Key Artefacts in the Initial Phases of IT Project Management:

Systematic Mapping Study

Oksana Nikiforova

, Kristaps Babris

, Megija Krista Miļūne

, Navyasri Tanguturi

and Óscar Pastor

Riga Technical University, Riga, Latvia

Universitat Politècnica de València, Valencia, Spain

Keywords: IT Project Artefacts (Artifacts), IT Project Management, IT Project Initiating, IT Project Planning, Systematic

Mapping Study.

Abstract: Mistakes made during the initial phases of an IT project are often critical as they can have cascading effect

that impact every following phase of the project, especially implementation. These mistakes can lead to

increased costs, delays and potential project failure. The initial phases of IT project, such as planning,

requirements gathering, and design, set the foundation for the entire project defining project objectives,

requirements and scope and setting the direction for the entire project. The paper demonstrates the results of

the systematic mapping study performed on the definition of the types of artefacts created during IT project

management before the implementation, as it lays the foundation for effective project planning, avoiding

common pitfalls and ensuring alignment with industry best practices.

1 INTRODUCTION

Projects in the field of IT are organized into unique

development phases. These phases assist teams from

the starting point to finish, guaranteeing that

complicated solutions are delivered successfully

(Helmlinger, 2023). Usually these stages have

initiation, planning, execution, monitoring and

closure as their parts - each plays a vital role in

maintaining concentration and gaining desired

results. The beginning stages where specifically the

initiation phase comes first followed by planning

stage hold much importance because they state

project goals and budgetary funds while assigning

resources properly thus offering an understandable

guide for teams (Omonije, 2024). Activities that

involve multiple functions like quality checking and

communication become crucial to fill spaces between

teams and make sure they align with project

objectives. The responsibility of overseeing these

tasks falls upon project managers who balance

https://orcid.org/0000-0001-7983-3088

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https://orcid.org/0000-0002-1320-8471

technical needs against monetary limits and time

factors to keep forward movement.

Recently, the COVID-19 pandemic has

transformed company working styles. The "agile-

style work environment" factor highlights the

importance of conveying information efficiently and

effectively using appropriate methods and tools in a

remote setting (Binboga and Gumussoy, 2024).

Studying prior research and established

frameworks like PMBOK (Project Management

Institute, 2013), PRINCE2 (Simonaitis et al., 2023),

or Agile (Agile manifesto 2001) methodologies

provides access to best practices and standards for

project management artefacts. By aligning with these

practices, the project can meet industry standards and

ensure consistency in documentation quality. This

insight ensures that necessary documents are

prepared at each phase, supporting both compliance

and project coherence. A literature survey performed

on understanding project documentation needs

reveals the variety of artefacts typically required,

Nikiforova, O., Babris, K., Mil¸

une, M. K., Tanguturi, N. and Pastor, Ó.

Key Artefacts in the Initial Phases of IT Project Management: Systematic Mapping Study.

DOI: 10.5220/0013471000003928

In Proceedings of the 20th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2025), pages 773-781

ISBN: 978-989-758-742-9; ISSN: 2184-4895

773

such as project charters, requirement specifications,

design documents, risk assessments, and testing

plans. It helps to set clear expectations for

documentation, making sure that important artefacts

aren’t overlooked, which could otherwise cause gaps

in requirements, design, or quality.

Studying industry best practices can help IT

managers to understand how other successful projects

have approached artefact creation and can provide

templates or guidelines that streamline work and

reduce project ambiguity. Many artefacts (such as

risk logs, compliance checklists, and quality

assurance plans) play a crucial role in risk

management and regulatory compliance (Schön et al,

2020). By understanding these through a literature

survey, project teams can proactively address

potential legal and security requirements and mitigate

risks associated with non-compliance. Recognizing

common risks and mitigation strategies found in

literature reduces the likelihood of issues during the

project and builds confidence among stakeholders.

Different project management methodologies (e.g.,

Waterfall, Agile, DevOps) require specific types of

artefacts. A literature survey clarifies the most used

documentation needs associated with each

methodology, helping project managers choose a

documentation strategy aligned with their project

needs. All these insights have strong traditions and

are used over the years, but the pandemic situation

changed the approach to IT project management and

put corrections on the ability to perform certain

processes and to support creation of particular

artefacts turning focus on total digitalization of the IT

project communication channels.

The goal of this paper is to go through the last five

years scientific publications addressed to the artefacts

used and created during IT projects corresponding to

software development and to identify the most used

and mentioned activities and their outputs during IT

project management before software implementation.

