Developing and maintaining software is a difficult task, and finding effective methods of understanding software is more necessary now than ever with the last few decades seeing a dramatic climb in the scale of software. Appropriate visualisations may enable greater understanding of the datasets we deal with in software engineering. As an aid for sense-making, visualisation is widely used in daily life (through graphics such as weather maps and road signs), as well as in other research domains, and is thought to be exceedingly beneficial. Unfortunately, there has not been widespread use of the multitude of techniques which have proposed for the software engineering domain. Tag clouds are a simple, text-based visualisation commonly found on the internet. Typically, implementations of tag clouds have not included rich interactive features which are necessary for data exploration. In this thesis, I introduce design considerations and a task set for enabling interaction in a tag cloud visualisation system. These considerations are based on an analysis of challenges in visualising software engineering data, and the perceptive influences of visual properties available in tag clouds. The design and implementation of interactive system Taggle based on these considerations is also presented, along with its broad-based evaluation. Evaluation approaches were informed by a systematic mapping study of previous tag cloud evaluation, providing an overview of existing research in the domain. The design of Taggle was improved following a heuristic evaluation by domain experts. Subsequent evaluations were divided into two parts - experiments focused on the tag cloud visualisation technique itself, and a task-based approach focused on the whole interactive system. As evidenced in the series of evaluative studies, the enhanced tag cloud features incorporated into Taggle enabled faster visual search response time, and the system could be used with minimal training to discover relevant information about an unknown software engineering dataset.

Developing and maintaining software is a difficult task, and finding effective methods of understanding software is more necessary now than ever with the last few decades seeing a dramatic climb in the scale of software. Appropriate visualisations may enable greater understanding of the datasets we deal with in software engineering. As an aid for sense-making, visualisation is widely used in daily life (through graphics such as weather maps and road signs), as well as in other research domains, and is thought to be exceedingly beneficial. Unfortunately, there has not been widespread use of the multitude of techniques which have proposed for the software engineering domain. Tag clouds are a simple, text-based visualisation commonly found on the internet. Typically, implementations of tag clouds have not included rich interactive features which are necessary for data exploration. In this thesis, I introduce design considerations and a task set for enabling interaction in a tag cloud visualisation system. These considerations are based on an analysis of challenges in visualising software engineering data, and the perceptive influences of visual properties available in tag clouds. The design and implementation of interactive system Taggle based on these considerations is also presented, along with its broad-based evaluation. Evaluation approaches were informed by a systematic mapping study of previous tag cloud evaluation, providing an overview of existing research in the domain. The design of Taggle was improved following a heuristic evaluation by domain experts. Subsequent evaluations were divided into two parts - experiments focused on the tag cloud visualisation technique itself, and a task-based approach focused on the whole interactive system. As evidenced in the series of evaluative studies, the enhanced tag cloud features incorporated into Taggle enabled faster visual search response time, and the system could be used with minimal training to discover relevant information about an unknown software engineering dataset.

