The Diversity of Approaches to Support Software Project
Management in the Agile Context: Trends, Comparisons and Gaps
Elielton da Costa Carvalho
and Sandro Ronaldo Bezerra Oliveira
Graduate Program in Computer Sciense, Institute of Exact and Natural Sciences, Federal University of Pará,
Belém, Pará, Brazil
Keywords: Software Project Management, Project Management Approaches, Systematic Review of Literature.
Abstract: The literature has reported a significant number of approaches to support software development teams. Due
to this diversity of approaches, the process of choosing which one is the most suitable for a given project
becomes a complex task as new approaches emerge. In addition, there has been no comprehensive work on
what these project management approaches are, nor what their main advantages and limitations are. Therefore,
it becomes important to research the characteristics of these approaches and map them to minimize decision
challenges. Therefore, the objective of this work is to identify primary studies in software engineering that
present approaches to support the management of software projects in the agile context. To achieve this goal,
we conducted a systematic review study and selected 65 studies on software project management approaches.
From these studies, we identified eight different types of approaches, with software being the most used ap-
proaches in this context. In addition, nine project areas were identified in which these approaches focus,
among which "Schedule" and "Quality" stand out as the areas with the greatest focus by the approaches.
Finally, we identified that the "Planning" is the phase of the project in which the approaches place more
Alignment between project management and
business strategy can significantly increase the
chances of organizations achieving their goals, as
well as improving their performance (Gomes and
Romão, 2016). In addition, agile development
favoured the software industry, but required
approaches that meet this new development
paradigm. In this way, exploring new approaches can
help organizations adapt more quickly to the new
realities of the economy (Parsi, 2021).
The literature has reported a significant number of
approaches (software, methodology, method, model,
tool, technique, framework, practice) to support
software development teams. Due to this diversity of
approaches, the process of choosing which one is the
most suitable for a given project becomes a complex
task as new approaches emerge. It is observed,
therefore, that the challenges in agile development
have been and continue to be explored, but there has
not been any comprehensive work on what these
project management approaches are, nor what are
their main advantages and limitations, which
indicates the need for a further research in this area
(Shrivastava and Rathod, 2017).
It is therefore important to research the
characteristics of these approaches and map them to
minimize decision challenges. Additionally, it is also
necessary to investigate how they are used and the
lessons learned from their use, in order to identify
opportunities for improvement (Varajão et al., 2017).
Thus, the objective of this work is to identify primary
studies in software engineering that present
approaches to support the software projects
management in the agile context.
To achieve this goal, we performed a systematic
review study and selected 65 studies on approaches to
software project management. In our results, we
identified 8 types of distinct approaches, 9 areas that
these approaches focus on, as well as 5 project phases
that they emphasize.
Carvalho, E. and Oliveira, S.
The Diversity of Approaches to Support Software Project Management in the Agile Context: Trends, Comparisons and Gaps.
DOI: 10.5220/0011063500003176
In Proceedings of the 17th International Conference on Evaluation of Novel Approaches to Software Engineering (ENASE 2022), pages 138-149
ISBN: 978-989-758-568-5; ISSN: 2184-4895
2022 by SCITEPRESS Science and Technology Publications, Lda. All rights reserved
In addition to this introductory section, this work
is structured as follows: Section 2 presents some
concepts on the topic of this research, Section 3
details the study design, Section 4 presents the results,
Section 5 presents the discussions, Section 6
addresses some threats to the validity of this work,
Section 7 brings some related works and Section 8
closes this work by presenting the conclusions.
This section introduces concepts related to software
project management and software project
management approaches.
The PMBOK Project Management Body of
Knowledge (2017) defines a project as a temporary
effort undertaken to create a unique product, service
or result. In turn, project management is defined as
the application of knowledge, skills, tools and
techniques to project activities in order to fulfill
project requirements. Banica et al. (2018) state that
the main objective of project management is to
provide expected results with quality, planned time,
and approved costs, in addition to being essential to
take care of risks. The PMBOK Guide (2017) also
mentions that several approaches can be used to assist
the project manager and support team collaboration.
Project management approaches are means that
aim to support the whole process or part of the
management process. These approaches can be
software, methodologies, practices, methods,
frameworks, models, among others (Kostalova et al.,
2015). These approaches contribute to a significant
gain in the efficiency and effectiveness of project
management. In addition, they allow a change in the
way of managing projects and give professionals
greater decision-making power, especially project
managers (Retnowardhani and Suroso, 2019). The
authors also reinforce that organizations should use
them to obtain better results in their projects.
This section presents the objectives of the work, the
research questions and the method used.
3.1 Goal and Research Question
This study aims to identify the approaches used to
support the software projects management in agile
context. We are interested in identifying the type of
approach, where it is applied within the project, its
main contributions and limitations, as well as the
form of evaluation used by its developers.
To formalize the objective of this study, the Goal-
Question-Metric (GQM) defined by Basili (1992)
was used. Thus, this study seeks to:
Analyze: primary studies, through a Systematic
Literature Review (SLR),
In order to: identify the approaches used in
software project management (SPM) that are
reported in the specialized literature,
Regarding: the definition, use and evaluation of
these approaches,
From the point of view of: researchers,
organizations and professionals in software
project management,
In context: industrial and academic agile
software development,
Thus, we propose the following research
questions (RQ):
RQ1: What is the name and type of approach?
