - Scopus: 72A Reference Model for Bim Capability Assessments(Elsevier Ltd., 2019) Yılmaz, Gökçen; Akçamete, Aslı; Demirörs, OnurVarious BIM capability and maturity models have been developed to assist architecture, engineering, construction and facilities management (AEC/FM) organizations in measuring the performance of their BIM utilizations. Due to differences in applicability and focus of these models, they are able to meet the demands of different BIM users. In this study, eight BIM capability and maturity models identified in the literature are compared based on several different criteria. The results show that there is no holistic model that includes process definitions that cover the facility life-cycle and contains measures for assessing all of these AEC/FM processes. A reference model for assessing BIM capability of AEC/FM processes was developed. It was grounded on the meta-model of ISO/IEC 330xx family of standards and developed iteratively via expert reviews and an exploratory case study. It includes AEC/FM processes which were evaluated using the BIM capability levels, their associated BIM attributes, and a four-point rating scale. BIM-CAREM was evaluated by conducting four explanatory case studies. The results showed that BIM-CAREM was capable of identifying BIM capabilities of different AEC/FM processes.Article Citation - WoS: 23Citation - Scopus: 31A Survey on Multithreading Alternatives for Soft Error Fault Tolerance(Association for Computing Machinery (ACM), 2019) Öz, Işıl; Arslan, SanemSmaller transistor sizes and reduction in voltage levels in modern microprocessors induce higher soft error rates. This trend makes reliability a primary design constraint for computer systems. Redundant multithreading (RMT) makes use of parallelism in modern systems by employing thread-level time redundancy for fault detection and recovery. RMT can detect faults by running identical copies of the program as separate threads in parallel execution units with identical inputs and comparing their outputs. In this article, we present a survey of RMT implementations at different architectural levels with several design considerations. We explain the implementations in seminal papers and their extensions and discuss the design choices employed by the techniques. We review both hardware and software approaches by presenting the main characteristics and analyze the studies with different design choices regarding their strengths and weaknesses. We also present a classification to help potential users find a suitable method for their requirement and to guide researchers planning to work on this area by providing insights into the future trend.Article Citation - WoS: 2Citation - Scopus: 2Density-Aware Cellular Coverage Control: Interference-Based Density Estimation(Elsevier, 2019) Eroğlu, Alperen; Yaman, Okan; Onur, ErtanAs demand for mobile communications increases, cells have to become smaller to efficiently use the scarce spectrum and to increase capacity, and small-cell networks will hereby emerge. They may be large in scale and highly dynamic resembling ad hoc networks due to the moving base stations. The variations in the density of the small cell networks impact the quality of service and introduce many novel challenges such as coverage control. We propose two novel base station density estimators, the interference-based density estimator (IDE) and the multi-access edge cloud-based density estimator (CDE) in a three-dimensional field. The estimators employ received signal strength measurements. We validate these two density estimators by using Monte-Carlo simulations. Furthermore, we analyze the impact of density on network outage in cellular networks and propose a density-aware cell zooming technique. According to the observations, base station (BS) density affects network coverage significantly. Received signal strength (RSS)-based density estimators can easily be implemented and applied in the network communication stack although they are more prone to shadowing and fading. Under favour of the density-aware cell zooming method, the network outage can be managed dynamically by adapting the transmit power, which provides a self-configurable and -organized network. (C) 2019 Elsevier B.V. All rights reserved.Article Citation - WoS: 6Citation - Scopus: 9Process Ontology Development Using Natural Language Processing: a Multiple Case Study(Emerald Group Publishing, 2019) Gürbüz, Özge; Rabhi, Fethi; Demirörs, OnurPurpose: Integrating ontologies with process modeling has gained increasing attention in recent years since it enhances data representations and makes it easier to query, store and reuse knowledge at the semantic level. The authors focused on a process and ontology integration approach by extracting the activities, roles and other concepts related to the process models from organizational sources using natural language processing techniques. As part of this study, a process ontology population (PrOnPo) methodology and tool is developed, which uses natural language parsers for extracting and interpreting the sentences and populating an event-driven process chain ontology in a fully automated or semi-automated (user assisted) manner. The purpose of this paper is to present applications of PrOnPo tool in different domains. Design/methodology/approach: A multiple case study is conducted by selecting five different domains with different types of guidelines. Process ontologies are developed using the PrOnPo tool in a semi-automated and fully automated fashion and manually. The resulting ontologies are compared and evaluated in terms of time-effort and recall-precision metrics. Findings: From five different domains, the results give an average of 70 percent recall and 80 percent precision for fully automated usage of the PrOnPo tool, showing that it is applicable and generalizable. In terms of efficiency, the effort spent for process ontology development is decreased from 250 person-minutes to 57 person-minutes (semi-automated). Originality/value: The PrOnPo tool is the first one to automatically generate integrated process ontologies and process models from guidelines written in natural language. © 2018, Emerald Publishing Limited.Article Citation - WoS: 67Citation - Scopus: 91A Survey on Modeling and Model-Driven Engineering Practices in the Embedded Software Industry(Elsevier Ltd., 2018) Akdur, Deniz; Garousi, Vahid; Demirörs, OnurSoftware-intensive embedded systems have become an essential aspect of our lives. To cope with its growing complexity, modeling and model-driven engineering (MDE) are widely used for analysis, design, implementation, and testing of these systems. Since a large variety of software modeling practices is used in the domain of embedded software, it is important to understand and characterize the-state-of-the-practices and also the benefits, challenges and consequences of using software modeling approaches in this domain. The goal of this study is to investigate those practices in the embedded software engineering projects by identifying to what degree, why and how software modeling and MDE are used. To achieve this objective, we designed and conducted an online survey. Opinions of 627 practicing embedded software engineers from 27 different countries are included in the survey. The survey results reveal important and interesting findings about the state of software modeling and MDE practices in the worldwide embedded software industry. Among the results: (1) Different modeling approaches (from informal sketches to formalized models) are