Research on Project-driven Teaching Mode Based on Software Development Model

Background: The contribution of modeling in software development has been a subject of debates. The proponents of model-driven development argue that a big upfront modeling requires substantial investment, but it will payoff later in the implementation phase in terms of increased productivity and quality. Other software engineers perceive modeling activity as a waste of time and money without any real contribution to the final software product. Considering present advancement of model-based software development in software industry, we are challenged to investigate the real contribution of modeling in software development. Objective: We analyze the impacts of UML modeling, specifically the production of class and sequence diagrams, on the quality of the code, as measured by defect density, and on defect resolution time. Method: Using data of a proprietary system, we conduct post-mortem analyses to test the difference in defect density between software modules that are modeled and not modeled. Similarly, we test the difference in resolution time between defects that are related to modeled and not modeled functionality. Result: We have found that the production of UML class diagrams and sequence diagrams reduces defect density in the code and the time required to fix defects. These results are obtained after controlling for the effects of co-factors such as code coupling and complexity. Conclusion: The results confirm that not only does the production of UML class diagrams and sequence diagrams possibly help improve the quality of software, but also it possibly help increase the productivity in software maintenance.

purpose of research of software development is to attempt to develop lower cost , high reliability, and a variety of software to meet user needs. This paper introduce the advantages and disadvantages of various software development model from software engineering perspective.It proposed use of scientific principles and methods of engineering specifications to guide the development of the software , run and maintain , and trying to organize the work of software development , and then explore a new way to get rid of the software crisis. Keywords-Software, software engineering, software development model

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract Using Programming Projects in an Operating Systems Course as a Capstone Software Engineering Experience Computer Engineering Technology students at the University of Dayton take two fundamental programming courses teaching the basics of algorithmic problem solving along with the VBA and C++ syntaxes. These courses develop a strong programming foundation for the students; however, they lack the ability to introduce software programming within larger software systems. The final course related to software development is a required operating systems course. This course contains three fundamental goals: to develop the students’ understanding of key operating system concepts, to increase the students’ software engineering capabilities, and to introduce the students to the internal workings of the Linux and Windows operating systems. The operating systems course relies heavily on software programming exercises as a key instrument in teaching students the framework and applications of modern operating systems. The unique aspect of this approach is that the programming projects are designed not as standalone activities, but instead as individual components of a larger software system. Therefore, each programming project focuses not just on learning new syntax related to operating system concepts, but also in how these concepts are relevant to the software system being developed. Students develop programs for both the Microsoft Windows and Linux operating systems, working heavily with their associated application programming interfaces and investigating processes, threads, synchronization, input and output, and scheduling issues. A complete course overview and synopsis of the software programming projects will be presented along with student performance and comments from an end of the semester survey. Introduction The Computer Engineering Technology (CET) Program at the University of Dayton (UD) was started in 1999 and included two software programming courses. These courses predominately focused on teaching the fundamentals of software programming and the syntax associated with the VBA and C++ languages. Likewise, to satisfy the ABET outcome requirements for computer engineering technology programs, the ETC Program at UD also required a new 3 credit lecture course entitled “Concepts & Applications of Operating Systems” to be taken during the students’ Junior year of study.1 This course was structured to provide students hands-on exposure to the internal workings of modern operating systems. During the 2004/2005 academic year, the material being taught in the software programming was evaluated. In accordance with the Computing Curricula 2001 (CC2001) report by the Computer Society of the Institute for Electrical and Electronic Engineers (IEEE-CS) and the Association for Computing Machinery (ACM), the two software programming courses being taught fell within the traditional imperative-first approach. This approach starts students off with software programming activities without any real preparations.2 After careful review, it was found that the student population being served needed to be taught the algorithmic thought process prior to the syntax as many of the students had no prior exposure to software programming and were struggling more with defining the problem solutions than with the specific syntax being taught.3 A modified algorithms-first approach from CC2001 report was applied to these courses. Instead

