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BOUNDARY LINES OF FUNCTIONAL AND NON-FUNCTIONAL REQUIREMENTS FOR SMALL SCALE APPLICATIONS The software development is referred as challenging task in various aspects. The first challenge is to understand the nature of the software package itself. As compared to other engineering disciplines, the computer program item isn’t significant and does not fulfill any corporeal laws which makes it depend on great practice instead of a fundamental theory. Disappointment comes when ventures exceed the allotted budget, require extra time or need vital functionality. Investigations has proved that the dynamic reason of project failure is the insufficient dealing with the requirements, the major agenda of the project must be fulfilled accordingly. The first and the foremost need in designing any software system is to develop the basic specifications of the software. Such specifications explain customer requests, where typically customers convey their needs in a natural language or in a written narration of the software system they want. Need of high-quality software specifications is a critical success factor, as any defects in the requirements will have a detrimental impact on the overall development process and result in high costs to fix them. This research basically educates us regarding the characteristics of the functional and nonfunctional requirements, and develops the boundary lines to segregate the requirements for small scale applications. After reviewing the literature critically, a framework is proposed which is able to help in classification of functional and non-functional requirements.
SOFTWARE PROJECT MANAGMENT APPROACH FOR REDUCING RISK IN GLOBAL SOFTWARE DEVELOPMENT PROJECTS Within the last several years, Global Software Development (GSD) has a significant impact on the business and software industries. Many software development companies enjoy the benefits of GSD, including cost reduction, cheap labor, and skilled workers around the clock, but these companies also posed some problems because of GSD. These problems affect the long-term survival of GSD projects. One of the GSD's major problems is communication amongst the various team members of the companies. As a result, the purpose of this research is to determine the communication issues that can affect on GSD and propose a mitigation strategy for the solution of the identified communication issues A systematic literature review (SLR) is carried out to determine communication issues in GSD, and then a mitigation strategy is proposed as a solution to these problems. After that, an online survey is conducted to validate the communication issues that can effect on GSD finds through SLR. Then a focus group conducted to validate the mitigation strategies that can be given for communication issues. The results of our research are to be helpful for GSD based companies in context of communication related issues. Our research is to be fruitful for the researchers that can find the solution of communication related issues in GSD.
IDENTIFICATION AND MITIGATION OF CHALLENGES IN MACROTASK CROWDSOURCING Crowdsourcing has become an evolution in which tasks are outsourced by open call format to large numbers of people to utilize collective intelligence. Macro-tasking crowdsourcing is used to resolve various complexities with different degrees of disintegration, assumes different expert level of knowledge in one or even more fields, and integrates adaptable. Processes for work management involving crowd involvement. Crowdsourcing should identify macro-tasking for tackling more complicated problems. Macro tasks could be defined as complicated multitasking that is often decomposable to micro tasks, though not always. Macrotask crowdsourcing has many advantages in every step of the software development life cycle due to its diversity of crowds, faster problem solving and significant cost savings but at the same time, there are many risks involved. Which affects the success of crowdsourcing in software development life cycle. In this search first of all we will identify all the challenges macrotask crowdsourcing through systematic literature review from the literature and then we will propose the mitigation plan to mitigate the challenges that causes the harm to the macrotask crowdsourcing system and approaches to prevent these challenges achieve goals of software macrotask crowdsourcing. We will use the mixed methodology of systematic literature review, qualitative and quantitative analysis to get our results. Systematic literature review will be used to identify the challenges of macrotask crowdsourcing and then we will confirm it from industry by doing the survey and then we will do the focus group to verify it from the experts. Our results will identify the challenges that causes the harm to software crowdsourcing and the mitigation plan to remove them to achieve the maximum results for macrotask crowdsourcing. Our research will cover the gap of identification of challenges of macrotask crowdsourcing and its mitigation plan to help all the stakeholders in the industry to achieve maximum results in the macrotask crowdsourcing projects. In the future phase we will implement these mitigation strategies in the industry .
