Software Project Planning Research Articles

Challenges of Integrating Artificial Intelligence in Software Project Planning: A Systematic Literature Review

Artificial intelligence (AI) has helped enhance the management of software development projects through automation, improving efficiency and enabling project professionals to focus on strategic aspects. Despite its advantages, applying AI in software development project management still faces several challenges. Thus, this study investigates key obstacles to applying artificial intelligence in project management, specifically in the project planning phase. This research systematically reviews the existing literature. The review comprises scientific articles published from 2019 to 2024 and, from the inspected records, 17 papers were analyzed in full-text form. In this review, 10 key barriers were reported and categorized based on the Technology–Organization–Environment (TOE) framework. This review showed that eleven articles reported technological challenges, twelve articles identified organizational challenges, and six articles reported environmental challenges. In addition, this review found that there was relatively little interest in the literature on environmental challenges, compared to organizational and technological barriers.

Construction and Validation of Early Software Size Estimation Models Based on ADAF-Adjusted ACD Metrics

Abstract Software size estimation is a vital activity of software project planning and management. Early software size estimation is a challenging task due to the limited information available during the early phases of software development. The goal of this paper is to construct and validate early software size estimation models based on four analysis-to-design adjustment factor (ADAF)-adjusted analysis class diagram metrics (i.e. ADAF-adjusted number of classes, ADAF-adjusted number of attributes, ADAF-adjusted number of methods and ADAF-adjusted number of relationships) using stepwise multiple linear regression and leave-one-out cross-validation. Furthermore, the prediction accuracy of the best-performing proposed model is also compared with the model based on objective class points. The results of this comparison reveal that our proposed method reduces errors significantly (i.e. on average, 16% reduction in mean absolute residual and 24% reduction in mean squared error).

A Critique on Task Allocation Processes in Distributed Agile Software Development

Distributed agile software development is implemented to tackle the increasing competition and changing requirements of the software industry. It inspires the development of emergent software applications and supports user satisfaction with fast delivery to market at low cost. Distributed software development presents a complex distributed team structure of the software industry having various workplaces. Distributed agile software development requires effective and well-organized decisions during task allocation. Task allocation is a challenging activity across the spectrum of committed software developers in a distributed environment. Effective task allocation under the pressure of achieving project objectives is a complex management problem in distributed agile software development. Task allocation process is proposed to support effective task allocation in distributed agile software development. Firstly, we identify different aspects of the task allocation context to explore the basic requirements of decision-making in DASD. Based on the information related to the identified aspects, different types of process activities are defined; those should be fulfilled to support the task allocation decisions. Task allocation process during software project planning requires comprehensive information about various factors that influence decision-making. The proposed task allocation process is evaluated based on the process activities. None of the current state-of-the-art research works focus on an approach for task allocation that completely fulfills all activities related to high-level processes or low-level processes. We fill this gap by identifying, classifying, sequencing, and proposing these activities that can be used to realize a methodical approach for a generic task allocation process in a distributed agile software development setup.

Study of Residential Building Model Using Power Project

Power project is the most preferred software for scheduling by construction experts throughout the world. The paper aims to know about the introduction of BIM fundamentals and to study the workflow of Power project software. The important features of the software (project planning, collaboration, scheduling, tracking and resource management) are studied. The report focuses on the attributes in which is try to explain our experience in a construction project using 4D Elecosoft power project software. The main aim of our project work is to design a G+3 residential building model using power project with 4D power project software. This is helpful in designing and analyzing a construction project using 4D power project which makes the project easier to finish it and mark the delay of the construction and I gained lot of ideas regarding 4D power project software and their purpose in the recent era of construction projects. I have also found how BIM or 4D power project software can make a project easier and earlier.

4D Scheduling and Simulation of a G+3 Residential Building using Power Project

Power project is the most preferred software for scheduling by construction experts throughout the world. The paper aims to know about the introduction of BIM fundamentals and to study the workflow of Power project software. The important features of the software (project planning, collaboration, scheduling, tracking and resource management) are studied. Cost and time together in Power project, analyzing budgeted, planned, and actual costs all against time. As a result, I have prepared a 4D scheduling and simulation for a G+3 residential building using the Powerproject software.