Thus, performing such a survey on artefacts created

during IT project initiating and planning provides a

roadmap to follow, helping IT project managers to

prepare for each phase with the right tools and

documentation. As a result, it can help to promote

alignment with best practices and its compliance and

to ensure efficient use of resources up to modern

trends within IT projects.

The paper is structured as follows: Section 2

provides a discussion on related work, Section 3

outlines the research methodology applied for study

collection, Section 4 presents and discusses the

research findings, and Section 5 offers concluding

remark.

2 RELATED WORK

To ensure that a solid foundation is established for the

effective implementation of IT projects, the initiation

phase is crucial in outlining objectives and aligning

stakeholder expectations. In recent years, researchers

have focused on the significance of artefacts and

models, particularly regarding their relevance during

the initiation phase for managing requirements,

planning, and potential execution. This section

reviews the current literature concerning artefacts in

the initiation phase, model transformations, and the

challenges encountered in this process.

An empirical study of Greer & Conradi (2009)

highlights the variation in documentation practices

among organizations and points out the trade-off

between the resources devoted to thorough

requirements engineering and the quality of the

resulting plans. It examines how requirements

frequently lack completeness or stability at the

beginning of a project, which can influence the

predictability and quality of initial planning,

including cost-value assessment and scope definition.

In a similar context Wiegers & Beatty (n.d.),

argue that textual descriptions increase the likelihood

of misunderstanding when used as the sole medium

for communicating requirements.

A most recent study performed by Kim et al.

(2024) further discusses this issue by comparing text-

based and model-based approaches within the domain

of knowledge representation. They identified that

both approaches are essential to realize genuine

reflective representations of complex information but

argue that model-based approaches provide clearer

and more structured depictions of knowledge in

situations, such as with multi-dimensional data. Their

study underlines that text-based representations are

very likely to be ambiguous, while model-based

approaches, such as process models or use case

diagrams, reduce ambiguity because they allow for a

better-structured form of communication for complex

ideas.

Building on this, a significant study performed by

Sànchez-Ferreres et al. (2018) compares textual

documentation with model-based representations.

While it stresses the fact that such model-based

descriptions are much clearer and more concise, it

underscores the importance of process models. In

particular, the use of Business Process Modelling

Notation (BPMN) can provide more ordered and less

vague ways of modelling project elements that can

better express communication between various

stakeholders.

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Model transformation is critical in the initiation

phase of IT projects, where textual requirements need

to be translated into structured, visual models to

reduce ambiguity and ensure clearer communication.

As explained by Sendall & Kozaczynski, (2003), an

effective model transformation language must be

both expressive and efficient in handling this

complexity of transforming as diversified textual

descriptions, such as project charters and business

cases, into structured models, such as UML diagrams,

BPMN, or ER diagrams. This transforms project

scope, objectives, and stakeholder requirements

clearly. Additionally, Sendall & Kozaczynski (2003)

further describes the importance of specifying

conditions about when the transformation is

applicable or valid. Transformations applied for IT

project initialization should only happen if there exist

certain conditions such as when the project scope or

goal is clear and well defined; or after taking approval

from other stakeholders. Again, it happens to align in

line with controlling project risks with the aim to

ensure models effectively capture changes made in

the process.

Authors have been performed a systematic

literature survey on last ten years solutions, where

model transformations are used for IT project

artefacts development during project initial stages

(Nikiforova et al., 2025). The results of this survey

identified artefacts, where model transformations

have been successfully applied, and areas where they

have not been utilized. While existing studies

emphasize the advantages of model-based

representations in IT project initiation, there is a

notable lack of understanding regarding which

artefacts are most transformed into models and the

specific methods or frameworks used for these

transformations. This gap includes limited insight

into the types of artefacts frequently utilized during

this phase, the systematic processes for deriving

models from these artefacts, and the challenges

encountered during these transformations.

Addressing this gap is critical for establishing

effective practices in IT project initiation, as it can

enhance clarity, alignment, and communication

among stakeholders.

The commonly studied user story often provides

an insufficient description of software requirements.

Numerous studies address challenges in requirements

specification and propose various solutions.

However, with the diversity of agile methods – each

incorporating distinct practices – solutions must align

with the specific ceremonies of each method. Few

studies examine practices for requirements

specification development within agile methods, and

none offer a comparative analysis of these practices

across different agile approaches (Herdika and

Budiardjo, 2020).

Traditional metrics for software quality, such as

defect density and mean time to failure, do not fully

align with Agile iterative and sprint-based processes,

prompting the need for new metrics like sprint

velocity and burn-down charts (Chakravarty and

Singh, 2021). Another research performed by

Jarzębowicz and Weichbroth (2021) investigates the

part of non-functional requirements in Agile Software

Development projects, concentrating on existing

methods and gathering techniques. A methodical

review of literature and ten interviews with specialists

from the industry unveiled a lack of agreement about

when non-functional requirements should be

recognized during the running cycle of a project.