The objective is to identify the type of SPM
approach that was used in the work, eg method,
software, technique, etc., as well as the name of
the approach,
RQ2: What are the strengths and limitations of
the approach? – The objective is to identify the
main points that deal with the advantages and
disadvantages of using the identified approach,
RQ3: How was the approach evaluated? The
objective is to identify the method used to
evaluate the use of the approach.
3.2 Method
To achieve the objective of this work, an SLR was
conducted. SLR is an evidence-based secondary
study method to systematically identify, analyze and
interpret all relevant documents related to a specific
research question (Kitchenham and Charters, 2007).
We performed the SLR from May/2021 to
January/2022. The study was organized in four
stages, adapted from (Kitchenham and Charters,
2007; Petersen et al., 2015), as follows:
Step 1 Definition of research questions: in this
step, three research questions were defined based
on the objective of the study (Subsection 3.1),
Step 2 – Search: in this stage, based on the
research questions, a replicable process was
defined for carrying out the search for studies in
selected scientific bases (Subsection 3.3),
Step 3 Study selection: in this step a replicable
process was defined and applied to select only
The Diversity of Approaches to Support Software Project Management in the Agile Context: Trends, Comparisons and Gaps
the relevant studies according to the objective of
this work (Subsection 3.4),
Step 4 Study classification and data extraction:
in this step, based on the research questions, a
strategy was defined to: (i) map the relevant data
from the primary studies (Subsection 3.5) and
(ii) present the results of the work (Section 4).
Two researchers participated in the planning and
execution of the work: a graduate student in
Computer Science and a professor / researcher with a
PhD in Software Engineering.
3.3 Search Strategy
The search took place in an automated way through a
string formed by a series of keywords and their
respective synonyms. These keywords were defined
based on the research questions, from the PICOC
(Population, Intervention, Comparison, Outcomes
and Context) structure suggested by Kitchenham and
Charters (2007).
However, "Comparison" and "Intervention" are
not part of the scope of this work. In this way, the
string was formulated with terms related to (i)
population, (ii) outcome and (iii) context. The terms
used were:
Population: project management,
Result: tool, method, technique, model,
technology, practice, standard, guide, work
product, methodology, framework, process,
principle, theme and profile,
Context: software and agile.
Thus, we got the following search string:
(“project management”) AND (“tool” OR “method”
OR “technique” OR “model” OR “technolog*” OR
“practice” OR “pattern” OR “standard” OR
“guide” OR “work product” OR “methodolog*” OR
“framework” OR “process” OR “principle” OR
“theme” OR “profile”) AND (“software”) AND
The search string was applied to the IEEE Xplore
and ACM DL databases. We did not search the EI
COMPENDEX and SCOPUS because, according to
the results of Souza et al. (2018), there was a high rate
of redundancy.
3.4 Study Selection
In this step of the work, inclusion (IC) and exclusion
(EC) criteria were applied in order to select only the
relevant works that answered our research questions.
The IC and EC are presented below.
IC: Studies that present some software project
management approach applied in the agile
context and studies that evaluated the approach
EC: Studies that are not written in English,
studies not available for download openly or
through the institutional IP of the researchers,
studies such as workshop reports, posters,
presentations, speaker keynotes, books, theses
and dissertations.
Each of the studies underwent a selection process
consisting of four steps: (i) two researchers read the
titles and abstracts of all studies and applied the
exclusion criteria, this step was defined as pre-
selection, (ii) the same researchers discussed
differences in the application of exclusion criteria to
reach a consensus, (iii) the researchers read the title
and abstract, and the full text if necessary, of the
studies selected in the first step to apply the inclusion
criteria, (iv) the researchers discussed differences in
the application of exclusion criteria to reach a
Regarding the IEEE, a total of 1339 studies were
returned, among which 1235 were excluded after pre-
selection, leaving 104 studies. About ACM, 1486
studies were returned when running the search string.
Of this total, 1233 were excluded in the pre-selection.
Thus, 253 studies remained. After pre-selection, the
remaining 357 primary study were read in full and
submitted to the IC and EC.
The process resulted in 65 primary studies (25
from IEEE and 40 from ACM) (available at
3.5 Study Classification and Data
To collect the necessary data that answer the research
questions defined for this work, a researcher was
responsible for reading the 65 selected studies.
Data analysis aims to classify the studies
according to the proposed research questions.
Therefore, the result of this SLR should map and
classify studies regarding: the presence of software
project management approaches, the project area and
phase approach was used, the advantages and
disadvantages of its use, and the form of evaluation
of the approach.
This section presents the results of SLR. Subsection
4.1 presents an overview of the results. Subsections
4.2, 4.3, and 4.4 describe the results for RQ1, RQ2,
ENASE 2022 - 17th International Conference on Evaluation of Novel Approaches to Software Engineering
and RQ3, respectively. In these subsections, the
primary studies will be referenced and identified by
codes and are available at the URL presented in
Subsection 3.4.
4.1 Overview
SLR looked for works between the years 2001 and
2021. However, the 65 selected primary studies are
distributed between the years 2004 and 2021, as
shown in Figure 1. Still based on Figure 1, it is
possible to notice that, despite a decrease in the
number of studies after 2008, the trend is for a growth
in the number of publications related to the subject of
this work, with a sharper peak from 2015. However,
it is also noted that the years 2020 and 2021 showed
a decrease significant in the number of publications.
According to Yanow and Good (2020), there was a
reduction in the number of publications in 2020 as
many universities and companies had to reduce their
research activities, as the laboratories were closed. It
should also be taken into account that the number of
studies in 2021 is lower as a result of the period of
execution of this work.