Spectral Clustering Effect in Software Development Effort Estimation

Software development effort estimation is essential for software project planning and management. In this study, we present a spectral clustering algorithm based on symmetric matrixes as an option for data processing. It is expected that constructing an estimation model on more similar data can increase the estimation accuracy. The research methods employ symmetrical data processing and experimentation. Four experimental models based on function point analysis, stepwise regression, spectral clustering, and categorical variables have been conducted. The results indicate that the most advantageous variant is a combination of stepwise regression and spectral clustering. The proposed method provides the most accurate estimates compared to the baseline method and other tested variants.

Residential Building Study Model Using Power Project

Power project is the most preferred software for scheduling by construction experts throughout the world. The paper aims to know about the introduction of BIM fundamentals and to study the workflow of Power project software. The important features of the software (project planning, collaboration, scheduling, tracking and resource management) are studied. The report focuses on the attributes in which is try to explain our experience in a construction project using 4D Elecosoft power project software. The main aim of our project work is to design a G+3 residential building model using power project with 4D power project software. This is helpful in designing and analyzing a construction project using 4D power project which makes the project easier to finish it and mark the delay of the construction and I gained lot of ideas regarding 4D power project software and their purpose in the recent era of construction projects. I have also found how BIM or 4D power project software can make a project easier and earlier.

Using Actors and Use Cases for Software Size Estimation

Software size estimation represents a complex task, which is based on data analysis or on an algorithmic estimation approach. Software size estimation is a nontrivial task, which is important for software project planning and management. In this paper, a new method called Actors and Use Cases Size Estimation is proposed. The new method is based on the number of actors and use cases only. The method is based on stepwise regression and led to a very significant reduction in errors when estimating the size of software systems compared to Use Case Points-based methods. The proposed method is independent of Use Case Points, which allows the elimination of the effect of the inaccurate determination of Use Case Points components, because such components are not used in the proposed method.

Particle Swarm Optimization for Predicting the Development Effort of Software Projects

Software project planning includes as one of its main activities software development effort prediction (SDEP). Effort (measured in person-hours) is useful to budget and bidding the projects. It corresponds to one of the variables most predicted, actually, hundreds of studies on SDEP have been published. Therefore, we propose the application of the Particle Swarm Optimization (PSO) metaheuristic for optimizing the parameters of statistical regression equations (SRE) applied to SDEP. Our proposal incorporates two elements in PSO: the selection of the SDEP model, and the automatic adjustment of its parameters. The prediction accuracy of the SRE optimized through PSO (PSO-SRE) was compared to that of a SRE model. These models were trained and tested using eight data sets of new and enhancement software projects obtained from an international public repository of projects. Results based on statistically significance showed that the PSO-SRE was better than the SRE in six data sets at 99% of confidence, in one data set at 95%, and statistically equal than SRE in the remaining data set. We can conclude that the PSO can be used for optimizing SDEP equations taking into account the type of development, development platform, and programming language type of the projects.

DECISION SUPPORT TECHNOLOGY FOR SPRINT PLANNING

Context. The article describes the relevant planning process of software projects, planning problems and different solutions to these problems basis on use of the Scrum methodology.Objective. The purpose of the work is to develop the technology for solving the sprint planning task in the face of uncertainty and possible risks from software development standpoint.Method. The most used software life cycle models are described. The choice of the Scrum as a widely used representative of agile methodology for software development is justified. An analytical review of the methods for estimation of the complexity of user stories is carried out. The major problems of sprint planning are highlighted. The model of the business process to implement an ITproject by Scrum in the form of an BPMN-diagram has been developed. The algorithm to solve the problem of Sprint Backlog planning with uncertainty has been elaborated. The common process of user stories selection from Product Backlog to Sprint Backlog and ways of solving the possible problems are considered. The task of estimation of labor intensity of user stories and the task of risk evaluation in planning are formalized. The technology of user story selection for Sprint Backlog has been developed. Numerical studies of the decision support technology proposed in the article are carried out. It allows suggesting it as the practical tool during sprint planning. The method of adequacy evaluation of proposed technology is offered. The set of key performance indicators for assessing the team performance is selected. Results. The sprint planning technology was developed, which project managers, product owners and development teams for increasing the effectiveness of decision-making process can use. Conclusions. The conducted experiments have confirmed the importance of the proposed decision support technology and allow recommending it for use in practice for planning of software projects. Scientific novelty is to improve the sprint planning process with the assistance of the proposed technology, which alleviates uncertainty while defining labor intensity of user stories and decreases time spent on decision making.