However, most experts give priority to early

recognition along with constant improvement

(Jarzębowicz and Sitko, 2020).

The related work in the area of machine learning

for guessing effort in Scrum projects shows the

difficulties and progressions in precisely predicting

project effort inside Agile frameworks. Usual

estimation methods, like expert opinion and

regression analysis, have frequently not been enough

in Agile environments because requirements and

iterations can change often in Scrum. To handle these

problems, researchers have more turned to ML

models - multiple studies prove that ML ways usually

do better than traditional strategies (Arora et al.,

2020). In response to practical challenges in Agile

estimation, studies have focused on identifying key

project factors, such as complexity and team

experience, that affect estimation accuracy.

Effective communication, training, and

documentation are essential for successful agile

requirement gathering. Collaboration and continuous

improvement are also crucial, and feedback from

stakeholders should be used to refine the approaches

(Simhadri and Shameem, 2023).

Not having enough documents or good quality

documents can make it hard for new members of the

project. They might struggle to understand systems

they are not familiar with and could make mistakes

because of misunderstanding things. It is helpful

when documentation is done at the end of a project

cycle, after decisions have been made about how to

implement everything (Nolan et al., 2022). That helps

people maintain and change the system in future

without needing constant updates as changes happen

in systems. Also making strict rules around storing

electronic document where people can easily find

them may help avoid problems related to lost or

Key Artefacts in the Initial Phases of IT Project Management: Systematic Mapping Study

775

unfindable information while also reducing

unnecessary extra documents that no one uses.

Recent work on scaling agility in organizations

has led to the development of taxonomies to

systematically categorize Agile frameworks. As

companies increasingly adopt frameworks for scaling

Agile practices, research aims to establish a

standardized understanding of the key dimensions

and characteristics of these frameworks (Turhan et

al., 2024). Wróbel et al. (2023) identified "Unfinished

Tasks" as the most common anti-pattern,

underscoring the critical role of effective planning

and task management within sprints. Wróbel et al.,

(2023) also identified several other common anti-

patterns, such as daily scrums exceeding the

recommended duration, user stories lacking full

refinement, and the sprint goal not being established

during the sprint planning meeting. Among the

various factors, customer-related and agile process

factors are stronger predictors of process efficiency,

sustainable software quality, and stakeholder

satisfaction than other factors (Binboga and

Gumussoy, 2024).

Based on comprehensive analysis of existing

literature reviews in the area, the authors arrived to

the following conclusions:

1) Further research could be conducted on the impact

of effective requirement gathering on project

outcomes (Simhadri and Shameem, 2023).

2) There is need for standardization of terminology,

as semantically similar factors are often labelled

differently across instrument (Santos et al., 2023).

3) When agile methods are implemented

inappropriately, projects risk delayed or defective

software, and overall decreased productivity (Nolan

et al., 2022).

4) Currently, the procedure and practices of agile

requirements engineering are still in the grey area

(Herdika and Budiardjo, 2020).

Consequently, the systematic mapping study

focusing on most published challenges in IT project

management during initial stages of software

development is not performed before and is quite

required in modern situation with the rapid

technologies and approaches changes. Moreover,

such literature survey can help to determine whether

which artefacts are more appropriate, guiding teams

to develop a process that best supports the project’s

scope and timeline.

3 RESEARCH METHODOLOGY

The primary objective of this systematic mapping

study research is to identify existing research on

artefacts used for IT project management at the initial

stages before the software implementation. In order

to provide a focused direction for the corresponding

papers collection the following research questions are

formulated:

1) Which artefacts are mentioned in scientific

papers as used for IT project management at the initial

stages of the project?

2) Which artefacts in the initial stage of projects

are obtained from which other artefacts on the same

stage?

The collection of the corresponding studies is

performed comprehensively in correspondence with

the approach described by Kitchenham and Brereton

(2013). An initial literature pool is constructed by

examining Scopus, IEEE, ACM, ScienceDirect,

IEEExplore databases of scientific papers. Firstly, the

pool is filtered by reviewing study titles and abstracts.

Secondly, a full-text assessment is performed for each

remaining study to identify its relevance to the

research scope. Subsequently, a snowballing

technique is applied to identify additional relevant

studies that may have been missed due to not being

found with the search query. The following criteria

are applied to select the initial pool of studies:

• Year of publication: 2020–2024.

• Language: English.

• Subject area: Computer science.

