REQUIREMENT PRIORITIZATION IN THE DEVELOPMENT OF SOFTWARE PROJECTS FOR CRITICAL INFRASTRUCTURE OBJECTS

Requirement prioritization is very useful for making decisions about product plan but most of the time it is ignored. In many cases it seems that the product hardly attains its principal objectives due to improper prioritization. Increased emphasis on requirement prioritization and highly dynamic requirements makes management of composite services time consuming and difficult task. When software project has rigid timelines, limited resources, but high client expectations, an instantaneous deployment of most vital and critical features becomes mandatory. The problem can be solved by prioritizing the requirements. Over the past years, various techniques for requirement prioritization are presented by a variety of researchers in software engineering domain. The proposed Adaptive Fuzzy Hierarchical Cumulative Voting (AFHCV) uses adaptive mechanism with existing Fuzzy Hierarchical Cumulative Voting (FHCV) technique, in order to increase the coverage of events that can occur at runtime. The adaptive mechanism includes Addition of new requirement set, Analysis and Reallocation of requirements, Assignment and Alteration of priorities and Re-prioritization. The re-prioritization is used to improve the results of proposed AFHCV. The proposed system compares the results of proposed AFHCV technique to the existing FHCV technique and the comparison shows the proposed AFHCV yields better results than FHCV.

Requirements prioritization (RP) is a crucial process which aims to evaluate candidate software requirements to be implemented in the next release of a software system. RP is often applied iteratively, according to various criteria, by multiple stakeholders, who may have different roles and needs. The problems encountered during the RP of large sets of requirements can be addressed by following a systematic large-scale decision-making (LSDM) process. The aim of this chapter is to propose an LSDM RP process which applies multi-criteria evaluation based on intuitionistic fuzzy sets (IFSs). IFSs are suitable to consider stakeholders hesitation for criteria importance and requirements ratings. The proposed process is supported by a recommender system which provides suggestions to stakeholders and also guide them to collaboratively reach consensus for the final RP. The proposed process is tested using an illustrative example. The results are promising since they demonstrate that the suggested process can effectively support multiple stakeholders to prioritize large requirements sets.

Traditional methods for requirements prioritization (RP) are currently limited by scalability and lack of automation issues. In recent years, there has been an exponential growth in the use of Artificial Intelligence (AI) techniques in different areas of software engineering (e.g., requirements analysis, testing, maintenance). In particular, I have found thirteen RP methods applying AI techniques such as machine learning, or genetic algorithms. 38% of these approaches seek to improve the scalability problem, whereas only 15% of them aim to improve the automation aspect along the RP process. Moreover, all these studies have carried out their evaluations with a number of requirements no greater than 100.In order to address the issues of scalability and lack of automation in RP, the present research project aims to propose a semi-automatic multiple-criteria prioritization method for functional and non-functional requirements of software projects developed within the Software Product-Lines paradigm. The proposed RP method will be based on the combination of Natural Language Processing techniques and Machine Learning algorithms, and for its validation, empirical studies will be carried out with real web-based geographic information systems (GIS). This paper describes the problem and technical challenges to be addressed, the related works, as well as the main contributions of the proposed solution.

Requirement prioritization is one of the most important approach in the process of requirement engineering due to use it in order to prioritize the execution sort of requirements with taking into account the viewpoints of stakeholders. Thus, in this study, grey wolf optimization (GWO) algorithm is applied in order to prioritize the requirements of a software project. GWO imitates the hunting behavior of grey wolves in nature. Which distinct from others that it has dominant leadership hierarchy which contains four main types; alpha, beta delta and omega wolves. In this paper, a proposed algorithm is presented to prioritize the requirements into ordered list. Furthermore, it is compared and evaluated with analytical hierarchy process (AHP) technique in terms of average running time and dataset size. The findings display that the RP-GWO performs better than AHP mechanism by approximately (30%).