An Instructional Feedback Technique for Teaching Project Management Tools Aligned With PMBOK

Contribution: An approach is presented to provide contextualized feedback for students using a project management (PM) tool. This approach covers the ten PM knowledge areas, guiding students through the planning of software projects. Background: Because software PM is unfeasible without the support of a PM tool there is a growing demand that these tools be taught in the higher education computer courses. Hence, several approaches already have been proposed to improve this teaching, such as educational PM tools or simulators, which facilitate the application of specific PM techniques and the treatment of their results. Another approach to improve the teaching of PM tools is instructional feedback, but little information is as yet available on how to provide instructional feedback when teaching software PM. Intended Outcomes: Instructional feedback, essential to helping students to learn, is based on an evaluation of their actions and decisions. To take advantage of this instructional approach, this paper proposes an instructional feedback technique to be employed in an instructional unit (IU) teaching PM tools aligned with the project management body of knowledge. Application Design: This technique was evaluated through an experiment carried out in undergraduate computer courses. Control and experiential groups were exposed to the same IU, with only the experiential group using the instructional feedback technique. Findings: The proposed feedback technique contributes to student learning, meeting students’ need for better explanations to acquire a comprehensive understanding of PM theory and its practice.

An Optimal Point is not Enough: The Motivation to Cope with Complex Software Project Planning

The proposed study examines the notion that software project managers do not necessarily choose the optimal Gantt chart while planning a software project. This suboptimal choice is biased by psychological perceptions of complexity, as well as by perceptions of risk level (anxiety). We claim that since the optimal plan is naturally more complex, the perceived complexity of Gantt charts influences project managers’ decisions and, when possible, causes them to avoid it. We assume that a “complexity adjustment” algorithm that would enable project managers to adjust the complexity of the Gantt chart to the required level of complexity will allow the manager to choose from among all relevant possible plans the one that meets project’s constraints, while the structural relationships between plan’ work units are at the level of complexity preferred by the manager (e.g., preference for serial activities over parallel ones). Such “feature” will enable managers to adjust the required level of complexity according to work-related anxiety levels. To assist in defining the research question and the relevant manipulations, a pre-test examined the perceived complexity of different basic relationships between work units (serial vs. parallel) and the perceived level of work-related anxiety.

An Examination of Perceived Ergonomic Workstation Design as a Determinant of Software Project Planning and Execution of a Programmer in India

An Examination of Perceived Ergonomic Workstation Design as a Determinant of Software Project Planning and Execution of a Programmer in India

Building New Tool for Software Project Planning Based on Meta-modeling Concepts and CMMI Meta-Standards

CMMI (Capability Maturity Model Integration) for development is a quality system targeting to improve the software development processes. It allows to measure organization maturity level and to improve its capacity in software development. MDE (Model Driven Engineering) is an approach that aims to automate the use of models in order to build more complex systems The software industry became a vital economic sector that employs a wide range of people. A quality assurance system becomes a real need to ensure the quality of software and to increase abilities of software companies to meet the requirements of customers. The paper aims to use a MDE approach to develop tools supporting any software company to adjust their software development process and then to meet the CMMI goals. this paper suggests a new structure of software development process in several models, and shows how to specify a metamodel for each step of this system. One of the advantages of the approach is very resilient and can support the software process development for several software companies and fit rapidly the changes in their software development process.

Satin bowerbird optimizer: A new optimization algorithm to optimize ANFIS for software development effort estimation

Accurate software development effort estimation is crucial to efficient planning of software projects. Due to complex nature of software projects, development effort estimation has become a challenging issue which must be seriously considered at the early stages of project. Insufficient information and uncertain requirements are the main reasons behind unreliable estimations in this area. Although numerous effort estimation models have been proposed during the last decade, accuracy level is not satisfying enough. This paper presents a new model based on a combination of adaptive neuro-fuzzy inference system (ANFIS) and satin bower bird optimization algorithm (SBO) to reach more accurate software development effort estimations. SBO is a novel optimization algorithm proposed to adjust the components of ANFIS through applying small and reasonable changes in variables. The proposed hybrid model is an optimized neuro-fuzzy based estimation model which is capable of producing accurate estimations in a wide range of software projects. The proposed optimization algorithm is compared against other bio inspired optimization algorithms using 13 standard test functions including unimodal and multimodal functions. Moreover, the proposed hybrid model is evaluated using three real data sets. Results show that the proposed model can significantly improve the performance metrics.