To identify potentially relevant studies, a

systematic search was conducted using a predefined

search query designed to capture relevant research

within the paper scope. The search query employed

the following keywords and logical operators:

("software" OR "information system") AND

("software development" OR "software project

management") AND ("software requirement

specification" OR "user story" OR "user stories")

AND ("scrum" OR "kanban" OR "waterfall" OR

"iterative" OR "incremental").

The initial search across these databases yielded a

total of 304 studies. After excluding duplicate entries

across databases, the remaining unique studies were

consolidated into a single dataset. A manual

screening process was subsequently conducted to

evaluate the relevance of each study. This process

involved assessing the titles, abstracts, and keywords

of the papers against the scope of the study. The

following inclusion criteria were used in the selection

process:

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1. Studies that explicitly address the IT project

management artefacts at the initial stages of projects.

2. Research focusing on specific methodologies or

frameworks such as Scrum, Kanban, Waterfall,

Iterative, or Incremental models.

3. Papers discussing software requirement

specification techniques, including user stories or

similar representations.

Exclusion criteria:

1. Studies unrelated to software project management

or development processes.

2. Papers focusing on later stages of IT projects.

3. Duplicate entries identified during the

consolidation of datasets across databases.

This rigorous selection process ensured that the

final pool of 118 studies was comprehensive,

relevant, and aligned with the research scope. 24

studies published in 2020, 29 - 2021, 25 – 2022, 20 –

2023, 20 – 2024.

Consequently, all the artefacts, notations used for

that artefacts and their types are registered in the

spreadsheet. In turn to perform systematic mapping

study on IT project artefact transformations, it is

essential to identify the artefact (-s) discussed in the

papers and to depict all mentioned transformations

among them in one scheme. The mapping results are

shown and discussed in the next section.

4 RESULTS AND DISCUSSION

The initiation phase of a project is generally seen as

the basis on which the whole project rests. According

to Russell (2018), during the initiation objectives are

clearly stated, the scope of the project is defined, and

a structure is created to align with the organizational

goals and stakeholder expectations, which makes or

breaks the success of the project. Initiating the project

is important because this is the stage which defines

the problems that need to be faced, specifies the

parameters of success, and defines the necessary

resources required for the project. Initiation of a

project refers not only to the launching of it but also

to laying the proper foundation of getting the project

executed properly.

In the initiation phase, textual descriptions are

used as the communicating key element of a project,

such as objectives, scope, and requirements from the

stakeholders. These text-based documents like

project charters, business cases, and requirement

specifications are often used at the onset of projects

for planning, thus ensuring all stakeholders have an

agreement on what the objectives of the project are.

However, textual descriptions in the initiation phase

are not without their challenges. Textual

documentation can allow requirements to be

ambiguous, and requirements of different types and

perspectives are in danger of being unintentionally

mixed-up during documentation. In that case, it is

difficult to isolate information pertaining to a certain

perspective amidst all the requirements in natural

language (Pohl, 2016).

Textual descriptions often cause ambiguity and

miscommunication among stakeholders, particularly

in complex IT projects where requirements must be

very well aligned. According to Wiegers & Beatty

(n.d.), the likelihood of misunderstanding is increased

when textual descriptions are used as the sole medium

for communicating project requirements.

In turn to overcome these limitations, many

organizations are looking at alternative approaches,

such as using models instead of textual descriptions.

Models are structured and visual ways of representing

information, which can reduce ambiguity and

enhance the clarity of the requirements (Pastor &

Molina, 2007). For example, process models, use case

diagrams, and entity-relationship diagrams are

accurate ways of expressing project elements and thus

enable easier identification of dependencies and

communicate complex concepts to diverse

stakeholders. These approaches, therefore, not only

enhance communication but also support more in

better project planning and execution.

The systematic mapping study explores

transformations among artefacts used during the

initial stages of IT projects, focusing on how the

transformations cover all the activities performed at

the beginning of the projects. The results provide

valuable insights into the processes and practices

adopted in the early stages of IT project development.

The study revealed a wide range of artefacts used at

the initial stages, including business models and

requirements, user stories, as well as product and

sprint backlog items. These artefacts vary in

abstraction levels, reflecting different stakeholder

perspectives and project needs.

Artefacts such as customer initial documentation

and high-level requirements documents serve as

transformations inputs, while user stories estimation

and prioritization as well as product and sprint

backlog planning and revision act as intermediate

representations for transitioning from project ideation

to elaboration before the development.

The analysis of studies collected by the research

methodology identifies common transformation

mechanisms, including manual translation, tool-

supported transformations, and model-driven

engineering practices (Nikiforova et al., 2009). For

Key Artefacts in the Initial Phases of IT Project Management: Systematic Mapping Study

777

example, business requirements are often translated

into system specifications using standardized

templates or through stakeholder workshops.