THE MARGINALIZING DIFFERENCE AMONG CUSTOMER’S NEEDS AND EXPECTATIONS Software engineering is defined as a process of analyzing, understanding the user requirements, and then designing, constructing, and testing the software product according to user requirements. The requirement elicitation is the foundation and first activity of the software development process. During the elicitation phase, we face several issues related to customer needs and wants. Our research aims to marginalize the customer’s needs and expectations. To identify the gap,we take an example through a literature review. First, we classify the gaps in the literature with support of a systematic literature review(SLR). We identify all high values possible gaps from literature. After that, we survey different software organizations .basically we used a mixed-method methodology to minimize the gaps. The mixed methodology will be used to minimize the gap between customer’s needs and wants. In mixed methodology, we used qualitative analysis and quantitative analysis. The validation takes place under the triangulation process. The triangulation process is based on both qualitative analysis and quantitative analysis. After the triangulation process, we proposed a framework to reduce the gaps between customers' needs and wants. Through framework give all possible high values solutions that are discussed in a different journal paper. We merge all possible high-value solutions in our framework. Our contributions are to minimize the gap between customer’s needs and expectations.
A FRAMEWORK FOR REQUIREMENTS CHANGE MANAGEMENT IN DISTRIBUTED AGILE DEVELOPMENT Requirements engineering (RE) is a salient phase in any software development project. Requirements keep changing in today’s software industry due to increased size and complexities. Therefore, an efficient requirements change management (RCM) process is vital for the success of any project. Distributed software development (DSD) has become a norm now and agile methods are being widely used in DSD to counter changing requirements. Agile methods and DSD, being opposite in nature to each other, present new challenges when they are incorporated together in distributed agile development (DAD). Therefore, an efficient RCM process is the need to today’s software industry. This research study has been conducted to fill this gap by presenting a framework for RCM in DAD. Systematic Literature Review (SLR) has been conducted to identify influencing factors that affect RCM process. Grounded theory is then applied for the analysis to categorize the resultant influencing factors. The resulting categories and the influencing factors for each category have been validated through expert review. After the expert review, a survey is conducted to prioritize the results according to their significance during the RCM process. Finally, a framework has been proposed to conduct the RCM process in DAD based on the prioritized categories and their prioritized influencing factors. The study concludes that RCM is vital for successful DAD projects and the proposed framework provides a systematic and scaled solution to conduct the RCM process in an effective manner. The application of proposed framework at a wider scale in the industry is a potential future work of this research study. Automating the framework is another interesting dimension for the future.
MANAGING HUMAN FACTOR IN PROJECT MANAGEMENT FAILURE The objective of any computer program advancement extend is to convey the program item on time, inside the concurred budget, and with the capabilities anticipated by the client. Shockingly, this objective is seldom accomplished. Understanding human components in program advancement, on the other hand, might offer assistance colossally in coming to this goal contribution. Overview of human coordination challenges that affect software development are presented in this thesis. Everyone wants their project to succeed, but not everyone succeeds. Similarly, because the best-trained managers are not always the most effective, some project managers are regularly more successful than others. Project success and failure are determined by the people who make up the project team. When only one person is involved in a project, it is simple, but when working on a long-term project, scientific principles and methods for software development are required, more people will be involved that straight away leads to project failure as Software failures are caused due to bugs, ambiguities, oversights and is interpretation of software projects. In this research thesis the failures caused by human factor, identifying all the human factor and then managing human factor by identifying gaps and giving mitigation guidelines will be identified. Failure in software project management has also been highlighted as being dependent on team makeup, team communication, and management team role.
IMPACT OF TEAM WISDOM ON SUCCESSFUL COMPLETION OF SOFTWARE PROJECTS IN GLOBAL SOFTWARE DEVELOPMENT Global Software Development (GSD) becomes more popular due to the involvement of diverse team members around the world. This diversity creates huge impact on successful completion of GSD projects. Team wisdom in GSD works best to assess the impact of this diverseness. Team wisdom can be conceptualized as multifaceted process to measure the knowledge stock of team members. It is also helpful to utilize that knowledge in decision making of GSD projects. A lot of research has been done in the context of team wisdom but there is lack of research on how team wisdom mechanisms effects successful completion of GSD projects. The aim of this study is to identify the software team wisdom mechanisms and their impact on successful completion of GSD projects. Systematic Literature Review (SLR) was conducted to identify team wisdom mechanisms. 31 out of 564 studies were selected for SLR. A detailed review of these studies was performed by following SLR protocols. Extracted results were analyzed by frequency analysis process. Team wisdom mechanisms: team networking, team diversity, team experience, team prudence, professional ethics and joint-epistemic actions were identified from the literature. Team experience, team networking and team diversity got the highest frequency from SLR. To find the impact of identified team wisdom mechanisms on successful completion of GSD projects, an interview approach was used. Semi structured interviews of eight GSD experts were conducted. Interview transcripts were analyzed by thematic analysis. Team experience and team networking were identified as the most effective team wisdom mechanisms in GSD context. Team diversity, team prudence and joint epistemic actions were considered to be the effective and professional ethics was defined as moderate team wisdom mechanism in GSD. Furthermore, the results of thematic analysis were validated through member checking process. GSD experts found these team wisdom mechanisms helpful in successful completion of software projects in global software development.