Figure 1: Distribution of studies per year.
Figure 2 presents the project areas where the
identified approaches are used. Based on this figure,
it is possible to verify that the focus of the approaches
is mainly focused on the areas of schedule (22
studies), quality (19 studies) and communications (17
studies), as is the case of the following primary
studies: [PS61], [PS59] and [PS30], respectively.
Figure 3 illustrates the project phases where the
approaches identified in this work are used. It is
possible to note that the approaches give more
emphasis to the project planning phase (36 studies),
in addition to the monitoring and control (28 studies)
of the same, as can be exemplified by [PS64] and
[PS10], respectively.
It is important to note that some studies focus on
more than one phase of the project at the same time,
as is the case, for example, of the following studies:
[PS07, PS12, PS28, PS54, PS65]. The same applies
to the project areas, because, as in the phases, there
are studies that are focused on more than one area
simultaneously, for example: [PS04, PS34, PS39,
PS47, PS57].
Figure 2: Project areas where identified approaches are
Figure 3: Project phases where identified approaches are
4.2 Type of Approach
This subsection presents results referring to RQ1
(“What is the name and type of approach?”).
From the selected studies, it was possible to
identify eight types of approaches, they are: software,
methodology, method, model, tool, technique,
framework and practice. Figure 4 illustrates the types
of approaches identified, as well as the number of
studies that address each of them.
Still based on Figure 4, it is possible to verify that
“software” is the most common type of approach used
to support the software projects management, this
approach being identified in 15 studies. Soon after,
approaches of the “methodology” type are the ones
that stand out the most, developed and / or used in 12
studies. Finally, among the types of approaches that
are most used, “method” appears in third place, with
The Diversity of Approaches to Support Software Project Management in the Agile Context: Trends, Comparisons and Gaps
this type of approach being identified in 11 primary
It is worth noting that “framework” and “practice”
approaches are the least used, according to data
extracted from primary studies. Such approaches
were observed only in four and two studies,
Figure 4: Types of approaches identified.
4.2.1 Software
As mentioned earlier, software is the most common
type of approach used to support software project
management. Table 1 presents the studies that present
this type of approach.
Table 1: Studies that present a “Software” approach.
Studies that present a “Software” approach
[PS01], [PS02], [PS06], [PS07], [PS10], [PS14], [PS16],
[PS21], [PS30], [PS40], [PS43], [PS44], [PS52], [PS61],
Morgan and Maurer (2006) [PS44] report in their
study the use of MasePlanner. MasePlanner is
software aimed at planning communication in the
project. It is software that, according to the authors,
supports interactions, facilitating non-verbal
communication. MasePlanner provides teams with a
digital environment that supports information
management in addition to natural interactions. With
respect to support for natural interaction, MasePlaner
allows planning work products to be created, edited
and organized in a similar way to paper planning
More recently, Alhazmi and Huang (2018)
[PS01] developed the Sprint Planning Decision
Support System (SPESS). This software aims to assist
managers in sprint planning. SPESS is primarily
based on three factors: developer competence,
developer seniority, and task dependency. This tool
aims to assign the tasks of each Sprint to the
developers ensuring that each team member
contributes to the maximum of their potential, and the
project planning is optimized for the shortest possible
The other studies that use software are focused on
communication [PS06, PS10, PS30, PS40, PS52],
quality [PS02, PS07, PS14, PS16, PS62], schedule
[PS07, PS14, PS43, PS61], scope [PS07] and
stakeholders [PS21]. It is worth noting that software
does not necessarily serve only one area of the
project. Begosso et al. (2019) [PS07], for example,
present SimScrumF. This software is a game that
focuses on promoting student engagement in the
process of learning the concepts of Scrum
methodology, widely used to manage software
development projects around the world. The game
addresses the process of managing the scope defined
for the project, aiming to deliver a product with
quality, within the pre-established schedule.
4.2.2 Methodology
Behind only software, methodologies were the most
used approaches to support project management.
Table 2 presents the studies that focus on this type of
Table 2: Studies that present a “Methodology” approach.
Studies that present a “Methodology” approach
[PS04], [PS09], [PS12], [PS13], [PS17], [PS20], [PS28],
[PS37], [PS39], [PS47], [PS53], [PS54]
Castillo-Barrera et al. (2018) [PS13] state that
before starting the execution of the project, it is
necessary to have previously carried out an analysis
and also a synthesis of the information that permeates
it. To this end, the authors present BloomSoft, a
methodology adapted from Bloom's Taxonomy and
used in conjunction with Scrum, which aims to
support teams in planning the construction,
integration and testing of the software that will be
developed in the project. Not only that, as the authors
also emphasize that the methodology makes it
possible to have an agile way of classifying the
complexity of user stories based on the verbs
identified in them and, concomitantly, to determine
from this classification the stage of Software
Development to which it belongs. Thus, the
development team has the possibility to classify the
stories in stages and, with that, make a better planning
for each Sprint.
Bierwolf et al. (2017) [PS09] report the use of
DevOps methodology in software project
management. DevOps aims to mitigate risks, in
particular to achieve a stable, secure and reliable
ENASE 2022 - 17th International Conference on Evaluation of Novel Approaches to Software Engineering
production environment. Through this form of
communication and collaboration, all stakeholders
manage any uncertainties that arise, for example, due
to changes in technology or any changes in the
environment. The work also performs a comparison
between the results of using traditional approaches in
relation to DevOps approaches. The comparison is
mainly related to aspects such as control and
mitigation of uncertainties and risks.