Similarly, models are converted into detailed

specifications using modelling tools.

Artefact transformations in IT projects encompass

a series of structured activities designed to ensure that

information flows accurately from one stage to the

next. These activities often require multidisciplinary

collaboration, domain expertise, and the integration

of tools to achieve seamless transitions. At the

beginning of IT projects, raw business needs are

collected through interviews, workshops, or surveys.

These needs are often vague and require refinement

into structured formats such as user stories or use

cases. Activities here include defining priorities,

identifying dependencies, and verifying requirements

with stakeholders to ensure clarity and alignment with

organizational goals. Figure 1 shows how these

activities are covered with transformations offered in

the studies collected for the mapping. Numbered

references to the artefact’s transformations used by

authors in the survey are decoded in Table 1, giving

the numbered reference in square bracket and the DOI

of the corresponding study.

The transformation of requirements into system

models is a critical step. Activities in this stage

involve creating process flows, data models, and

architecture diagrams to represent the intended

solution. These models serve as blueprints for

development teams, translating abstract requirements

into actionable designs. Misinterpretation of

requirements during transformations is especially

evident when it is performed from informal artefacts

(e.g., user stories) to structured ones (e.g., prioritized

and estimated product or sprint backlog).

Figure 1: Transformations among IT project artefacts at the initial project stages offered in the collected studies.

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Table 1: DOI of the studies offered the solutions for transformations shown in Figure 1.

ID DOI ID DOI

PS001 10.1007/978-3-030-63329-5_2. PS084 10.1111/isj.12282

PS002 10.1007/978-3-030-77474-5_2. PS086 10.1007/s10664-020-09876-x

PS004 10.1007/978-981-15-1081-6_53. PS087 10.1007/s10664-022-10208-4

PS005 10.1145/3493244.3493257 PS088 10.48550/arXiv.2008.02502.

PS007 10.29007/6vwh PS090 10.1007/978-3-030-36674-2_30

PS008 10.1002/smr.2247. PS091 10.1145/3403746.3403902

PS009 10.1016/j.advengsoft.2022.103159. PS092 10.1109/ICSE-SEET55299.2022.9794220

PS010 10.1007/978-981-15-1451-7_59 PS094 10.11591/eei.v9i6.2484

PS012 10.1109/OCIT59427.2023.10430672. PS095 10.1145/3468264.3473106

PS013 10.1109/ICOCO56118.2022.10031863. PS096 https://ceu

-ws.org/Vol-3776/paper02.pdf

PS014 10.1109/SERA51205.2021.9509045. PS098 10.1049/sfw2.12037

PS015 10.1109/IBSSC53889.2021.9673243 PS100 10.1109/ICBATS54253.2022.9759013

PS016 10.1109/ACCESS.2021.3064424. PS101 10.1016/j.infsof.2022.107079

PS018 10.11591/ijece.v11i6.pp5342-5350. PS102 10.1109/ICNC47757.2020.9049681

PS021 10.1007/978-3-030-81242-3_10. PS104 10.1109/ASE51524.2021.9678939

PS023 10.1007/978-981-19-9888-1_32 PS105 DOI:10.5381/jot.2022.21.3.a3

PS024 10.1007/978-3-031-35251-5_29 PS106 DOI:10.1145/3387940.3392241

PS025 10.1016/j.procs.2020.09.052. PS107 10.1007/978-3-030-89817-5_30

PS026 10.1007/978-3-031-71142-8_21 PS108 10.1007/s11219-024-09688-y

PS029 10.1177/1063293X20958541 PS109 10.1016/j.jss.2022.111479

PS030 10.1109/APSEC57359.2022.00058. PS110 10.5753/cibse.2024.28454

PS031 10.1007/978-3-031-43126-5_10 PS111 https://ceu

-ws.org/Vol-3414/pape

-1-preface.pdf

PS032 10.1145/3605098.3635901 PS113 10.1109/ICCSAI59793.2023.10421235.

PS033 10.1007/978-981-16-0404-1_24 PS114 10.1145/3524614.3528633.

PS035 10.1109/ACCESS.2020.3010968 PS115 10.3390/info14060327

PS036 10.1109/APCIT62007.2024.10673601 PS116 10.11591/ijeecs.v21.i1.pp360-366.