MACHINE LEARNING BASED STUDENT GRADE PERFORMANCE ANALYSIS Machine learning algorithms may be able to address the growing difficulty of integrating student-related data for the prediction of student performance in order to make better administrative decisions. Machine learning reviews data mining techniques and provides various models to predict students' performance. The study aims to identify the factors that can improve the students’ performance using machine learning techniques. Machine learning involves various features, and it needs statistical and classification algorithms for better prediction. This study indicates the key factors and predicts student performance with better accuracy based on identified factors. Currently, different studies are using various machine learning techniques to predict students' performance. This research presents a paradigm for evaluating academic achievement in students. In this research, the dataset is carefully chosen which includes demographics, previous academic records, and information related to family background. The data was collected from students of various universities. Due COVID-19, the data was collected through online questionnaires and twenty-four different attributes were selected which were taken from different previous studies after being pre-processed. The study is designed to determine the key attributes influencing the students' performance. Another important part of predication is based on different classifiers having various classification algorithms. The result of this study show that the Support Vector Machine is better than various other algorithms. As a result of this study, student’s performance can be improved by working on the specific features which can improve the quality of education. Furthermore CNN can be used to improve accuracy by collecting more data which can help for better utilization of school systems.
REQUIREMENT ENGINEERING PROCESS FOR MOBILE APPLICATION DEVELOPMENT: CHALLENGES AND RESOLUTIONS Due to the extensive usage of smartphones, more and more development firms are investing in mobile app development to leverage the growing demand. With this ongoing demand for mobile development, the presence and importance of web applications cannot be denied. Although both mobile and web development have pros and cons. Talking about the advancement in technologies, mobile applications are on top priority. But, it is still questionable what are and what type of challenges do the mobile developers face during the execution of the requirement engineering process while developing software applications for mobile platforms. So, for this purpose, research is conducted based on the entire software requirement engineering process that is determining the challenges for the execution of the entire requirement engineering process focusing the mobile development. The research has adopted the Systematic Literature Review for investigating the challenges, then an Expert Review is piloted for the validation of the list of challenges. Finally, an Industrial survey for the proposal of mitigating the challenges is accompanied. As a contribution to the research study, a validated and finalized list of 46 Challenges along with their Resolution Strategies is presented. This research may guide the practitioners and academicians towards the Requirement Engineering Process for Mobile Application Development.
COMMUNICATION MEDIUM CHALLENGES AND SOLUTIONS TOWARDS AGILE IN GSD The process of developing software projects while having interactions of different organizations, people and technology across international boundaries, national cultures and languages is known as Global software development. GSD team members having various cultures and times zones are located at various positions. GSD is used at large scale in software industry as it provides many benefits but there are number of communication medium challenges that are being faced by global team members. There is need to identify those communication medium challenges with their solutions for effective communication across different sites This research work adopts Systematic Literature Review approach to report the communication medium challenges and Industrial survey approach to find out the solution of purposed challenges. The findings of this study reported 11 challenges. The purposed solutions of 11 mentioned challenges are also discussed in this research work. The results of this research work are expected to help researchers to understand communication medium challenges of agile in GSD and to understand the solutions for resolving these challenges.