As software engineering is a socio-technical research field, there is a myriad of research strategies and data sources that researchers need to consider when designing their studies. These choices determine different tradeoffs in terms of generalizability, realism, and control, among other aspects of research quality. It is not possible to create a perfect study, so these strengths and weaknesses are acceptable at the study level; however, when a research community's collective body of work suffers from an imbalance in these tradeoffs it can negatively impact overall research quality. Through this thesis, I investigate the research strategies and data sources that are used by the software engineering research community, and reflect on how this may affect aspects of research quality in our collective body of work. I apply Runkel and McGrath's models of research strategies and data sources to the software engineering domain through a systematic mapping study of three years of International Conference on Software Engineering (ICSE) proceedings and a mixed-methods survey of the authors of these papers. I found that a majority of papers report computational studies relying on trace measures rather than active human participation, showing an imbalance where generalizability and realism are prioritized over control. Through my survey, I confirmed that researcher participants explicitly prioritized realism and generalizability over control, impacting their research design choices. This imbalance in prioritization has the potential to lead to a collective failure to control for extraneous factors in the measurement of human behavior in software development, and without understanding what causes the behaviors we measure, we cannot fully understand why certain approaches and techniques work better than others, thus slowing our ability to advance as a research domain. Therefore, I present a call to action for the community to critically examine and discuss the issues raised by this research, and implement changes to increase the quality and diversity of our future work as a community. / Graduate / 2019-08-08

Submitted by PPG Ci?ncia da Computa??o (ppgcc@pucrs.br) on 2017-12-11T16:00:35Z No. of bitstreams: 1 Gianlucca_Oliveira_Puglia_dis.pdf: 2043630 bytes, checksum: f7fc70f33d1d15b56eded8458fbed2fa (MD5) / Approved for entry into archive by Tatiana Lopes (tatiana.lopes@pucrs.br) on 2017-12-18T11:25:26Z (GMT) No. of bitstreams: 1 Gianlucca_Oliveira_Puglia_dis.pdf: 2043630 bytes, checksum: f7fc70f33d1d15b56eded8458fbed2fa (MD5) / Made available in DSpace on 2017-12-18T11:49:55Z (GMT). No. of bitstreams: 1 Gianlucca_Oliveira_Puglia_dis.pdf: 2043630 bytes, checksum: f7fc70f33d1d15b56eded8458fbed2fa (MD5) Previous issue date: 2017-03-21 / As tecnologias de mem?rias n?o-vol?teis s?o uma grande promessa na ?rea de arquitetura de computadores e ? esperado que sejam poderosas ferramentas para solucionar os problemas referentes a manipula??o eficiente de dados dos dias de hoje. Estas tecnologias prov?m alta performance e acesso em granularidade de bytes com a distinta vantagem de serem persistentes. Por?m, afim de explorar estas tecnologias em todo seu potencial, os sistemas e arquiteturas de hoje precisam buscar meios de se adaptar a esta nova forma de acessar dados e de superar os desafios que v?m com ela.Trabalhos existentes na ?rea j? prop?em m?todos para adaptar as arquiteturas existentes para o uso de NVM bem como formas inovadoras de empregar estas mem?rias em futuras aplica??es. No entanto, o suporte dos sistemas operacionais a estas solu??es, ainda que existente, ainda ? muito limitado. Neste trabalho, n?s apresentamos duas varia??es da chamada de sistema msync, modeladas para explorar as caracter?sticas das tecnologias de NVM e garantir consist?ncia para os dados dos usu?rios. Ambas s?o solu??es simples que permitem aos usu?rios definirem checkpoints de seus arquivos usando a sintaxe comum de sistemas de arquivos. N?s implementamos e testamos estes m?todos sobre o sistema operacional Linux utilizando como base um sistema de arquivo nativamente voltado a NVM. Nossos resultados mostram que estes mecanismos s?o capazes de garantir a integridade dos arquivos mesmo na presen?a de falhas no sistema enquanto mant?m uma performance razo?vel. / Upcoming non-volatile memory technologies are a big promise in computer architecture and are expected to be powerful tools to address today?s issues regarding efficient data manipulation. They provide high performance and byte granularity while also having the distinct advantage of being persistent. However in order to explore these technologies to their full potential, existing systems and architecture must adapt to this new way of working with data and workaround the challenges that come with it. Existing work in the area already proposes methods to adapt existing architecture to NVM as well as innovative ways to employ these memories in future applications. However operating system support to such NVM-enabled solutions, although existent, still very limited. In this work, we present two variations of the existing mmap system call, designed to both explore NVM characteristics and provide user data consistency. Both are very simple solutions that allow users to control the persistence and define checkpoints to their files while using the common mapped file syntax. We have implemented and tested these methods over Linux using a NVM file system as our base. Our results show that these mechanisms can ensure file integrity in the presence of system failures while also providing a reasonable performance.