There is also a methodology that varies from
Scrum and is presented by Baptista (2008) [PS04].
uScrum, the methodology described in the
aforementioned study, manages uncertainty and the
unknown, allowing the team involved in the project
to react quickly to changes in the most diverse
conditions. uScrum allows the team to effectively
prioritize regular work alongside the more difficult
creative work. The methodology prioritizes tasks in
monthly iterations based on their importance, urgency
and timeliness and, like Scrum, they are also called
4.2.3 Method
Another type of approach that stands out are methods,
as this type of approach was identified in 11 of the 65
selected studies and, together with models, is the third
most used to support software project management.
Table 3 presents the studies that deal with methods.
Table 3: Studies that present a “Method” approach.
Studies that present a “Method” approach
[PS03], [PS05], [PS08], [PS11], [PS15], [PS23], [PS26],
[PS31], [PS50], [PS56], [PS64]
Haugen (2006) [PS26] describes the use of
Planning Poker. The aim of the study is to examine
whether introducing the planning poker process into
user story estimation improves estimation
performance compared to unstructured group
estimation. In this process, the customer first explains
each user story to the developer group. Developers
then discuss the work involved in implementation to
the point where everyone feels they have enough
information to estimate the effort required. All
developers then estimate the user story independently
and reveal their estimates simultaneously. Next, the
developers with the lowest and highest estimates
justify their estimates, and the group continues the
discussion to decide on a collective estimate, possibly
conducting one or more additional rounds of
individual estimates.
Zhang et al. (2016) [PS64] address in their study
on Early Software Size Estimation (ESSE), a method
that can extract semantic features from natural
language requirements automatically and build size
estimation models for the project. ESSE performs a
semantic analysis of requirements specification
documents by extracting information and
disseminating activation. Then, characteristics related
to complexity are extracted from the semantic
analysis results. In addition, ESSE extracts local
resources and global resources to do word-level
semantic analysis. Then, using these features, size
drivers and actual sizes from historical project data,
the size estimation model can be established by
regression algorithms. Finally, ESSE can estimate the
size of a new project using this size estimation model.
The other studies that use some software project
management methods are concerned with managing
quality [PS05, PS50], schedule [PS11], resources
[PS31, PS56], scope [PS03] and project risks [PS23].
In addition, these same studies are focused on the
following project phases: planning [PS11, PS23,
PS31], execution [PS50] and monitoring and control
[PS03, PS05, PS23, PS31, PS56].
4.2.4 Model
As well as the methods, it was possible to identify,
through the selected studies, 11 models that aim to
support the software projects management in agile
context. Table 4 presents the studies that focus on this
type of approach.
Table 4: Studies that present a “Model” approach.
Studies that present a “Model” approach
[PS22], [PS25], [PS27], [PS29], [PS34], [PS36], [PS46],
[PS48], [PS55], [PS58], [PS59]
Godoy et al. (2019) [PS22] present a new software
development tool based on agile methodologies
Scrum and Kanban and adapted to the current trend
of the global software environment. The Blueprint
model proposes lightweight project management that
is combined with a team organization to encourage
and facilitate communication between teams in
different locations. Blueprint introduces important
adaptations to Scrum and Kanban to reduce unwanted
bureaucracy and to facilitate global software
Perkusich et al. (2013) [PS48] developed a
Probabilistic Model with Baysian Network. As the
name suggests, the model is a Bayesian network that
represents a software development project managed
in essence with the Scrum methodology. Scrum
Masters should use it to identify project issues and
guide the team to improve the project's chances of
The Diversity of Approaches to Support Software Project Management in the Agile Context: Trends, Comparisons and Gaps
success. The model produces data with probability
values that represent the current status of key project
factors. It should be used to identify problems and
prioritize areas for improvement. The prioritization of
areas for improvement should be a collaborative
activity and the model should only be used as a source
of information to guide the discussion.
The remaining studies that deal with some model
focus on project schedule management [PS34, PS36,
PS58]. In addition to the aforementioned studies,
there are those focused on risk management [PS27,
PS46], communication [PS25], scope [PS29],
stakeholders [PS55] and quality [PS59]. These same
studies still focus on different phases of the project,
such as: planning [PS25, PS46, PS58, PS59],
execution [PS36, PS55] and monitoring and control
[PS27, PS29].
4.2.5 Tool
Based on the selected studies, five tools were
identified that support the software projects
management. Table 5 presents these studies.
Table 5: Studies that present a “Tool” approach.
Studies that present a “Tool” approach
[PS18], [PS38], [PS42], [PS49], [PS63]
Vivian et al. (2015) [PS63] expose in their study
a Panel to View Online Teamwork Discussions. The
tool is a dashboard that extracts and communicates
the distribution of team roles and members' emotional
information in real time. The panel is composed of a
series of elements: team participation and distribution
of roles, team and individual sentiment analysis and
team and individual emotions. It provides real-time
analysis of teamwork discussions and visualizes team
members' emotions, the roles they have taken, and the
overall team sentiment during the course of a
collaborative project.
Mateescu et al. (2015) [PS42] present a tool called
aWall. It is an agile team collaboration tool for large
multi-touch wall systems. aWall was designed based
on empirical user research using new concepts of
interaction and visualization to support and promote
the highly collaborative and communicative agile
work style. The tool is based on web technology and
can be used both in co-located and distributed
environments. According to the study authors, the
tool can be crucial for agile teams, since the agile
process depends on intense interaction, collaboration
and constant open communication between team
members. The remaining studies that deal with tools
turned their attention to the monitoring and control of
the project schedule, and to the planning of the scope.
