ANALYSIS OF REQUIREMENTS VOLATILITY DURING SOFTWARE DEVELOPMENT LIFE CYCLE USING THE SPSS METHOD

Requirements Prioritization (RP) is an attempt to rank the requirements based on the value added to the business. It is a preprocessingstep in software implementation as well as a prevalent need thing to get customer satisfaction, decrease the risk of requirements volatility, develop cost-effective software, and maintain the level of quality in the software system. Many research focusing on prioritizing the requirements using one or several criteria like time, dependency, and scalability. However, all of them concern with sequential prioritization only. To the best of our knowledge no work focused on parallel ranking in prioritization, which permit the simultaneous requirements implementation that reducing the implementation time. In this study we developed a new requirements prioritization for determine the requirements priority level in parallel format using Random Forest classifier based MoSCoW method (RF-MM). When we applied our prioritization model on to (Testcase MIS system with priority) industrial dataset. the total implementation time were equal to 76.0 seconds when ranking in sequential format; whereas the total time were equal to 33 seconds in parallel ranking. Hence, the parallel ranking capable of reducing implementation time to more than half.

Requirements Prioritization (RP) is an attempt to rank the requirements based on the value added to the business. It is a preprocessingstep in software implementation as well as a prevalent need thing to get customer satisfaction, decrease the risk of requirements volatility, develop cost-effective software, and maintain the level of quality in the software system. Many research focusing on prioritizing the requirements using one or several criteria like time, dependency, and scalability. However, all of them concern with sequential prioritization only. To the best of our knowledge no work focused on parallel ranking in prioritization, which permit the simultaneous requirements implementation that reducing the implementation time. In this study we developed a new requirements prioritization for determine the requirements priority level in parallel format using Random Forest classifier based MoSCoW method (RF-MM). When we applied our prioritization model on to (Testcase MIS system with priority) industrial dataset. the total implementation time were equal to 76.0 seconds when ranking in sequential format; whereas the total time were equal to 33 seconds in parallel ranking. Hence, the parallel ranking capable of reducing implementation time to more than half.

One of the main obstacles in software development projects is requirement volatility (RV), which is defined as uncertainty or changes in software requirements during the development process. Therefore, this research tries to understand the underlying factors behind the RV and the best practices to reduce it. The methodology used for this research is based upon qualitative research using interviews with 12 participants with experience in agile software development projects. The participants hailed from Austria, Nigeria, the USA, the Philippines, Armenia, Sri Lanka, Germany, Egypt, Canada, and Turkey and held roles such as project managers, software developers, Scrum Masters, testers, business analysts, and product owners. Our findings based on our empirical data revealed six primary factors that cause RV and three main agile practices that help to mitigate it. Theoretically, this study contributes to the body of knowledge relating to RV management. Practically, this research is expected to aid software development teams in comprehending the reasons behind RV and the best practices to effectively minimize it.

Mastering Requirements Volatility: Strategies for Dynamic Environments and Multiple Stakeholders in Government Software Projects

The success of software development projects is often hindered by time pressure (TP), leading to decreased productivity, compromised quality, and increased risk of failure. To address this issue, it is crucial to understand the key factors contributing to TP in software development projects. In line with the study's objectives, the review methodology followed the Kitchenham and Charters criteria, and a search strategy encompassed four primary digital databases, namely IEEE, ACM Digital Library, Science Direct, and Springers, resulting in 4,500 relevant sources. After applying inclusion and exclusion criteria, a total of 128 papers were selected for analysis. This paper offers a comprehensive overview of the factors contributing to TP in software development. This study synthesizes the findings from multiple studies to guide practitioners in improving their project management approaches and highlights the significance of enhancing various aspects of the development process. The findings highlight the importance of improving project management, estimation techniques, knowledge, and skills to effectively manage TP. Additionally, managing requirements volatility, setting clear goals and objectives, and reducing distractions and interruptions emerge as crucial strategies for mitigating TP and enhancing project success. Furthermore, selecting software developers based on their personality traits is recommended to foster a work environment conducive to reduced TP and improved software development outcomes. By understanding and addressing these factors, software development teams can alleviate TP and increase the likelihood of successful software products. Implementing these recommendations can contribute to reduced TP, improved project outcomes, and enhanced overall success in software development.

Systematic derivation of customized development sprints for an agile development of wind turbines

The current uncertain and volatile business context is challenging firms worldwide, leading to the need to be responsive at a competitive cost. This trend is so substantial that it even affects industries traditionally competing in rather stable contexts, such as the process industry. Although the process industry includes multiple sectors with different technologies and processes, these share several aspects that make the industry as a whole distinctive to the discrete manufacturing industry. Based on a literature review, this study identifies and describes trends leading the process industry to the need for responsiveness, corresponding solutions to accommodate the need, and related challenges hindering the industrialization and diffusion of solutions in this industry. This study shows that trends, such as the uncertainty and volatility of market requirements, are challenging the process industry to develop reconfigurability solutions across multiple production levels. The development of reconfigurability solutions is hindered by modularity, integrability, co-ordination and collaboration challenges.