Nowadays, autonomous driving revolution is getting closer to reality. To achieve the Autonomous driving the first step is to develop the Advanced Driver Assistance System (ADAS). Driver-assistance systems are one of the fastest-growing segments in automotive electronics since already there are many forms of ADAS available. To investigate state of art of development of ADAS towards Autonomous Driving, we develop Systematic Mapping Study (SMS). SMS methodology is used to collect, classify, and analyze the relevant publications. A classification is introduced based on the developments carried out in ADAS towards Autonomous driving. According to SMS methodology, we identified 894 relevant publications about ADAS and its developmental journey toward Autonomous Driving completed from 2012 to 2016. We classify the area of our research under three classifications: technical classifications, research types and research contributions. The related publications are classified under thirty-three technical classifications. This thesis sheds light on a better understanding of the achievements and shortcomings in this area. By evaluating collected results, we answer our seven research questions. The result specifies that most of the publications belong to the Models and Solution Proposal from the research type and contribution. The least number of the publications belong to the Automated…Autonomous driving from the technical classification which indicated the lack of publications in this area.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-08-17T12:14:52Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_AlexNery_V18 (VFinal_Biblioteca).pdf: 3946748 bytes, checksum: 139ad5265a5a9bfe6cb97a591113354a (MD5) / Made available in DSpace on 2016-08-17T12:14:54Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_AlexNery_V18 (VFinal_Biblioteca).pdf: 3946748 bytes, checksum: 139ad5265a5a9bfe6cb97a591113354a (MD5) Previous issue date: 2015-02-27 / FACEPE / Contexto – Tem-se observado que o interesse em conduzir estudos empíricos vem aumentando na comunidade de Engenharia de Software, permitindo melhorar a qualidade das pesquisas e acelerar a adoção de novas tecnologias no mercado de software. Para fomentar pesquisas empíricas nesse contexto, é essencial entender os ambientes, diretrizes, processos, ferramentas e outros recursos disponíveis para conduzir tais estudos. Objetivo – Esta pesquisa tem o objetivo de identificar mecanismos de suporte (metodologias, framework, ferramentas, guias, processos, etc.) utilizados para planejar e conduzir estudos empíricos na comunidade de Engenharia de Software Empírica. Além disso, espera-se mapear outras evidências importantes na área, como os métodos empíricos mais utilizados e a evolução, ao longo dos anos, do uso de estratégias e mecanismos de pesquisa empírica. Método – Foi adotado o Estudo de Mapeamento Sistemático, conduzido de acordo com guias e diretrizes de Engenharia de Software Baseada em Evidências. Resultado – Foram identificados 375 mecanismos. Este trabalho fornece um catálogo com informações de todos os mecanismos e em quais estratégias empíricas são aplicados. Serão abordados os mecanismos mais utilizados para guiar os principais métodos empíricos. Este trabalho também discute outras informações relevantes da comunidade de Engenharia de Software Empírica. Observou-se que a maioria dos mecanismos utilizados como referência para guiar estudos empíricos é adotado de outras áreas científicas. Além disso, muitos estudos não aplicam estratégias empíricas e / ou não citam referências para apoiar sua pesquisa. Experimento e estudo de caso são os métodos empíricos mais aplicados. Conclusão – Esta pesquisa evidenciou que a realização de estudos empíricos na Engenharia de Software tem aumentado ao longo dos anos. No entanto, ainda há lacunas a serem preenchidas, como o desenvolvimento de novos ambientes e recursos para auxiliar atividades específicas nessa área. Portanto, um catálogo de mecanismos de suporte, onde e como foram aplicados, é um trunfo importante para a comunidade de Engenharia de Software. Tal recurso pode promover a realização de estudos empíricos, no sentido de auxiliar a escolha sobre quais estratégias e guias usar em uma pesquisa. Além disso, foram identificadas novas perspectivas e lacunas que podem orientar a definição de outras pesquisas voltadas para a melhoria e disseminação de estudos empíricos na área. / Context – It is possible to observe that empirical studies are gaining recognition in the Software Engineering research community, allowing improve quality of researches and accelerate the adoption of new technologies in the software market. In order to foster empirical research in this context, it is essential understand the environments, guidelines, process, tools, and other mechanisms available to conduct such studies. Objective – This research aims to identify support mechanisms (methodology, framework, tool, guidelines, process, etc.) used to plan and to conduct empirical studies in the Empirical Software Engineering community. In addition, it is expected to map other evidence of this area, as the most widely used empirical methods and the evolution of the use of empirical strategies and mechanisms along the years. Method – The method adopted was the Systematic Mapping Study conducted according to guidelines of Evidence-Based Software Engineering. Result - A total of 375 mechanisms were identified. This work provide a catalog with information of all the identified mechanisms and the empirical strategies in which they were used to support. And also describes the most used support mechanisms to guide the main types of empirical strategies in Software Engineering. This study also discusses relevant findings of the Empirical Software Engineering community. It was observed that the most mechanisms used as a reference to guide empirical studies are not specific to this area. Besides, many studies did not apply empirical strategies and/or did not cite any resource to support their research. Experiment and case study are the empirical strategies most applied. Conclusion – This research showed that the performance of empirical studies in Software Engineering has increased over the years. However, there are still gaps to be filled, as the development of support mechanisms to specific activities in this area. Therefore, the list of support mechanisms, where and how they were applied is an important asset to the Software Engineering community. Such asset can foster empirical studies aiding the choice regarding which strategies and mechanisms to use in a research, as well as pointing out examples where they were used, mainly to newcomers researchers. Also, were identified new perspectives and gaps that foster other research for the improvement and dissemination of empirical research in this area.