PS037 10.1155/2021/6611407. PS117 10.1145/3377812.338216

PS038 10.1155/2022/3556809 PS118 10.1109/ICoDSE56892.2022.9972012

PS039 10.1109/RE57278.2023.00034 PS119 10.1007/978-3-030-94238-0_12

PS040 10.1142/S0218194023430015 PS121 10.1109/CONISOFT58849.2023.00017

PS041 10.1109/ICIC53490.2021.9693024. PS123 https://web.archive.org/web/20201105065450i

PS042 10.1145/3328778.3366948 PS124 10.1007/978-3-031-21388-5_24

PS044 10.1109/ACCESS.2023.3305249 PS126 10.1109/RE57278.2023.00041

PS047 10.1007/978-3-030-63329-5_2 PS129 10.1007/978-3-031-60227-6_11.

PS048 10.1145/3555776.3577696 PS132 10.1007/s11219-022-09593-2

PS049 10.1145/3419604.3419793 PS134 10.1109/CONISOFT52520.2021.00023

PS050 10.18517/ijaseit.10.1.10176 PS135 10.1186/s13173-021-00114-w

PS051 10.3390/informatics11010012 PS137 10.1109/ACCESS.2024.3393831

PS052 10.1109/SEAI62072.2024.10674233 PS139 10.1007/978-3-031-03884-6_39

PS053 https://ceu

-ws.org/Vol-3672/PT-paper2.pdf PS140 10.1109/ENC56672.2022.9882947

PS054 10.1109/ICITSI56531.2022.9970965 PS141 10.3390/educsci11020073

PS056 10.1016/j.infoandorg.2020.100288. PS143 10.1007/s10664-022-10192-9.

PS058 10.1109/INCOFT60753.2023.10425234 PS144 10.1007/978-3-030-96308-8_107

PS060 10.1007/s00766-022-00384-6 PS145 10.1109/ICT4S55073.2022.00013

PS061 10.1109/KI55792.2022.9925969. PS148 10.1109/ESEM56168.2023.10304859.

PS064 10.1145/3383219.3383245 PS149 10.1080/20421338.2021.1955431

PS065 10.1007/978-3-030-67445-8_11 PS150 10.14569/IJACSA.2023.0140788

PS066 10.1007/978-981-19-7663-6_67 PS151 10.1109/CONISOFT55708.2022.00016.

PS067 10.1109/CIMPS61323.2023.10528839 PS152 10.1109/ATSIP62566.2024.10639040.

PS068 10.3390/math11061477 PS154 10.1007/978-3-030-89912-7_36

PS070 10.1016/j.infsof.2024.107447 PS155 10.1109/ICSME52107.2021.00017

PS071 10.1109/ACCESS.2024.3414614. PS156 10.14569/IJACSA.2021.0121225

PS072 https://api.semanticscholar.org/CorpusID:270069156 PS157 10.1016/j.jss.2021.111013

PS073 10.1007/978-3-031-64576-1_17 PS158 10.1109/TELE58910.2023.10184341

PS077 10.1109/ICITACEE50144.2020.9239165 PS159 10.1109/ICIDM51048.2020.9339668

PS079 10.3390/app14198991 PS160 10.1007/978-3-030-88304-1_9

PS080 10.1007/978-3-030-79976-2_6 PS161 10.1109/IC2IE50715.2020.9274564

PS081 10.1109/CBI52690.2021.10066 PS162 https://www.researchgate.net/publication/381164049

PS083 10.1007/978-3-031-70245-7_19 PS163 10.1007/978-3-031-19968-4_5

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779

The lack of standardized transformation processes

often leads to inconsistencies and misalignments

between artefacts, which can propagate errors to later

stages. Tools and frameworks supporting

transformations significantly improve the accuracy

and efficiency of artefact obtaining from some source

information in a form of well-structure

transformation rules. Model-driven tools, for

example, automate certain aspects of design creation,

ensuring consistency across artefacts. Many IT

projects use specialized tools to support artefact

transformations. For example, requirements

management tools may generate traceability matrices,

while e.g. UML modelling tools can create technical

diagrams (Nikiforova and Pavlova, 2008). Tool-

assisted activities often include importing, exporting,

and refining artefact formats to maintain

compatibility and ensure information consistency

across platforms. However, over-reliance on tools

without proper customization or stakeholder input

can lead to generic solutions that fail to address

specific project contexts. As well as transformations

are rarely one-direction and linear.

5 CONCLUSIONS

This study examined the studies on creation of IT

project artefacts used in the initial stages of project

management, with a focus on methodologies and

frameworks such as Scrum, Kanban, Waterfall,

Iterative, and Incremental models. The "agile-style

work environment" factor emphasizes the critical

need for efficient and effective communication,

leveraging suitable methods and tools to ensure

seamless information exchange in a remote work

context. This highlights the critical role of well-

defined IT project artefact, especially at the initial

stages of the projects and underscores the need for

structured approaches, collaborative practices, and

technological support to optimize obtaining of these

artefacts as complete and consistent.