User requirements are the building blocks for development of software applications. User requirements decide the width and breadth of any software. Nowadays, test scenarios are prepared from the user requirements, which give the test engineers ample scope to review the test plan thoroughly before doing software testing. Regression testing is carried out to know the effect of requirement changes on the functionalities and performance of the software. Test scenario prioritization, which is one of the techniques to perform regression testing, maximizes the ease of debugging for the system under test. The code based test scenario prioritization and model based test scenario prioritization have their own limitations. So, to achieve ease of debugging and to get more time for reviewing the test plans, researchers are now working on test scenario prioritization using requirements collected from the end users. In this paper, we propose an approach named Requirement based test scenario prioritization to prioritize test scenarios using requirements collected from end users for developing software applications. The user’s functional requirements are collected and is assigned with some weight depending upon different factors like complexity of implementing the requirements, type of release of the requirements, requirement volatility, coupling between requirements etc. Test scenarios are generated from requirements collected from the end users. Then, the final priority weight of each test scenario is found out by considering the weight of each requirement covered by the corresponding test scenario and the percentage of requirements coverage made by each test scenario. The test scenarios are prioritized based on the final priority weight. The proposed approach is evaluated using average percentage of fault detection metric and is found to be very efficient in early test scenario prioritization and detection of faults.

Product Line Engineering (PLE) is a crucial practice in many software development environments where software systems are complex and developed for multiple customers with varying needs. At the same time, many development processes are use case-driven and this strongly influences their requirements engineering and system testing practices. In this paper, we propose, apply, and assess an automated system test case classification and prioritization approach specifically targeting system testing in the context of use case-driven development of product families. Our approach provides: (i) automated support to classify, for a new product in a product family, relevant and valid system test cases associated with previous products, and (ii) automated prioritization of system test cases using multiple risk factors such as fault-proneness of requirements and requirements volatility in a product family. Our evaluation was performed in the context of an industrial product family in the automotive domain. Results provide empirical evidence that we propose a practical and beneficial way to classify and prioritize system test cases for industrial product lines.

This study aims to identify the effect of poorly written requirements specifications of software development and its continuous changes; on information systems’ projects success and its influence on time and cost overrun of the project based on empirical understanding in practice. As the world is moving towards the internet of things and due to the dramatic increase in demand on complex information systems projects, the development of information systems became more difficult and handling the customers’ requirements became very challenging. This research follows a conclusive design, Using a descriptive research design was held first to reveal and discover the characteristics of a good requirement, and then a quantitative method was used through conducting questionnaire and distributing to more than 400 participants in the software industry in Egypt, to understand the relationship between variables and how to improve the quality of data based on real world observations or experiment. The data collected was analyzed using python and R analysis techniques. The results indicates that, the organizations with the highest quality of requirements and less requirement volatility, have higher software success rates in terms of Project’s efficiency as well as Business and direct organizational success, while the requirements volume doesn’t have significant effect on success rates. From this analysis we developed an initial model.

Todays market evolution and high volatility of business requirements put an increasing emphasis on the ability for systems to accommodate the changes required by new organizational needs while maintaining security objectives satisfiability. This is all the more true in case of collaboration and interoperability between different organizations and thus between their information systems. Ontology mapping has been used for interoperability and several mapping systems have evolved to support the same. Usual solutions do not take care of security. That is almost all systems do a mapping of ontologies which are unsecured.We have developed a system for mapping secured ontologies using graph similarity concept. Here we give no importance to the strings that describe ontology concepts, properties etc. Because these strings may be encrypted in the secured ontology. Instead we use the pure graphical structure to determine mapping between various concepts of given two secured ontologies. The paper also gives the measure of accuracy of experiment in a tabular form in terms of precision, recall and F-measure.

The paper proposes the methods to construct an interbranch uncertainty chessboard. With the use of real databases, volatility of direct requirements and interbranch flows of uncertainty are computed. Different applications are discussed, among them are general equilibrium, fiscal risk, stability of the national economy, entrepreneurship.

Popularity of mobile phones and huge growing for mobile applications make developers in need for flexible software process, which can deal with many challenges facing the mobile app development process. These challenges include: volatility of requirements, strong user involvement, development time tightness, process simplicity, and production of valuable software in low cost. This research study investigates the current mobile app development approaches adopted in Omani market and provides a comparison between existing methods. The results reveal that Agile approach is the most popular model for mobile software engineering in Omani, as it naturally fits most of the applications required in this market. The study also discusses various agile process models such as Scrum, XP, Lean, DSDM, and others. It is concluded that XP model is the most preferable model used by Omani developers due to its dynamic and adaptive nature for different mobile app processes. The study provides also a series of recommendations for mobile app developers which should help in selecting the most appropriate method that suits the targeted market sector

