Risk factors in software development projects: a systematic literature review

Menezes, Júlio; Gusmão, Cristine; Moura, Hermano Perrelli de

doi:10.1007/s11219-018-9427-5

Cited by 31 publications

(20 citation statements)

References 36 publications

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“…2 Odzaly et al [69] A prototype tool for agile risk management, within the context of agile projects; it makes use of software agents to support risk identification, evaluation, and monitoring [69]. 3 RisCal [70] This is a generic tool that supports all the risk estimation activities. The activities in this estimation are risk identification, risk analysis, and risk prioritisation.…”

Section: Limitations Of This Studymentioning

confidence: 99%

“…Risks can lead to organizations' making losses which may have to do with product quality, increased production costs, length of time taken to complete a project, meeting deadlines for the project, and so on [2]. Correct identification and tracking of the different risk factors will therefore help to enhance project success rate and achieve quality software [3]. If the former activities are not carried out, that may in the long term lead to software development firms having a smaller share of the market [2].…”

Section: Introductionmentioning

confidence: 99%

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Risk management in the software life cycle: A systematic literature review

Masso

Pino

Pardo

et al. 2020

Computer Standards & Interfaces

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Risk management (RM) plays a key role in project management, as it allows identification and prompt management of threats that may arise during project execution. Furthermore, project management within the software industry is evolving rapidly nowadays, a fact that implies new challenges, because the emergence and use of fresh approaches has brought a greater degree of complexity to the RM process. The objective of this paper is to carry out a systematic literature review (SLR) in the field of software risk, in an attempt to characterize and present the state of the art of this field, identifying gaps and opportunities for further research. From the analysis of the results of this SLR it could be observed that interest on the part of the scientific community has turned away from the definition of research work that addressed an integrated risk management process, to pay attention to work that concentrates on specific activities of this process. It was also possible to see that there is a clear lack of scientific rigour as regards the process of validation in the different studies, and a deficiency in the use of standards or of de facto models to define these.

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Section: Limitations Of This Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk management in the software life cycle: A systematic literature review

Masso

Pino

Pardo

et al. 2020

Computer Standards & Interfaces

View full text Add to dashboard Cite

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“…They analyzed the relationships between risk dimensions and overall project performance. More recently, Menezes et al [65] identified 148 risk factors through a systematic literature review and classified them according to the SEI Taxonomy [52]. Related research [66]- [68] has also been done in using statistical analysis for evaluating risk factors in software projects.…”

Section: Software Project Risk Factorsmentioning

confidence: 99%

Factors Affecting On-Time Delivery in Large-Scale Agile Software Development

Kula

Greuter²,

Deursen

et al. 2022

IIEEE Trans. Software Eng.

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Late delivery of software projects and cost overruns have been common problems in the software industry for decades. Both problems are manifestations of deficiencies in effort estimation during project planning. With software projects being complex socio-technical systems, a large pool of factors can affect effort estimation and on-time delivery. To identify the most relevant factors and their interactions affecting schedule deviations in large-scale agile software development, we conducted a mixed-methods case study at ING: two rounds of surveys revealed a multitude of organizational, people, process, project and technical factors which were then quantified and statistically modeled using software repository data from 185 teams. We find that factors such as requirements refinement, task dependencies, organizational alignment and organizational politics are perceived to have the greatest impact on on-time delivery, whereas proxy measures such as project size, number of dependencies, historical delivery performance and team familiarity can help explain a large degree of schedule deviations. We also discover hierarchical interactions among factors: organizational factors are perceived to interact with people factors, which in turn impact technical factors. We compose our findings in the form of a conceptual framework representing influential factors and their relationships to on-time delivery. Our results can help practitioners identify and manage delay risks in agile settings, can inform the design of automated tools to predict schedule overruns and can contribute towards the development of a relational theory of software project management.

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“…A key challenge against successful software engineering is the early prediction of project failure. Unclear project goals, poor teamwork communication, imprecise project requirements, and many other factors may contribute to project failure [21]. Despite there is a fair number of studies exploring project failure analysis and prediction from the industrial perspective [22,23].…”

Section: Introductionmentioning

confidence: 99%

“…Dhir et al [20] investigated success and failure factors among academic software engineering projects, focusing on the agile approach of software development. In [21], authors found that poor establishment of requirements in addition to technical skills shortage are the critical risk factors behind software engineering project failure. Research efforts in [45] advise an automated approach for source code assessment leveraging long short-term memory (LSTM) neural network.…”

Section: Introductionmentioning

confidence: 99%

Teamwork Distribution: Local vs. Global Software Engineering Project Development Teamwork

AL-Taharwa

2020

Int. J. Emerg. Technol. Learn.

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Deliverable and course project become the preferred mean to measure learner competency and attainment of intended learning outcomes in IT-fields. Proper setup and evaluation for teamwork projects remains a key challenge for e-learning systems. This study investigates the possibility to improve the early prediction of academic software engineering project failure by treating teamwork differently according to the distribution of teamwork participants. Two configurations of teamwork distribution are considered. In the first configuration, a teamwork may include international participants, but all team participants are affiliated to the same institution, namely local teamwork. In the second configuration, a teamwork may include participants from different institutions, namely global teamwork. Software engineering projects are approached from two distinct perspectives. First, obeying the best practices during the system development life cycle (SDLC), namely, process perspective. Second, characteristics of the final deliverable deployed at each milestone of the SDLC, namely product perspective. A publicly released dataset collected by a designated e-learning environment is leveraged to validate the proposed approach. Results indicate a noticeable variance among local and global distributions. These results puts evidence that the reasons behind software engineering teamwork project failures may vary depending on the distribution of the teamwork, local vs. global. Consequently, it advise to customize e-learning systems differently according to the teamwork distribution.

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Risk factors in software development projects: a systematic literature review

Cited by 31 publications

References 36 publications

Risk management in the software life cycle: A systematic literature review

Risk management in the software life cycle: A systematic literature review

Factors Affecting On-Time Delivery in Large-Scale Agile Software Development

Teamwork Distribution: Local vs. Global Software Engineering Project Development Teamwork

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