Submitted by Fabio Sobreira Campos da Costa (fabio.sobreira@ufpe.br) on 2016-08-17T12:23:47Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_AlexNery_V18 (VFinal_Biblioteca).pdf: 3946748 bytes, checksum: 139ad5265a5a9bfe6cb97a591113354a (MD5) / Made available in DSpace on 2016-08-17T12:23:47Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_AlexNery_V18 (VFinal_Biblioteca).pdf: 3946748 bytes, checksum: 139ad5265a5a9bfe6cb97a591113354a (MD5) Previous issue date: 2015-02-27 / FACEPE / Contexto – Tem-se observado que o interesse em conduzir estudos empíricos vem aumentando na comunidade de Engenharia de Software, permitindo melhorar a qualidade das pesquisas e acelerar a adoção de novas tecnologias no mercado de software. Para fomentar pesquisas empíricas nesse contexto, é essencial entender os ambientes, diretrizes, processos, ferramentas e outros recursos disponíveis para conduzir tais estudos. Objetivo – Esta pesquisa tem o objetivo de identificar mecanismos de suporte (metodologias, framework, ferramentas, guias, processos, etc.) utilizados para planejar e conduzir estudos empíricos na comunidade de Engenharia de Software Empírica. Além disso, espera-se mapear outras evidências importantes na área, como os métodos empíricos mais utilizados e a evolução, ao longo dos anos, do uso de estratégias e mecanismos de pesquisa empírica. Método – Foi adotado o Estudo de Mapeamento Sistemático, conduzido de acordo com guias e diretrizes de Engenharia de Software Baseada em Evidências. Resultado – Foram identificados 375 mecanismos. Este trabalho fornece um catálogo com informações de todos os mecanismos e em quais estratégias empíricas são aplicados. Serão abordados os mecanismos mais utilizados para guiar os principais métodos empíricos. Este trabalho também discute outras informações relevantes da comunidade de Engenharia de Software Empírica. Observou-se que a maioria dos mecanismos utilizados como referência para guiar estudos empíricos é adotado de outras áreas científicas. Além disso, muitos estudos não aplicam estratégias empíricas e / ou não citam referências para apoiar sua pesquisa. Experimento e estudo de caso são os métodos empíricos mais aplicados. Conclusão – Esta pesquisa evidenciou que a realização de estudos empíricos na Engenharia de Software tem aumentado ao longo dos anos. No entanto, ainda há lacunas a serem preenchidas, como o desenvolvimento de novos ambientes e recursos para auxiliar atividades específicas nessa área. Portanto, um catálogo de mecanismos de suporte, onde e como foram aplicados, é um trunfo importante para a comunidade de Engenharia de Software. Tal recurso pode promover a realização de estudos empíricos, no sentido de auxiliar a escolha sobre quais estratégias e guias usar em uma pesquisa. Além disso, foram identificadas novas perspectivas e lacunas que podem orientar a definição de outras pesquisas voltadas para a melhoria e disseminação de estudos empíricos na área. / Context – It is possible to observe that empirical studies are gaining recognition in the Software Engineering research community, allowing improve quality of researches and accelerate the adoption of new technologies in the software market. In order to foster empirical research in this context, it is essential understand the environments, guidelines, process, tools, and other mechanisms available to conduct such studies. Objective – This research aims to identify support mechanisms (methodology, framework, tool, guidelines, process, etc.) used to plan and to conduct empirical studies in the Empirical Software Engineering community. In addition, it is expected to map other evidence of this area, as the most widely used empirical methods and the evolution of the use of empirical strategies and mechanisms along the years. Method – The method adopted was the Systematic Mapping Study conducted according to guidelines of Evidence-Based Software Engineering. Result - A total of 375 mechanisms were identified. This work provide a catalog with information of all the identified mechanisms and the empirical strategies in which they were used to support. And also describes the most used support mechanisms to guide the main types of empirical strategies in Software Engineering. This study also discusses relevant findings of the Empirical Software Engineering community. It was observed that the most mechanisms used as a reference to guide empirical studies are not specific to this area. Besides, many studies did not apply empirical strategies and/or did not cite any resource to support their research. Experiment and case study are the empirical strategies most applied. Conclusion – This research showed that the performance of empirical studies in Software Engineering has increased over the years. However, there are still gaps to be filled, as the development of support mechanisms to specific activities in this area. Therefore, the list of support mechanisms, where and how they were applied is an important asset to the Software Engineering community. Such asset can foster empirical studies aiding the choice regarding which strategies and mechanisms to use in a research, as well as pointing out examples where they were used, mainly to newcomers researchers. Also, were identified new perspectives and gaps that foster other research for the improvement and dissemination of empirical research in this area.