The effectiveness of generative artificial intelligence models in software development is determined not only by their ability to generate correct solutions but also by their adherence to quality metrics and their resilience to exceptional scenarios. In this context, a comparative evaluation was conducted on four models using 10 fundamental algorithm problems and 10 object-oriented programming problems in the C# programming language. The generated solutions were assessed in terms of time complexity, memory usage, lines of code, number of variables and methods, and execution time. In addition, meaningful edge-case scenarios were employed to measure error tolerance and exception handling performance. The findings indicate that all models produced functionally valid solutions, yet exhibited limitations in advanced software engineering practices such as modularity, comprehensive error management, performance measurement, and unit testing. The analysis revealed that ChatGPT and Gemini stood out in terms of structure and consistency, Claude demonstrated greater reliability in handling errors, while Copilot offered advantages in code simplicity. Overall, the results highlight the importance of evaluating generative AI models not only under ideal conditions but also in atypical scenarios to ensure software quality and reliability.

This paper explores different models of software development based on their definition and process. Moreover, the models are connected to the lifecycle of the software project. The different software development models differ based on their approach to the requirements and the end product. The risk associated with each model is one of the distinctive features of each one of them. The study provides a comparison based on the advantages and disadvantages of each development model, which allows researchers and practitioners to make a choice in their research or project.

The Modeling in Software Engineering (MiSE) workshops are a collaboration between the ICSE and MoDELS research communities, with a focus on using models to facilitate software development.

This study focuses on the innovative model of practical courses in Dance Studies majors in universities, guided by core literacy. Through an in-depth analysis of the current state of practical courses in university Dance Studies programs, it is found that traditional teaching models are inadequate in cultivating students' core literacy. Based on this, a series of innovative strategies are proposed, covering the reconstruction of course objectives, optimization of teaching content, innovation of teaching methods, and improvement of the evaluation system. The aim is to construct an innovative model for practical courses that meets the demands of the times and effectively enhances students' core literacy in dance, providing new ideas and references for talent cultivation in university Dance Studies programs.

Computer programming skill is an essential skill for information technology and for some other natural science department students. However, teaching and learning computer programming ideas and skills has been recognized as a great challenge to both teachers and students. Therefore, the development of efficient learning strategies and environments for computer programming courses have become an important concept. This study is intended to recommend strategies for improving academic performance which can be used in teaching computer programming course effectively to undergraduate students in information technology related departments or informatics departments (including information Technology, computer science, and software engineering and information systems This concluded that there is a need for strategies for improving academic performance which requires planning and implementation to strengthen the motivation of the students to study, boost their academic performance, and uplift the quality of education in information technology departments. Finally, relevant and important workable recommendations have been suggested by the researcher.

Welcome to the Empirical Software Engineering’s special issue on predictive models in software engineering. The goal of such methods is repeatable, refutable (and possibly improvable) results in software engineering. Many of the recent papers in SE literature are based on data from on-line repositories such as http://promisedata.googlecode.com. This introduces a kind of selection in the kinds of papers published at this venue. Our first paper pushes past that bias to explore a very rich time-based data set. In “Predicting the Flow of Defect Correction Effort using a Bayesian Network Model”, Schulz et al. use a Bayes net to explore the effects of removing defects at different stages of the software lifecycle. Their work shows how to calibrate general models to the particulars of a company’s local particulars. Our next paper “The Limited Impact of Individual Developer Data on Software Defect Prediction” by Bell et concludes there is no added value to reasoning on some aspects of social aspects of programmer teams working on a code. This is a timely counterpoint to other research that eschews code measures for other approaches based only on social metrics. Our last paper explores the complicated issue of parameter tuning. In “Using Tabu Search to Configure Support Vector Regression for Effort Estimation”, Corazza et al. offers automated guidance for setting the parameters that control a learner. This is a matter of critical importance since even the best learner can perform poorly if its operator uses the wrong settings. A special issue like this is only possible due to the hard work of a dedicated set of authors are reviewers. We would like to express our gratitude to all authors who submitted their papers this special issue. We would also like to thank our reviewers for their meticulous evaluation of the submissions. The success of special issues such as this one largely stands on their shoulders. Empir Software Eng (2013) 18:433–434 DOI 10.1007/s10664-013-9252-1