Automatically Modeling Developer Programming Ability and Interest Across Software Communities

Developer profile plays an important role in software project planning, developer recommendation, personnel training, and other tasks. Modeling the ability and interest of developers is its key issue. However, most existing approaches require manual assessment, like 360[Formula: see text] performance evaluation. With the emergence of social networking sites such as StackOverflow and Github, a vast amount of developer information is created on a daily basis. Such personal and social context data has huge potential to support automatic and effective developer ability evaluation and interest mining. In this paper, we propose CPDScorer, a novel approach for modeling and scoring the programming ability and interest of developers through mining heterogeneous information from both community question answering (CQA) sites and open-source software (OSS) communities. CPDScorer analyzes the questions and answers posted in CQA sites, and evaluates the projects submitted in OSS communities to assign expertise scores as well as interest scores to developers, considering both the quantitative and qualitative factors. When profiling developer's ability and interest, a programming term extraction algorithm is also designed based on set covering. We have conducted experiments on StackOverflow and Github to measure the effectiveness of CPDScorer. The results show that our approach is feasible and practical in user programming ability and interest modeling. In particular, the precision of our approach reaches 80%.

Investigating the impact of developer productivity, task interdependence type and communication overhead in a multi-objective optimization approach for software project planning

One of the most important activities in software project planning involves scheduling tasks and assigning them to developers. Project managers must decide who will do what and when in a software project, with the aim of minimizing both its duration and cost. However, project managers often struggle to efficiently allocate developers and schedule tasks in a way that balances these conflicting goals. Furthermore, the different criteria used to select developers could lead to inaccurate estimation of the duration and cost of tasks, resulting in budget overruns, delays, or reduced software quality. This paper proposes an approach that makes use of multi-objective optimization to handle the simultaneous minimization of project cost and duration, taking into account several productivity-related attributes for better estimation of task duration and cost. In particular, we focus on dealing with the non-interchangeable nature of human resources and the different ways in which teams carry out work by considering the relationship between the type of task interdependence and the productivity rate of developers, as well as the communication overhead incurred among developers. The approach is applied to four well-known optimization algorithms, whose performance and scalability are compared using generated software project instances. Additionally, several real-world case studies are explored to help discuss the implications of such approach in the software development industry. The results and observations show positive indications that using a productivity-based multi-objective optimization approach has the potential to provide software project managers with more accurate developer allocation and task scheduling solutions in a more efficient manner.

Correlation of Software Project Plan Element and QCD by unified Structural Modeling

Correlation of Software Project Plan Element and QCD by unified Structural Modeling

제한된 프로젝트 기간을 고려한 품질 기반 소프트웨어 프로젝트 계획 생성 기법

Software project planning includes several processes for estimating the effort required to complete software project tasks, allocating human resources to tasks, and creating a project plan. Because software planning is becoming more complicated as the size of software projects grow, it is difficult for project managers to decide on a reasonable project plan. To help them, many automatic software project planning approaches have been proposed. The approaches all focus on minimizing project duration. But if the plan is simply to minimize the duration, without considering software quality, the plan can harm the eventual software quality. In our research to create a reasonable project plan, we consider software quality as well as duration of the project, by defining a software quality score. The project manager can plan the project to maximize software quality for a specific project duration.

An Optimized Resolution for Software Project Planning with Improved Max?Min Ant System Algorithm

Software Project Management (SPM) is one of the primary factors to software success or failure. SPM has been the bottleneck in software engineering area. We apply an improved Max–Min Ant System algorithm to Software Project Planning to make the appropriate worker-task assignment in a software project so the cost and duration of the project are minimized. Experimental results shows that using this Improved Ant Colony Optimization algorithm can obtain a feasible solution which can help us to get the appropriate PERT Graph and Gantt Chart of the software project, then we can obtain the minimized project duration and cost. So Software project management can been improved.