An Industry Survey of Demotivators for Scaling Up Agile Methodology Traditional software development approaches advocate heavy upfront planning, extensive documentation and reluctance to change adoption. These characteristics attributed to the failure of many software development projects in the past. Eventually, agile software development approach evolved that changed many of the aspects of traditional software development such as flexible planning, light documentation, change embracing approach. These approaches yielded better results when applied to the small-scale software projects but challenges were encountered when agile approaches were applied to large scale software projects. This research study aims to seek the opinion of the industry practitioners regarding the demotivators faced while scaling agile methodologies as mentioned in the literature. Questionnaire survey has been adopted as the research methodology due to its aptness in this research study. 143 survey respondents have contributed their valuable opinions for data collection in this research study. To map the industry survey findings with the literature survey, a comparison has been made between the top ranked demotivators from literature and industry survey. Statistical data analysis reveals a high degree of consistency between the findings of literature review and the opinion of large-scale agile software practitioners. Moreover, the best practices to address the demotivators have also been discussed at length.
ROLE OF DATA MINING IN MEDICAL HEALTHCARE Data mining (DM) is a progressive field that helps in finding useful and meaningful information from large data. It aids to determine knowledge and patterns from complex data. Health data needs various investigative procedures in identifying vital information that is used for decisionmaking. In healthcare, organization’s data is mostly stored in digital format all over the world. Enhancement is always an important feature to examine. In the medical healthcare field, various researchers are interested to contribute accordingly. The data of medical healthcare exists but it needs more attention by applying DM techniques and sort in a more compatible form of knowledge. However, the lack of a comprehensive and systematic narrative encourages for bearing a systematic literature review (SLR) on this topic. This research aims to find updated knowledge of DM and machine learning (ML) techniques in medical healthcare. The comparison is prepared based on three different methods which include quantitative-based, image-based, and signals-based. In this study, SLRs focus on the published literature of a specific research field by the findings of all relevant studies that address a set of research questions while being objective, systematic, clear, and replicable. Firstly, this study answers the current status of DM, ML, and their algorithms. Secondly, three different methods are compared and propose a framework to help the data analysts and data science experts to know about the suitable DM, ML techniques, and methods for medical healthcare.
AN EMPIRICAL STUDY ABOUT POSITIVE IMPLICATIONS OF REQUIREMENTS VOLATILITY ON THE SOFTWARE ARCHITECTURE Requirement volatility is a fundamental activity that occurs throughout the software development life cycle. But, nowadays, it is becoming a striking reason for software project failures, such as software defects and resource management issues, especially in the context of the software architecture. A software architecture that indicates the complete vision of the upcoming system is one of the major areas that could be adversely affected by the requirements volatility. This phenomenon indicated the close connection and equal worth of both these twin peaks of the Software Development Life Cycle (SDLC) i.e. ‘requirement volatility’ and ‘software architecture’. Moreover, modern software development models are fragile, wherein, the software architectures must be designed flexibly to accommodate future changes. However, the fragile nature of requirement volatility indicated their positive activity, and nor does it means an uncontrolled state of existence. Nevertheless, it is a challenging activity but it could be achieved through sound knowledge. For implementation, this study adopted a systematic literature review to identify the list of factors related to the software architecture which are also validated by the experts of the domain. In the end, an industrial survey was conducted to propose the positive implications of identified factors on software architecture. Accordingly, this study contributed a refined and validated list of 27 factors along with their positive implications. Moreover, this study revealed that communication issues and dependencies are the main factors that are causing requirement volatility and factors related to architecture i.e. traceability, design implementations, documentation, and architectural complexity having major implications on the software architecture. Accordingly, to better assist in the development process, the practitioners or developers must have to consider these factors to deal with the upcoming changes more, effectively.
PAKISTAN GRAM PRODUCTION FORECASTING USING BAYESIAN TIME SERIES MODELING The Bayesian approach/statistics, is a statistical decision approach that provides a tool for combining prior probabilities and their distribution about the nature of states. It provides tool to the people to modernize their views in the indication of fresh improved record or data. When working with such issue along time series models is that they too fit commonly when estimating models have large numbers of attributes above somewhat short length/time periods. In our case, this is not such a problem but possibly be when eyeing many attributes, these are common quite in economic prediction. One explanation to over fit problem is using a Bayesian approach, which opens a way to enforce specific priors on attributes. The aim of this thesis is to forecast the production of Gram, which include different attributes like gram cultivation area, production of Gram, the yield of a gram, the cost and prices of gram. For time collection or series data, ARIMA based state space modeling is used to forecast different future attributes of rabbi food crops of Pakistan including gram.