Among critical stakeholders of software projects developed in public institutions are software developers and project managers affiliated to sub-contractor companies, who are working onsite at the public institutions. The aim of this study is to determine the effect of working onsite in public software projects for software developers and managers with respect to selected factors. The research is designed as an exploratory and qualitative study. The study participants were 10 software developers, one technical team leader and four project managers, all having long experiences in working on public software projects on client premises. Semi-structured interview technique is employed as the data collection method and “ analysis” was applied on the obtained participant responses. Following this analysis, “key ” approach was used to identify the issues to be further considered. It has been determined that the productivity of software developers working onsite at public institutions is low due to intense requests, shortened time to fulfill these requests, and long duration of authorization processes. Moreover, a finding of the study is that the quality of the developed projects and the motivation of the developers are considered to be low for the same aforementioned reasons. Among the foremost causes for these results are the fact that employees work under two different hierarchical structures one in the public institution and one in the software company, more than one managers assign work and there is an authority confusion between organizational units and people in the public institutions.

As one of the gatekeepers of quality software systems, requirements’ prioritization (RP) is often used to select the most important requirements as perceived by system stakeholders. To date, many RP techniques that adopt various approaches have been proposed in the literature. To identify the strengths, opportunities, and limitations of these existing approaches, this paper studied and analyzed the RP field in terms of its significance in the software development process based on the standard review guidelines by Kitchenham. By a rigorous study selection strategy, 122 relevant studies were selected to address the defined research questions. Findings indicated that RP plays a vital role in ensuring the development of a quality system with defined constraints. The stakeholders involved in RP were reported, and new categories of the participating stakeholders were proposed. Additionally, 108 RP techniques were identified and analyzed with respect to their benefits, prioritization criteria, size of requirements, types in terms of automation level, and their limitations; 84 prioritization criteria were disclosed with their frequency usages in prioritizing the requirements. The study revealed that the existing techniques suffer from serious limitations in terms of scalability, the lack of quantification, and the prioritization of the participating stakeholders, time consumption, requirement interdependences, and the need for highly professional human intervention. These findings are useful for researchers and practitioners in improving the current state of the art and state of practices.

This paper reports on the user centered, formative evaluation of tools and the validation of models for the analysis of historical textbooks in the context of the digital history project Children and their World . The goal of the project is to create methods for computer‐supported, interactive analysis that can be applied to a large corpus of historical textbooks on history and geography (∼5000 volumes). A first version of a tool for text analysis has been created based on a user centered design process, including a contextual study on current work practices of historians, participative design workshops, and the prioritization of requirements with the project stakeholders. In addition, several generations of text models used in these tools have been iteratively evaluated by the historians in the project. In the context of a cooperative validation study, researchers have used these tools to examine existing hypotheses from the field. The method enables the validation of text models regarding established knowledge, provides additional insights into the requirements for tools and visualizations, and helps to strengthen the expert users' trust in the tools. Based on the findings, this paper proposes four principles for the analysis of a corpus of historical texts. Moreover, the methods presented are discussed regarding the application of user centered design in the context of digital humanities projects.

Requirements prioritization is a critical activity during the early software development process, which produces a set of key requirements to implement. The prioritization process offers a parity among the requirements based on multiple characteristics, including end-users’ preferences, cost to implement, and technical dependencies. This paper presents an interactive method to requirements prioritization that leverages the pairwise comparisons and a constraint solver. Our method employs an interactive accumulation of knowledge from the requirements analyst when the relative priority among the requirements cannot be determined based on the existing knowledge from the requirements documents. The final ranking of the requirements is produced via the constraint solver and interactive pairwise comparisons. We evaluate the proposed method using the requirements from a real healthcare project. The proposed prioritization method relying on a constraint solver outperforms state-of-the-art interactive prioritization methods in terms of effectiveness and robustness to analyst’s errors.

Most software projects have more candidate requirements than can be realised within the time and cost constraints. This paper presents a novel multi-criteria decision analysis process to prioritise requirements. The novelty of the presented idea is three-fold. Firstly, to prioritise requirements, it distinguishes two categories of requirements according to their level of abstraction: low-level requirements and high-level requirements. Then, it relates business goals to the requirements of low-level which contribute to their fulfilment. This will improve the completeness and traceability of requirements. Secondly, requirements prioritisation is based on their degree of contribution to the identified business goals and their importance. So, business goals become the evaluation criteria. Finally, this process takes into account relationships and dependencies that may exist between business goals. At this end, we employ analytic hierarchy process (AHP) method to give weights to business goals and Choquet integral to calculate a global score, i.e. priority, for requirements.