Fehlmann and Kranich (2017) [PS18], for example,
through a Bayesian Approach Burn-up Chart, were
able to provide estimates of how much additional
time is needed to complete the planned work.
4.2.6 Technique
Following what was verified regarding the tools, from
the selected studies, five techniques were also
identified that aim to support the software projects
management, as shown in Table 6
Table 6: Studies that present a “Technical” approach.
Studies that present a “Technique” approach
[PS33], [PS35], [PS41], [PS51], [PS60]
Stapel et al. (2011) [PS60] present Flow Mapping,
a technique of the FLOW Method to plan and guide
communication in distributed development projects.
To achieve these goals, the technique is centered on
the visualization of a FLOW map. A FLOW map is a
special FLOW model (i.e. visualization of project
participants, documents and information flows)
extended by features to improve awareness in
distributed teams. According to the authors, when
using the Flow Mapping approach, the
communication of a distributed project can be
planned in a working day.
Kroll et al. (2017) [PS35] used a Genetic
Algorithm-Based Assignment technique. The
technique was used to assign tasks in a global
software development (GSD) project. The technique
uses a queue-based GSD simulator to evaluate the
fitness function. Results based on a multiple case
study (applying the technique to data from three real-
world projects) show that the approach could be
better than project managers' task assignments.
4.2.7 Framework
Four studies present some framework that supports
the software projects management in agile context, as
can be seen in Table 7.
Table 7: Studies that present a “Framework” approach.
Studies that present a “Framework” approach
[PS19], [PS24], [PS32], [PS45]
Silva and Oliveira (2016) [PS19] developed an
Agile Project Portfolio Management Framework. The
framework refers to a flexible approach to portfolio
management, suggesting faster and more dynamic
meetings, focusing mainly on the interaction and
ENASE 2022 - 17th International Conference on Evaluation of Novel Approaches to Software Engineering
commitment of those involved in the process. Some
agile practices that can be used in each activity of this
framework are: planning portfolio management,
identifying new proposals, analyzing candidate
projects, composing the project portfolio and
monitoring portfolio.
Guerrero et al. (2019) [PS24] present Eagle, a
framework that supports a systematic way to define,
measure and visualize the practices of members of
software development teams following agile
principles. Specifically, the framework provides
microservices architecture based on the “Governify”
ecosystem for managing accordingly. The framework
provides an ecosystem of tools for organizations to
define their best practices to follow and track the
adherence of their teams and members in order to
learn about their pitfalls and improve the project over
Jain and Suman (2018) [PS32] expose in their
study on a project management framework for global
software development (GSD). The GSD Project
Management Framework, as the authors call the
approach, assimilates the knowledge areas of the
PMBOK with the knowledge areas necessary for an
effective management of the GSD. It would guide the
project manager on aspects to consider when
executing distributed projects. The presented
framework covers feasibility and risk management,
virtual team management, knowledge management,
scope and resource management, performance
management and GSD integration management.
4.2.8 Practice
As shown in Figure 4, practices were the least
identified types of approaches in the selected studies,
with a total of two studies that only address some of
them, as shown in Table 8.
Table 8: Studies that present a “Practice” approach.
Studies that present a “Practice” approach
[PS57], [PS65]
Schreiber et al. (2017) [PS57] discuss a practice
called Metrics Driven Research Collaboration
(MEDIATION). The practice aims to ensure that all
project participants have an ongoing common
objective: the success of the project. As per
established practice, the project team should focus on
the most important requirements and continually
verify that the software product conforms to the
defined scope and corresponding metrics. The
practice further establishes that the status, challenges
and progress of the project be transparent to all team
members at all times.
Zhang et al. (2020) [PS65] implemented a practice
called Fireteam, a practice that focuses on small
teams in the software industry. Fireteam is nothing
more than a teamwork style. The practice defines two
to five members to handle the division of labor and
coordination issues in traditional development teams.
Briefly, the practice aims to reduce project
management overheads and improve productivity,
through the institutionalization of the practice of
small teams throughout the organization, to solve
problems arising from human and social aspects, such
as friendship, talent, skill and communications.
4.3 Strengths and Limitations of Ap-
This section gives an overview of the main
advantages and disadvantages / limitations of the
approaches identified from the selected studies.
4.3.1 Strengths
When a researcher / developer proposes to develop a
certain approach, he is looking for some means that
help him to break specific barriers of the context in
which he is inserted. Regarding the approaches that
aim to support the software projects management,
identified from the selected studies, it is no different.
They all have some advantages and even though they
are, in some cases, different from each other, at the
end of the day they all have the same objective: to
efficiently support software development teams.
Some approaches, despite being virtual, try to be
as close as possible to the real world [PS38], as with
the tool developed by Liskin and Schneider (2012)
[PS38]. Likewise, the approaches identified always
try to reduce the effort required by the team to
complete a project task [PS34, PS56, PS58, PS59].
These approaches are considered robust enough to
identify problems in the project and correct them in
time, avoiding further damage to resources, schedule
and, consequently, to the project [PS48].
Also noteworthy are those approaches that
provide great ease in terms of planning
communications, as is the case of Flow Mapping
presented by Stapel et al. (2011) [PS60] that allows
communication planning in up to one day. In
addition, it has an approach that allows the reduction
of Sprint time, when working with Scrum, without the
project losing quality, even if the reduction is
minimal, as reported by Alhazmi and Huang (2018)
[PS01], and Kroll et al. (2017) [PS35].