Putting Requirements and Quality at the Core of Global Service Delivery: Current Efforts and Future Plans at Pace University

This paper proposed a method named "analytical teaching", and completely introduced its teaching characteristics and the implementation methods. Combining computer programming courses, it put forward a specific reformation proposal about the traditional teaching models. At the same time, this paper demonstrates that "analytical teaching" has great significance in developing student's awareness of innovation, ability of innovation and spirit of innovation.

The University of Southern California (USC) teaches a two-semester real-client project course as a core course in USC's MSCS-SE (Master of Science in Computer Science and Software Engineering) degree program. The course has evolved rapidly, each year introducing many changes in order to satisfy the course stakeholder's win conditions. The course has also been our primary experimental testbed for evolving our MBASE (Model-Based Architecting and Software Engineering) model integration framework. In turn, this framework, along with the CRESST (Center for Research on Evaluation, Standards and Student Testing) cognitive demands analysis has served as an effective means of managing the course's rapid evolution. A further test of the framework has been its application to undergraduate software engineering project courses at other institutions. This paper provides a description and examples of USC's experience in constructing and evolving a family of software engineering project courses based on the MBASE software engineering model integration framework. A discussion of course needs, use of software engineering models, a description of MBASE, use of the CRESST model of learning objectives, course development and experiences are presented. The approach has been used successfully at Columbia University and to a lesser degree at other institutions. Much of the current and historical materials and resources described in this paper are freely available for educational use.

Background and Purpose: The teaching objectives of senior vocational education emphasise professional skills training. In information technology and computer studies, computer programming is an extremely important foundation course for its corresponding professions. However, many studies on programming courses have pointed out that computer programming is a difficult subjectto learn; even undergraduates in information technology and computer studies are deterred by it. According to past research, learners' maladaptive cognition and behavior when learning computer programming tend to affect learning achievement. The purpose of this study is to explore the effects of the maladaptive cognition and learners' behavior in computer programming courses on their learning achievement. Methods: For that reason, this study applied a research survey to investigate the relationship between learners' maladaptive cognition and behavior and learning achievement in computer programming courses. The research participants were students in the information management department of technical and vocational schools who had previously taken programming courses. A surface strategy scale and a procrastination scale were adopted as research instruments to measure learners' maladaptive cognition and behaviour, respectively. Results: The results showed that learners' maladaptive cognition in the learning processes of computer programming courses had a significant, positive impact on their maladaptive behaviour and a significant, negative impact on their learning achievement. These findings indicate that learners' maladaptive cognition affects learning processes and effectiveness. For that reason, learners should reduce the incidence of maladaptive cognition during learning activities, so as to effectively lessen its negative impact on learning outcomes. The results of this study could be used as a reference for educators and educational researchers when designing curricula in the field of computer programming.

DevOps is a fine fusion of development and operations teams together to deliver more efficient, reliable and quality software. DevOps make use of alternative set of automation tools for different development stages of software. The research presented in th is paper analyses selective automation tools to provide comprehensive and comparative tabular analysis followed by graphical comparison according to latest Google Trends. Best performer tools out of these alternative tool sets are grouped together into int egrated tool chain (ITC) in order to escalate DevOps performance in future. A hybrid automated model for software development using these selective automation tools from the ITC is also proposed. This analytic comparison will prove to be a big utility for young researchers, students and software developers to be cognizant with DevOps automation cul ture. Study of other tools or enhancement of the proposed hybrid model could also be considered as a part of future research.

Chapter 9 - Domain 8: Software Development Security