Key findings were identified such as the role of

artefacts, different transformation mechanisms, text

description issues, technological support and the

impact of flexible and remote working environments.

While the study provides valuable insights, its

limitations include industry differences, reliance on

secondary sources and contextual differences. The

study offers practical guidelines for improving

project initiation and forms the basis for future

research on the optimisation of artefact

transformation in IT projects.

The study has been validated through a systematic

selection process that ensures the reliability and

relevance of the data collected. A comprehensive

literature review identified 80 relevant studies from

an initial 304 publications across multiple academic

databases. The inclusion criteria ensure that only

studies directly addressing the research objectives are

considered. However, while the study analysed a

wide range of studies, it may not have covered all the

nuances of artefact transformation across different

sectors and organisational structures. The reliance on

secondary data sources means that some contextual

details and case-specific insights may be overlooked,

and differences in project complexity, stakeholder

involvement and technological support further affect

the applicability of the findings.

The added value of this study is the identification

of structured transformation methods, highlighting

the importance of model-based tools and

collaborative practices. While this lays the

foundations for improving the accuracy and

consistency of artefacts, further empirical research

and case studies are needed to validate these findings

in real IT project environments.

ACKNOWLEDGEMENTS

This research has been supported by Research and

Development grant No RTU-PA-2024/1-0015 under

the EU Recovery and Resilience Facility funded

project No. 5.2.1.1.i.0/2/24/I/CFLA/003

“Implementation of consolidation and management

changes at Riga Technical University, Liepaja

University, Rezekne Academy of Technology,

Latvian Maritime Academy and Liepaja Maritime

College for the progress towards excellence in higher

education, science, and innovation”.

REFERENCES

Agile Manifesto (2001) https://agilemanifesto.org/

Binboga, B., Gumussoy, C. (2024). Factors Affecting Agile

Software Project Success, IEEE Access, vol. 12, 95613-

95633, DOI: 10.1109/ACCESS.2024.3384410

Chakravarty, K., Singh, J. (2021). A Study of Quality

Metrics in Agile Software Development. In: Machine

Learning and Information Processing. Advances in

Intelligent Systems and Computing, vol 1311. Springer.

DOI: 10.1007/978-981-33-4859-2_26

Greer, D., & Conradi, R. (2009). Software project initiation

and planning – an empirical study. IET Software, 3(5),

356–368. DOI: 10.1049/iet-sen.2008.0093

ENASE 2025 - 20th International Conference on Evaluation of Novel Approaches to Software Engineering

780

Helmlinger, P. (2023). Agile transformation: A case study

on early stage of agile adoption, Our Economy,

Sciendo, Warsaw, Vol. 69, Iss. 1, 56-67, DOI:

10.2478/ngoe-2023-0006

Jarzębowicz, A., Sitko, N. (2020). Agile Requirements

Prioritization in Practice: Results of an Industrial

Survey, Procedia Computer Science, v. 176, pp 3446-

3455, DOI: 10.1016/j.procs.2020.09.052

Jarzębowicz, A., Weichbroth, P. (2021). A Qualitative

Study on Non-Functional Requirements in Agile

Software Development, IEEE Access, v. 9, 40458-

40475, DOI: 10.1109/ACCESS.2021.3064424

Josep Sànchez-Ferreres, Han, Carmona, J., & Lluís Padró.

(2018). Aligning textual and model-based process

descriptions. Data & Knowledge Engineering, 118, 25–

40. DOI: 10.1016/j.datak.2018.09.001

Kim, M. K., Kim, J., & Heidari, A. (2024). Exploring the

multi-dimensional human mind: Model-based and text-

based approaches. Assessing Writing, 61, 100878–

100878. DOI: 10.1016/j.asw.2024.100878

Kitchenham, B.; Brereton, P. (2013) A systematic review

of systematic review process research in software

engineering, Inf Softw Technol, vol. 55, no. 12, 2049–

2075, DOI: 10.1016/j.infsof.2013.07.010

Nikiforova, O., Babris, K., Karlovs-Karlovskis, U.,

Narigina, M., Romanovs, A., Jansone, A., Grabis, J., &

Pastor, O. (2025). Model Transformations Used in IT

Project Initial Phases: Systematic Literature Review.