The Diversity of Approaches to Support Software Project Management in the Agile Context: Trends, Comparisons and Gaps
4.3.2 Limitations
One of the points to take into account when we are
talking about any type of approach, whatever the
purpose it was developed for, are its limitations (now
called disadvantages). Limitations are inherent to any
work, especially when it comes to team-focused
approaches. Regarding software project management
approaches, there are a number of limitations
identified in some selected studies and that end up
extending to the others.
Initially, it was possible to observe that there is an
approach that focuses, among other things, on the
constant repair of the project and the work products
generated by it. However, the act of constantly fixing
defects can bring additional efforts to developers, as
reported by Tang (2008) [PS34]. There are also
approaches that rely entirely on solid and equal
commitment from all team members. If the team is
not 100% focused and committed, the project
naturally tends to fail [PS12, PS28, PS47, PS54], as
less engaged employees could perform activities
inappropriately, even with the help of the approach,
as Godoy et al. (2019) [PS22].
Some approaches are not so recommended for
planning a small number of tasks, as they were
developed to deal with large volumes of data, as with
the Sprint Planning Decision Support System
(SPESS), developed by Alhazmi and Huang (2018)
[PS01]. Other approaches do not constantly monitor
the project and this limits the team's view of the
progress of what is being developed, as Stapel et al.
(2011) [PS60].
With regard specifically to software, many
plugins that are developed to compose them end up
falling into disuse quickly, as is the case of plugins
developed for Redmine, reported in the study by
Dowling and McGrath (2015) [PS16]. For the
authors, while there is an active community of
developers working on Redmine and creating
valuable plugins, this is something of a double-edged
sword. That's because, plugins are not always
compatible with the latest versions, causing
headaches during the update and failures in
functionality of features that teams previously used.
4.4 Evaluating Approaches
This section presents the main ways used by the
authors of the selected studies to evaluate and validate
their approaches.
The way most used by the authors of the works to
evaluate their approaches was the case study, with a
total of 55 studies that used this method. Trapa and
Rao (2006) [PS61], for example, applied their
approach to a project called Cronos, where user
stories were divided into tasks and inserted into the
software. Each task was assigned to two developers
who were responsible for assigning the time estimate
for each task they were responsible for. After that,
reports were generated with information about the
project completion time and the impacts of the
additions of new functionalities that came to exist.
Some studies used questionnaires to obtain
feedback on the approach developed, five studies
more precisely. Bastarrica et al. (2017) [PS05]
formulated two research questions to identify the
advantages and disadvantages of using their
approach. Data collection involved a structured
questionnaire that was made available to the CEOs
and a technical professional from each company. The
purpose of the questionnaire was to capture actual and
desired practices in relation to project management.
Regarding observational assessments, a total of
three studies used this assessment method. We can
highlight the study by Mateescu et al. (2015) [PS42]
who, from the observation of the use of the proposed
approach, were able to identify positive points and
points for improvement, as well as conclusions about
how efficient the proposed approach can be in a
project. The authors verified that aWall takes
advantage of the resolution of web technology and
thereby surpasses the possibilities of existing desktop
tools. They noted that each agile meeting has its main
task and specific objective, but also needs various
supporting information and artifacts.
Finally, two studies conducted internal
evaluations, that is, the developers of the approaches
themselves evaluated them based on their own
metrics, without necessarily having made the
approaches available to third parties. Bruegge et al.
(2009) [PS11] evaluated the feasibility and
performance of their approach from two classification
experiments. The first experiment classified the tasks
according to the activity to which they belonged. In
the second experiment, the approach was employed
to classify the status of tasks, that is, the machine
learning engine predicts whether these tasks have
already been completed or not.
This section presents our main conclusions and
impressions of the results presented in Section 4.
The first item to note refers to the results on which
areas and phases of project management the
approaches emphasize. As illustrated in Figure 2, the
ENASE 2022 - 17th International Conference on Evaluation of Novel Approaches to Software Engineering
areas of schedule, quality and communication are the
areas that received the most attention from the
authors. Something similar can be observed in
(Carvalho et al., 2020). The authors identified,
through an opinion survey with software project
managers, that the areas of schedule and
communication are the two areas that these
professionals are most concerned about.
Specifically on the schedule, the area most
emphasized in the studies, it was possible to observe
that the focus in this area is given by the fact that
estimating the time and the project schedule are
crucial tasks and extremely influence the project
results (Zhang and Jin, 2020). Regarding the phases,
it was observed that the authors give greater emphasis
to project planning. That is because planning is
crucial to the success of a project. Tasks need to be
allocated to team members, taking into account task
precedence, balancing the workload of team
members, and ensuring quality (Lin et al., 2014).
Regarding the type of approach, it was possible to
verify that software is the most commonly used type
of approach to support the software projects
management. Results like this can be considered
common, considering that currently several systems
that automate processes are becoming more and more
commonplace. Such systems facilitate the work of
people in different fields of application (Uspenskiy et
al., 2019). Shaikh et al. (2018) also state that project
management software is widely used because it
includes several useful features that facilitate the
work of the team, especially the project manager,
features such as task management, real-time
monitoring, chatbox, notifications and alerts.
In addition to software, project management
methodologies also stood out. During the analysis of
the selected studies, it was possible to identify 12
studies that deal with this type of approach. Among
these methodologies, one that stands out is Scrum.