widely used in the embedded software industry with different needs and all of the usages could be effective depending on the various modeling characteristics; (2) The majority of participants use UML; and the second most frequently selected response is “Sketch/No formal modeling language” which shows the wide-spread informal usage of modeling; (3) In model-driven approaches, it is not so important to have a graphical syntax to represent the model (as in UML) and depending on the type of target embedded industrial sector, modeling stakeholders prefer models, which can be represented in a format that is readable by a machine (as in DSL); (4) Sequence diagrams and state-machines are the two most popular diagram types; (5) Top motivations for adopting MDE are: cost savings, achieving shorter development time, reusability and quality improvement. The survey results will shed light on the state of software modeling and MDE practices and provide practical benefits to embedded software professionalsArticle Citation - WoS: 33Citation - Scopus: 46A Semi-Automated Approach for Generating Natural Language Requirements Documents Based on Business Process Models(Elsevier Ltd., 2018) Aysolmaz, Banu; Leopold, Henrik; Reijers, Hajo A.; Demirörs, OnurContext: The analysis of requirements for business-related software systems is often supported by using business process models. However, the final requirements are typically still specified in natural language. This means that the knowledge captured in process models must be consistently transferred to the specified requirements. Possible inconsistencies between process models and requirements represent a serious threat for the successful development of the software system and may require the repetition of process analysis activities. Objective: The objective of this paper is to address the problem of inconsistency between process models and natural language requirements in the context of software development. Method: We define a semi-automated approach that consists of a process model-based procedure for capturing execution-related data in requirements models and an algorithm that takes these models as input for generating natural language requirements. We evaluated our approach in the context of a multiple case study with three organizations and a total of 13 software development projects. Results: We found that our approach can successfully generate well-readable requirements, which do not only positively contribute to consistency, but also to the completeness and maintainability of requirements. The practical use of our approach to identify a suitable subcontractor on the market in 11 of the 13 projects further highlights the practical value of our approach. Conclusion: Our approach provides a structured way to obtain high-quality requirements documents from process models and to maintain textual and visual representations of requirements in a consistent way.Article Citation - WoS: 66Citation - Scopus: 85Factors Influencing the Understandability of Process Models: a Systematic Literature Review(Elsevier Ltd., 2018) Dikici, Ahmet; Türetken, Oktay; Demirörs, OnurContext Process models are key in facilitating communication in organizations and in designing process-aware information systems. Organizations are facing increasingly larger and more complex processes, which pose difficulties to the understandability of process models. The literature reports several factors that are considered to influence the understandability of process models. However, these studies typically focus on testing of a limited set of factors. A work that collects, abstracts and synthesizes an in-depth summary of the current literature will help in developing the research in this field. Objective We conducted a systematic literature review (SLR) focusing on the empirical studies in the existing literature in order to better understand the state of the research on process model understandability, and identify the gaps and opportunities for future research. Method We searched the studies between the years 1995 and 2015 in established electronic libraries. Out of 1066 publications retrieved initially, we selected 45 publications for thorough analysis. We identified, analyzed and categorized factors that are considered to influence the understandability of process models as studied in the literature using empirical methods. We also analyzed the indicators that are used to quantify process model understandability. Results Our analysis identifies several gaps in the field, as well as issues of inconsistent findings regarding the effect of some factors, unbalanced emphasis on certain indicators, and methodological concerns. Conclusions The existing research calls for comprehensive empirical studies to contribute to a better understanding of the factors of process model understandability. Our study is a comprehensive source for researchers working on the understandability of process models and related fields, and a useful guide for practitioners aiming to generate understandable process models.Article Citation - WoS: 26Citation - Scopus: 30Ensuring Performance and Provider Profit Through Data Replication in Cloud Systems(Springer Verlag, 2017) Tos, Uras; Mokadem, Riad; Hameurlain, Abdelkader; Ayav, Tolga; Bora, ŞebnemCloud computing is a relatively recent computing paradigm that is often the answer for dealing with large amounts of data. Tenants expect the cloud providers to keep supplying an agreed upon quality of service, while cloud providers aim to increase profits as it is a key ingredient of any economic enterprise. In this paper, we propose a data replication strategy for cloud systems that satisfies the response time objective for executing queries while simultaneously enables the provider to return a profit from each execution. The proposed strategy estimates the response time of the queries and performs data replication in a way that the execution of any particular query is still estimated to be profitable for the provider. We show with simulations that how the proposed strategy fulfills these two criteria.Article Citation - WoS: 7Citation - Scopus: 11Exploiting Model Morphology for Event-Based Testing(Institute of Electrical and Electronics Engineers Inc., 2015) Belli, Fevzi; Beyazıt, MutluModel-based testing employs models for testing. Model-based mutation testing (MBMT) additionally involves fault models, called mutants, by applying mutation operators to the original model. A problem encountered with MBMT is the elimination of equivalent mutants and multiple mutants modeling the same faults. Another problem is the need to compare a mutant to the original model for test generation. This paper proposes an event-based approach to MBMT that is not fixed on single events and a single model but rather operates on sequences of events of length k ≥ 1 and invokes a sequence of models that are derived from the original one by varying its morphology based on k. The approach employs formal grammars, related mutation operators, and algorithms to generate test cases, enabling the following: (1) the exclusion of equivalent mutants and multiple mutants; (2) the generation of a test case in linear time to kill a selected mutant without comparing it to the original model; (3) the analysis of morphologically different models enabling the systematic generation of mutants, thereby extending the set of fault models studied in related literature. Three case studies validate the approach and analyze its characteristics in comparison to random testing and another MBMT approach.