Submitted by Natalia de Souza Gonçalves (natalia.goncalves@ufpe.br) on 2016-09-28T12:40:17Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao - Larissa Falcao - Final - Correcoes Biblioteca - Entrega.pdf: 1172723 bytes, checksum: b0a57a917a5abab25c66870d353d906f (MD5) / Made available in DSpace on 2016-09-28T12:40:17Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertacao - Larissa Falcao - Final - Correcoes Biblioteca - Entrega.pdf: 1172723 bytes, checksum: b0a57a917a5abab25c66870d353d906f (MD5) Previous issue date: 2016-02-18 / CNPq / Software Engineering professionals need to have information about new support mechanisms to decide, not at random, what option is best adapting it needs. One way of obtaining this information is through empirical studies that make the mechanisms used to support the design and development of software, be evaluated in practice. Thus, scientific research through experiments and empirical studies are fundamental during the evaluation of any new technology to software development. In this context, researchers perform experiments to check their proposals under controlled conditions. Therefore, experiments are an important category of empirical studies and are the classical approach for identifying cause-effect relationships. The goal of this dissertation is qualitatively and quantitatively characterizes and analyze human-centric experiments in software engineering, published in three journals andthree conferences proceedings from 2003 to 2013. To reach this objective was performed a systematic mapping study that includes all full papers published at EASE, ESEM, ICSE, ESEJ, JSS, TSE. Based on manual searches in those important conferences and journals in Software Engineering, were analyzed 3671 papers. 244 primary studies were identified as relevant, reporting experiments. In these experiments, we obtained qualitative and quantified data about authors and institutions, subjects, tasks performed, environment, replication and threats to validity. From the analysis performed, this work conclude that despite guidelines exist now, there is a large gap in the report of the experiments. The main contribution of this work is to provide the reporting status of human-centric software engineering experiments and how this field has matured. This work also proposes a list of information that an experiment report expected to have. / Profissionais de engenharia de software precisam ter informações sobre os novos mecanismos de apoio, a fim de decidir sem ser ao acaso, qual é a melhor opção que se adapta ao que se precisa. Uma maneira de obter essas informações é através de estudos empíricos, que permitem que os mecanismos utilizados para apoiar a concepção e desenvolvimento de software sejam avaliados na prática. Assim, a pesquisa científica através de experimentos e estudos empíricos são de fundamental importância na avaliação de qualquer nova tecnologia para desenvolvimento de software. Pesquisadores realizam experimentos para verificar as suas propostas sob condições controladas. Portanto, os experimentos são uma categoria importante de estudos empíricos e são a abordagem clássica para identificar relações de causaefeito. O objetivo deste trabalho é caracterizar qualitativa e quantitativamente, e analisar experimentos centrados em humanos em engenharia de software, publicados em três jornais e três conferências de 2003 a 2013. Para atingir este objetivo foi realizado um estudo de mapeamento sistemático que inclui todos os artigos completos publicados no EASE, ESEM, ICSE, ESEJ, JSS, TSE. Com base em pesquisas manuais nessas importantes conferências e periódicos em Engenharia de Software, foram analisados 3671 artigos. 244 estudos primários foram identificados como relevantes, relatando experimentos. Nesses experimentos foram obtidos dados qualitativos e quantificados sobre autores e instituições, participantes, tarefas realizadas, o ambiente, replicação e ameaças à validade. A partir da análise realizada, este trabalho conclui que apesar dos guias existirem agora, há uma grande lacuna no relatório desses experimentos. A principal contribuição deste trabalho é fornecer o status dos relatórios de experimentos centrados em humanos em engenharia de software e como este campo amadureceu. Este trabalho também propõe uma lista de informações que um relatório de experimento deve ter.