Abstract Requirements volatility is a major issue in software development, causing problems such as higher defect density, project delays, and cost overruns. Software architecture that guides the overall vision of software product is one of the areas that is greatly affected by requirements volatility. Since critical architecture decisions are made based on the requirements at hand, changes in requirements can result significant changes in architecture. With the wide adoption of agile software development, software architectures are designed to accommodate possible future changes. However, the changes has to be carefully managed as unnecessary and excessive changes can bring negative consequences. An exploratory case study was conducted to study the impact of requirements volatility on software architecture. Fifteen semistructured, thematic interviews were conducted in a European software company. The research revealed poor communication, information distortion, and external dependencies as the main factors that cause requirement volatility and inadequate architecture documentation, inability to trace design rationale, and increased complexity as the main implications of requirements volatility on software architecture. Insights from software teams' awareness of the requirement volatility, factors contribute to it, and possible ways to mitigate its implications will be utilized to improve the management of requirement volatility during software architecting process.

Requirements are found to change in various ways during the course of a project. This can affect the process in widely different manner and extent. Here we present a case study where-in we investigate the impact of requirement volatility pattern on project performance. The project setting described in the case is emulated on a validated system dynamics model representing the waterfall model. The findings indicate deviations in project outcome from the estimated thereby corroborating to previous findings. The results reinforce the applicability of system dynamics approach to analyze project performance under requirement volatility, which is expected to speed up adoption of the same in organizations and in the process contribute to more project successes.

Global software development (GSD) is a modern approach that is currently being adopted by software organisations, mainly because of significant return on investment it produces. In the GSD projects, the development teams operate under the three distributed dimensions: geographical, cultural and temporal distances which increases substantial communication difficulties and becomes the development activities more challenging especially related to requirement volatility. The objective of this study is to identify the relationship between requirements volatility, and GSD project success. We have proposed a GSD risk-based model that consider project performance risk as a mediating variable for analysing the impact of requirement volatility on GSD project success. A questionnaire study was conducted from the 103 GSD experts to validate the proposed model. The findings reveal that requirements volatility increases the project performance risk which has a negative impact on the GSD project success which can be managed by the flexible management.

Agile methods adoption has increased in recent years because of its contribution to the success rate of project development. Nevertheless, the success rate of projects implemented using Agile methods has not completely reached its expected mark, and selecting the appropriate Agile methods is one of the reasons for such lag. Selecting the appropriate Agile methods is a challenging task because there are so many methods to select from. In addition, a lot of organizations consider the selection of Agile methods as a mammoth task. Therefore, to assist Agile team members, this study aimed to investigate how the appropriate Agile methods can be determined for different projects. Based on a Grounded Theory study, 23 Agile experts drawn from 19 teams across thirteen countries were interviewed. Hence, this study employed the Ground Theory of selecting Agile methods. Sixteen factors, grouped into five categories, have been found to affect the selection of twenty Agile methods. The nature of project (size, maturity, criticality and decomposability), development team skills (communication skills, domain knowledge, team technical skills and maturity), project constraints (cost/value/ROI, cost of change, time, scope and requirements volatility), customer involvement (collaboration, commitment and domain knowledge) and organizational culture (type of organizational culture) are the key factors that should guide Agile team members in the selection of an appropriate Agile methods based on the value these factors have for different organizations and/or different projects.

Development of COSYSMO 3.0: An Extended, Unified Cost Estimating Model for Systems Engineering

New Roles of Cost Estimates of Computer Systems (CS) Applied Software (AS) development and usage within CS successful development (modernization) are identified. These roles are Rationales and Means for Decisions coordination concerning CS Value and life cycle (LC) Cost balancing that satisfies all CS stakeholders. To enable these Roles Methods for AS Cost estimating unification is substantiated under CS LC specifics (LC evolutionary models diversity, (non)developmental ready-to-use items usage, CS and AS requirements volatility, their tightening for efficiency, reliability and security). Within the expert-analytical approach for AS Cost Estimation initiated by the authors the unification tool, named as an Information Technology for formalized Cost estimation Problem multiple informed solving over LC with AS expert assessments within their common information environment, is provided. The Technology unifies the authors' techniques for AS development/ annual maintenance Cost evaluating with COCOMO II.2000.4 model and approved methods (universal and special for defense CS) within the author's methodology of Diagnostic Expertise. Technology components are described: open AS and AS LC models Classifiers; mathematical Methods (for expert assessing, AS efforts evaluating, its transforming into cost up to regulations, forming/refining efforts regression models); Methods Applicability to AS Function; Sub-models of AS Cost expert assessing and experts selecting Processes. Elaborated Technology accelerates and cheapens AS Cost estimation due improving its methods based on their results and unifying procedures. It provides all CS and AS LC participants in timely manner with sound, adequately specialized and compatible Cost estimates facilitating Decisions substantiality and informational consistency concerning CS development (modernization) rational processes as well as keeping those processes’ efficiency acceptable for all stakeholders. Problems in programming 2018; 4: 15-29