This methodology was used directly in four studies
[PS12, PS28, PS47, PS54] and indirectly, through
adaptations, in two studies [PS04, PS07]. One of the
reasons for this is that Scrum teams are the most
important factors in improving the performance of a
project's success. Like any agile development
method, Scrum follows a collaborative and guided
approach to software development, reflecting the
principles of the Agile Manifesto (Michael et al.,
Something that caught our attention when
analyzing the studies was how the approaches focus
on team commitment and engagement. However, as
reported in Subection 4.3.2, some approaches impose
a process of constant communication and interaction,
using these items as a way of evaluating the
performance of team members. However, care must
be taken with this particular issue, as there are
approaches that can give the false impression that a
collaborator is not helping or not engaged in the
project. This is because this type of approach is based
on and draws its conclusions from constant
interactions. However, not always someone who
helps in the project interacts as often, but can
contribute with more technical information [PS63].
Still on the limitations, it was found that some
approaches are not recommended to plan a small
number of tasks, as they were developed to deal with
large volumes of data. In this case, the ideal is for the
organization to invest in tools that constantly monitor
it, especially when dealing with a large-scale project
Regarding the evaluations of the approaches
conducted by the authors, it was possible to notice a
considerable rate of studies that used the case study
as a form of evaluation, a rate that corresponds to 86%
of the analyzed studies. This rate allows us to verify
that this type of evaluation manages to generate more
satisfactory and more reliable results, as the approach
is submitted to a real environment and from its use,
data are extracted that allow the planning and conduct
of improvements, in addition to the reduction of
possible limitations that the approach may present.
Based on the results listed and described in this
paper, it is possible to state that, although there was a
drop in the number of studies in the years 2020 and
2021 (the latter year justified by being the year of
conducting this SLR), there is an interest in part of
academia and industry to develop research aimed at
managing software projects, especially research that
focuses on approaches that aim to facilitate this
This section discusses potential threats to the validity
of this study and actions taken to address validity
issues. We used the structure proposed by Wohlin et
al. (2000).
6.1 Construct Validity
To minimize the risk that the SLR would not bring the
studies that answered the research questions, a test
was carried out with the search string. Four studies
that proved to meet the research objectives were
manually selected and then it was verified if, when
The Diversity of Approaches to Support Software Project Management in the Agile Context: Trends, Comparisons and Gaps
running the string in the bases, these same studies
would return, which in fact happened.
6.2 Internal Validity
During the extraction process, studies were ranked
based on our judgment. Studies that depend on the
judgment of the authors can carry with them a bias
that needs to be mitigated as much as possible. With
that in mind, throughout the study analysis process,
weekly meetings were held to discuss and reach a
consensus on which studies should really be selected.
6.3 External Validity
It is possible that SLR does not return all relevant
studies on approaches that support software project
management. To mitigate this risk, we identified and
relied on studies similar to this one so that it was not
started from scratch.
6.4 Conclusion Validity
To ensure the conclusion validity of our study, we
present throughout Section 4 charts and tables
exposing the results generated directly from the data
and we discuss the observations and explicit trends.
This ensures a high degree of traceability between
data and conclusions. In addition, our corpus of
studies is available to other researchers. Furthermore,
the SLR process was carried out with the support of a
PhD professor who has extensive experience in
studies of this genre, with several publications in
software engineering.
This section presents similar studies that are directly
or indirectly related to the investigation of the present
study. Despite all efforts, we did not find secondary
studies that searched the literature on approaches to
support software project management in agile
context. However, there are secondary studies that
explore other aspects of software project
Couto et al. (2021) conducted research consisting
of a systematic literature mapping (SLM) and a
survey, with the objective of identifying visualization
approaches that could help in the software projects
management. As a result, the authors identified 16
visualization approaches that meet the research
objectives. Finally, based on the identified
approaches, the authors proposed an extension of the
PMBOK, adding two more processes, namely: "Plan
Data Visualization" and "Implement Data
El Bajta et al. (2018) performed an MSL to
identify and classify studies on software project
management approaches in the context of global
software development. The authors identified, from
the analysis of 84 articles, the strengths and
weaknesses of each approach and analyzed their
applications in the industry. The results obtained in
the work indicate that the interest in software project
management for the GSD has increased since 2006. It
was also found that the most frequently reported
methods (40%) are those used for coordination,
planning and monitoring, together with with time and
cost estimation techniques.
As can be seen in the studies described above,
they are not focused on the same context, nor on the
same objective of this SLR. However, we believe that
they serve as a basis for our work as they focus on
software project management or part of it, as is the
case of Vieira et al. (2020) that focus only on project
risk management. Therefore, this work is unique in
that it explicitly deals with software project
management approaches in agile context, focusing
not only on one type of approach and not only on an
area or phase of the project, but covering it as a whole.
This study described an SLR to identify approaches
that support the software projects management in
agile context. We selected 65 primary studies, from
2004 to 2021. Of these, 22 studies address approaches
focused on project schedule management and 36
studies are focused on the planning phase.
We observed that software is the most common
approach among all the others, being identified in a
total of 15 studies, followed by the methodologies
that appear in 12 studies. We found some positive
points related to the use of these approaches, such as:
reducing the effort required by the team, provide
greater ease in terms of communications planning and
reduce Sprint time when working with Scrum. In
addition, we identified some negative points, as we
can highlight: there are approaches that fully depend
on an equal commitment of all team members and
there are approaches that require many tasks in the
initial phase of the project.