Computers, 14(2), 40. https://doi.org/10.3390/

computers14020040

Nikiforova, O., Nikulsins, V., Sukovskis U. (2009)

Integration of MDA framework into the model of

traditional software development, Frontiers in Artificial

Intelligence and Applications, 187 (1), 229 - 239, DOI:

10.3233/978-1-58603-939-4-229

Nikiforova, O., Pavlova, N. (2008) Development of the tool

for generation of UML class diagram from two-

hemisphere model, 3rd International Conference on

Software Engineering Advances, 105 - 112, DOI:

10.1109/ICSEA.2008.37

Nolan, A., Strickland, B., Quinn, A., et al. (2022).

Exploring Aspects of Agile Software Development

Risk – Results from a MLR. In: Yilmaz, M., et al. (eds)

Systems, Software and Services Process Improvement.

Communications in Computer and Information

Science, vol 1646. Springer. DOI: 10.1007/978-3-031-

15559-8_35

Omonije, A. (2024). Agile Methodology: A

Comprehensive Impact on Modern Business

Operations. International Journal of Science and

Research, 13. DOI: 10.21275/SR24130104148

Pastor, O.; Molina, J. (2007). Model-driven architecture in

practice: A software production environment based on

conceptual modelling. Springer, DOI: 10.1007/978-3-

540-71868-0.

Pastor, O., Nöel, R., Panach, I. (2021) From Strategy to

Code: Achieving Strategical Alignment in Software

Development Projects Through Conceptual Modelling.

Transactions on Large Scale Data Knowledge Centred

Systems. 48: 145-164, DOI: 10.1007/978-3-662-

63519-3_7

Pasuksmit, J., Thongtanunam, P., & Karunasekera, S.

(2021). Towards Just-Enough Documentation for Agile

Effort Estimation: What Information Should Be

Documented? IEEE International Conference on

Software Maintenance and Evolution, 114–125. DOI:

10.1109/ICSME52107.2021.00017

Pohl, K. (2016). Requirements Engineering Fundamentals,

2nd Edition: A Study Guide for the Certified

Professional for Requirements Engineering Exam -

Foundation Level - IREB compliant. United States:

Rocky Nook.

Project Management Institute (2021). A Guide to the

Project Management Body of Knowledge: PMBOK(R)

Guide (7th. ed.). Project Management Institute.

ISBN:978-1-935589-67-9

Russell, J. S., Pferdehirt, W. P., & Nelson, J. S. (2018).

Project Initiation, Scope, and Structure. Unizin.org;

University of Wisconsin-Madison.

https://wisc.pb.unizin.org/technicalpm/chapter/project-

initiation-scope-and-structure/

Santos, R., Cunha, F., Rique, T., et al. (2023). Evolution of

Teamwork Quality Instruments in Agile Software

Development: A Systematic Literature Review, 216-

225. DOI: 10.1145/3613372.3613404

Schön, EM., Radtke, D., Jordan, C. (2020). Improving Risk

Management in a Scaled Agile Environment. In: Stray,

V., et al. (eds) Agile Processes in Software Engineering

and Extreme Programming. XP 2020. Lecture Notes in

Business Information Processing, vol 383. Springer.

DOI: 10.1007/978-3-030-49392-9_9

Sendall, S.; Kozaczynski, W. (2003). Model

transformation: the heart and soul of model-driven

software development. IEEE Software, 20(5), 42–45.

DOI: 10.1109/ms.2003.1231150

Simhadri, R., Shameem, M. (2023). Challenges in

Requirements Gathering for Agile Software

Development. 27th International Conference on

Evaluation and Assessment in Software Engineering

ACM, 406–413. DOI: 10.1145/3593434.3594237

Simonaitis, A., Daukšys, M., Mockienė, J. (2023). A

Comparison of the Project Management Methodologies

PRINCE2 and PMBOK in Managing Repetitive

Construction Projects. Buildings 2023, 13, 1796. DOI:

10.3390/buildings13071796

Turhan, Y., Buehrle, D., Herzwurm, G. (2024). Developing

a Taxonomy for Agile Scaling Frameworks. 7th ACM

International Workshop of Software-intensive

Business: Software Business in the era of generative

artificial intelligence, ACM, p. 8. DOI:

10.1145/3643690.3648239

Wiegers, K., & Beatty, J. (n.d.). Software Requirements,

Third Edition. https://thuvienso.hoasen.edu.vn/

bitstream/handle/123456789/9059/Contents.pdf?seque

nce=5&isAllowed=y

Wróbel, M., Przała, D., Weichbroth, P. (2023). Exploring

the Prevalence of Anti-patterns in the Application of

Scrum in Software Development Organizations, DOI:

10.15439/2023F9562

Key Artefacts in the Initial Phases of IT Project Management: Systematic Mapping Study

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