Context: Software reuse is considered as the key to a successful software development because of its potential to reduce the time to market, increase quality and reduce costs. This increase in demand made the software organizations to envision the use of software reusable assets which can also help in solving recurring problems. Till now, software reuse is confined to reuse of source code in the name of code scavenging. Now a day, software organizations are extending the concepts of software reuse to other life cycle objects as they realized that reuse of source code alone does not save money. The academia has put forward some assets as reusable and presented methods or approaches for reusing them. Also, for a successful software reuse the organizations should assess the value of reuse and keep track on their reuse programs. The other area which is vital for software reuse is the maintenance. Maintenance of reusable software has direct impact on the cost of the software. In this regard, academia has presented a number of techniques, methods, metrics and models for assessing the value of reuse and for maintaining the reusable software. Objectives: In our thesis, we investigate on the reusable assets and the methods/ approaches that are put forward by the academia for reusing those assets. Also a systematic mapping study is performed to investigate what techniques, methods, models and metrics for assessing the value of reuse and for maintaining the reused software are proposed and we also investigate their validation status as well. Methods: The databases like IEEE Xplore, ACM digital library, Inspec, Springer and Google scholar were used to search for the relevant studies for our systematic mapping study. We followed basic inclusion criteria along with detailed inclusion/exclusion criteria for selecting the appropriate article. Results: Through our systematic mapping study, we could summarize the list of 14 reusable assets along with the approaches/methods for reusing them. Taxonomy for assessing the value of reuse and taxonomy for maintaining the reusable software are presented. We also presented the methods/metrics/models/techniques for measuring reuse to assess its value and for maintaining the reusable software along with their validation status and areas in focus. Conclusion: We conclude that, there is a need for defining a standard set of reusable assets that are commonly accepted by the researchers in the field of software reuse. Most metrics/models/methods/approaches presented for assessing the value of reuse and for maintaining the reuse software are academically validated. Efforts have to be put on industrially validating them using the real data.

Context and background: Requirements engineering(RE) is a first and a very important phase in any software development which helps in building a suitable and customer satisfactory product. In the past few years, the use of Agile software development has become popular in the industry. Customer communication plays an important role in any software development life cycle. Customers state the requirements needed to develop a product in the Requirements Engineering phase. A project is likely to fail due to problems in customer communication during the RE phase. Objective: This thesis aims to study the Customer communication challenges in Agile requirements engineering, prioritize these challenges, and also find out the mitigation strategies to overcome these challenges. Research Method: A systematic mapping study is conducted to find out the customer communication challenges. Based on the data collected from the systematic mapping study, a survey is conducted to find out the mitigation strategies to overcome the customer communication challenges faced in the RE phase and also prioritize these challenges. Results: Based on the data collected from the systematic mapping study, a total of 18 customer communication challenges are identified. In the second step, a survey is conducted based on the identified challenges. The prioritization of these challenges is done by calculating the risk analysis of the challenges from the survey data. And finally, mitigation strategies are mentioned to overcome all the identified 18 challenges.