Key Artefacts in the Initial Phases of IT Project Management:
Systematic Mapping Study
Oksana Nikiforova
1a
, Kristaps Babris
1b
, Megija Krista Miļūne
1c
, Navyasri Tanguturi
1d
and Óscar Pastor
2e
1
Riga Technical University, Riga, Latvia
2
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
a
https://orcid.org/0000-0001-7983-3088
b
https://orcid.org/0000-0003-3855-6963
c
https://orcid.org/0009-0002-2417-4518
d
https://orcid.org/0009-0004-2203-6976
e
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., Tangutur i, N. and Pastor, Ó.
Key Artefacts in the Initial Phases of IT Project Management: Systematic Mapping Study.
DOI: 10.5220/0013471000003928
Paper published under CC license (CC BY-NC-ND 4.0)
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
Proceedings Copyright © 2025 by SCITEPRESS – Science and Technology Publications, Lda.
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.
ENASE 2025 - 20th International Conference on Evaluation of Novel Approaches to Software Engineering
774

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:
ENASE 2025 - 20th International Conference on Evaluation of Novel Approaches to Software Engineering
776

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.
ENASE 2025 - 20th International Conference on Evaluation of Novel Approaches to Software Engineering
778

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
r
-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
r
-ws.org/Vol-3414/pape
r
-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
d
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
r
-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
Key Artefacts in the Initial Phases of IT Project Management: Systematic Mapping Study
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
781