Requirement engineering is one of the most significant phases of software engineering. Success or failure of any software project relies heavily on better requirement engineering process. Better awareness of the requirements is fundamental for requirements engineering. Requirement Prioritization is an important component of requirement engineering process. In this paper, we have highlighted some serious shortcomings related to existing requirement prioritization techniques. Based on these findings, we have proposed an intelligent fuzzy logic based technique for requirements prioritization based on the perceived value of each requirement. We have also proposed a framework for evaluation of existing as well as proposed requirement prioritization techniques.

With the expansion of the scale of software projects and the number of users, excessive software requirements are repeating and overlapping one another. It is getting more fundamental and important to sort the requirements according to their priority using the technologies of software requirements prioritization for costs saving and demands satisfying. This paper analyzed the merits and demerits of the technologies of software requirements prioritization based on sorting and searching, summarized and discussed some important problems demanding prompt solution, related to requirements clustering and redundancy elimination, customers clustering and requirements prioritization based on customer groups, the management of the dependencies between requirements.

Background: Requirement prioritization plays key role in software development process. It is essential to prioritize the requirements for making the correct decision for either a single or multiple release of a product. In this paper we performed a systematic analysis on some of the significant factors like importance of requirements, risks, cost and time in context of requirement prioritization. Objective: With benefits these prioritization methods also have some limitations and shortcoming that are brought up in this paper. Stakeholders, managers, developers or their representatives make decisions for prioritization of requirements. Many techniques are analyzed how to manage these prioritizations considering general goals and limitations. Method: For the identification and analyzing of research articles published during 2009-2017, Systematic Literature Review based method is used in this paper. Results: In recent researches 40 different requirement prioritizations techniques has been used. This SLR also shows the major research gaps regarding techniques and tools for software requirements prioritization. Conclusion: This research shows the major prioritization techniques and tools for requirements elicitation. Tools & techniques identified in this study will assist future researchers to expend their views in the context. Moreover, it will help requirement engineers and practitioners to choose requirement prioritization techniques and tools according to their needs.

The technical debt metaphor is increasingly being used to describe the effect of delaying certain software maintenance tasks on software projects. Practitioners understand intuitively how technical debt can turn into a serious problem if it is left unattended. However, it remains unknown how serious the problem is and whether explicit measurement and management of technical debt is useful. In this paper, we explore the effect of technical debt by tracking a single delayed maintenance task in a real software project throughout its lifecycle and simulate how explicit technical debt management might have changed project outcomes. The results from this study demonstrate how and to what extent technical debt affects software projects. The study also sheds light on the research methodologies that can be used to investigate the technical debt management problem.

PurposeThe purpose of this paper is to construct a two-stage risk management framework for international construction projects based on the meta-network analysis (MNA) approach. A plethora of international construction studies seems to assume risks as independent and therefore, risk intervention strategies are usually critiqued as ineffective.Design/methodology/approachIn the risk assessment stage, a multi-tiered risk network structure was developed with the project objectives, risk events, risk factors and stakeholders, and critical risk factors were selected based on a series of calculations. In the risk intervention stage, targeted risk intervention strategies were proposed for stakeholders based on the results of the first stage. A highway construction project in Eastern Europe was selected as a case study.FindingsThe results showed that 17 risk factors in three categories – external, stakeholder-related and internal – are critical, and the project manager, construction management department, supplier and contract department are the most critical stakeholders that affect the entire project performance. Based on the critical risk factors and project stakeholders, targeted risk intervention strategies were proposed. The risk assessment results of MNA were found to be more reliable and consistent with the project conditions than the risk matrix method; the risk intervention strategies of MNA can effectively address project objectives.Originality/valueThis study modeled risk priorities based on risk associations and put forward a new method for risk management, supplementing the body of knowledge of international construction. The results of this study are of critical importance in management practices.

Machine learning based success prediction for crowdsourcing software projects