From the results, it was possible to verify how
important and how project management approaches
are for the development of software with more
quality, in addition to being able to see some
ENASE 2022 - 17th International Conference on Evaluation of Novel Approaches to Software Engineering
limitations that still need to be mitigated, which
therefore gives opportunities to researchers in the area
to develop further in the area. In this line, we plan as
future works to apply a survey to software project
managers who work in industry and / or academia to
verify if what is being presented in the literature is
being used in organizations and, finally, apply
Grounded Theory to build one or more theories about
the main advantages and disadvantages of using the
approaches identified in the survey.
The authors would like to thank the Coordination for
the Improvement of Higher Education Personnel
(CAPES) in Brazil for the financial support for the
granting of a scholarship for a master's degree.
Banica, L., Hagiu, A., Bagescu, A., Gherghinescu, A.
(2018). Designing A Website for A Recruitment
Agency with Pmbok Methodology. Scientific Bulletin-
Economic Sciences, 17(1), 60-67.
Basili, V. R. (1992). Software modeling and measurement:
the Goal/Question/Metric paradigm.
Carvalho, E. C., Malcher, P. R. C., & Santos, R. P. (2020).
A Survey Research on the Use of Mobile Applications
in Software Project Management. In SBQS'20: 19th
Brazilian Symposium on Software Quality.
Couto J., Kroll J., Ruiz D. and Prikladnicki R. (2021). A
PMBoK Extension Proposal for Data Visualization in
Software Project Management.In Proceedings of the
23rd International Conference on Enterprise
Information Systems - Volume 2: ICEIS, ISBN 978-
989-758-509-8, pages 54-65. DOI: 10.5220/0010454
El Bajta, M., Idri, A., Ros, J. N., Fernandez-Aleman, J. L.,
Carrillo de Gea, J. M., Garcia, F., & Toval, A. (2018).
Software project management approaches for global
software development: a systematic mapping study.
Tsinghua Science and Technology, 23(6), 690–714.
Gomes, J., Romão, M. (2016). Improving Project Success:
A Case Study Using Benefits and Project Management.
Procedia Computer Science, 100, 489–497.
Kitchenham, B., Charters, S. (2007). Guidelines for
performing systematic literature reviews in software
Kostalova, J., Tetrevova, L., Svedik, J. (2015). Support of
Project Management Methods by Project Management
Information System. Procedia - Social and Behavioral
Sciences, 210, 96–104.
Lin, J., Yu, H., Shen, Z., Miao, C. (2014). Studying task
allocation decisions of novice agile teams with data
from agile project management tools. In ASE '14:
ACM/IEEE International Conference on Automated
Software Engineering.
Michael, D., Dazki, E., Santoso, H., R. Indrajit, E. (2021).
Scrum Team Ownership Maturity Analysis on
Achieving Goal. In 2021 Sixth International
Conference on Informatics and Computing (ICIC).
Paasivaara, M., Lassenius, C. (2011). Scaling Scrum in a
Large Distributed Project. In 2011 5th International
Symposium on Empirical Software Engineering and
Measurement (ESEM).
Parsi, N. (2021). The Next Agile Awakening: Four Agile
Leaders Discuss New Possibilities in a World of
Sudden Change. PM Network, 35(3), 36–43.
Petersen, K., Vakkalanka, S., Kuzniarz, L. (2015).
Guidelines for conducting systematic mapping studies
in software engineering: An update. Information and
Software Technology, 64, 1–18.
PMBOK Guide. (2017). Project management body of
knowledge (pmbok® guide). In Project Management
Retnowardhani, A., Suroso, J. S. (2019). Project
Management Information Systems (PMIS) for Project
Management Effectiveness: Comparison of Case
Studies. In 2019 International Conference on Computer
Science, Information Technology, and Electrical
Engineering (ICOMITEE). IEEE.
Shaikh, T. H., Khan, F. L., Shaikh, N. A., Shah, H. N., &
Pirani, Z. (2018). Survey of Web-Based Project
Management System. In 2018 International
Conference on Smart Systems and Inventive
Technology (ICSSIT).
Shrivastava, S. V., Rathod, U. (2017). A risk management
framework for distributed agile projects. Information
and Software Technology, 85, 1–15.
Uspenskiy, M. B., Smirnov, S. V., Loginova, A. V., &
Shirokova, S. V. (2019). Modelling of Complex Project
Management System in the Field of Information
Technologies. In 2019 III International Conference on
Control in Technical Systems (CTS).
Varajão, J., Colomo-Palacios, R., Silva, H. (2017). ISO
21500:2012 and PMBoK 5 processes in information
systems project management. Computer Standards &
Interfaces, 50, 216–222.
Vieira, M., C. R. Hauck, J., Matalonga, S. (2020). How
Explicit Risk Management is Being Integrated Into
Agile Methods: Results From a Systematic Literature
Mapping. In SBQS'20: 19th Brazilian Symposium on
Software Quality.
Wohlin, C., Runeson, P., Höst, M., Ohlsson, M. C.,
Regnell, B., Wesslén, A. (2000). Experimentation in
Software Engineering. Springer US.
Yanow, S. K., Good, M. F. (2020). Nonessential Research
in the New Normal: The Impact of COVID-19. The
American Journal of Tropical Medicine and Hygiene,
102(6), 1164–1165.
Zhang, S., Jin, L. (2020). Research on Software Project
Schedule Management Method based on Monte Carlo
Simulation. In 2020 IEEE 5th Information Technology
and Mechatronics Engineering Conference (ITOEC).
The Diversity of Approaches to Support Software Project Management in the Agile Context: Trends, Comparisons and Gaps