International Journal of Scientific and Research Publications, Volume 7, Issue 6, June 2017
ISSN 2250-3153
333
Software Project Planning with Tracking and Oversight
Aregbesola, Moses Kehinde
Department of Mathematics and Computer Science, Elizade University, Ilara-Mokin, Ondo State, Nigeria
Abstract- Software project management has been identified as
a major determinant factor of software project’s success or
failure. Software Project Planning (SPP) and Software Project
Tracking and Oversight (SPTO) have equally been identified as
two key process areas in software project management at
maturity level 2 of the SEI CMMI. Following the need for
consistent software process improvement in software industries
world-over, especially as it concerns software project
management, this study focused on evaluating the current level
of performance of the two identified KPAs, SPP and SPTO in the
software industry. Besides a broad review of literature, a study
was conducted covering 30 software companies in the Nigerian
geographical area. The study employed both the survey and the
action research approaches with some of the companies selected
as case studies for further appraisal. The study revealed some
level of strength in the performance of the practices associated
with SPP and SPTO in the Nigerian software industry. The
results of the study were consistent with findings of earlier
studies in enterprises whose maturity levels at the time of study
were similar to that of the Nigerian software industry. Several
recommendations were given for improving the performance of
the practices associated with SPP and SPTO key process areas in
particular, and software project management in general.
Index Terms- Software Project Planning, SPP, Software
Project Tracking and Oversight, SPTO, Nigeria Software
Companies, Software Industry, CMMI, Key Practice Area, KPA,
Capability Maturity Model Integration, Software Process.
I. INTRODUCTION
N
an and Harter (2009) described software project
management as the art and science of planning,
coordinating and providing leadership for software projects. In
order to be successful, organizations usually need effective and
efficient project plans to help manage and possibly bring down
the overall cost of software development. Typically, as a project
increases in size, so thus the accompanying complexity, thereby
further intensifying the need for thorough planning. A number of
studies have shown that a large percentage of project failures
were as a result of poor project planning. For instance, Ding and
Jing (2003) in their study reported that in China, more than 40
percent of failed software projects were unsuccessful because of
ineffective planning of human resources and project tasks. Chang
et al. (2008) explained that the main reason for this was that
unlike other projects, software project activities were peopleintensive and that the related resources were mostly human
resources. Meanwhile, the human resource allocation had already
been described as a complex task. Kurien and Nair (2014)
therefore puts forward that since cost and time are the significant
dynamics in software projects, effective tools for managing these
factors could create more room for success. An effective
planning tool was considered important because an effective plan
maximizes the overall cost and time required for a software
project. Some of the project management techniques that have
been applied in software project planning include the critical path
method (CPM), the program evaluation and review technique
(PERT), and the resource-constrained project scheduling
problem (RCPSP) model (Shtub, Bard and Globerson, 2005). For
calculating project workload and cost, as well as deciding project
schedule and resource allocation, the COCOMO model (Chen
and Zhang, 2013) is the model commonly employed.
Software Project Planning (SPP) and Software Project
Tracking and Oversight (SPTO) also known as Project
Monitoring and Control are two closely knit key process areas
(KPA) at maturity level 2 of the Software Engineering Institute
(SEI) Capability Maturity Model Integration (CMMI). The SEI
CMMI maturity level 2 (Managed) is the maturity level that lay
emphasis on software project management. As has already been
described, SPP which is closely knit with SPTO play very pivotal
roles in the software project management process. A software
development plan, the output from the SPP KPA, is a
prerequisite for SPTO (Paulk et al., 1993). The established plans
from the SPP KPA are the necessary foundation for managing
the software project, as described in the SPTO KPA.
The Software Engineering Institute upgraded their
capability maturity model (CMM) with the CMMI in 2001
(CMMI Product Team, 2006). The CMM Integration was
designed to address the problem of using multiple CMMs.
CMMI is an outstanding process maturity framework, made up
of 5 maturity levels, for practical organizations that desire to
accomplish higher levels of performance in their activities
(Hurst, 2017; Glover and Dennie, 2017; O’Neill, 2017).
Although software is excluded from the titles and from the topics
within the five levels of the CMMI because the CMMI
encompasses a broader process-orientation, the current study is
however focused on software and therefore includes software in
its titles.
It is expected that findings from the current study will
provide insight to software organizations across the globe about
the current state of their software development process with
regards SPP and SPTO. It is equally expected that these findings
would endear software enterprises towards higher levels of
performance in trying to achieve significant improvement in their
software development processes. In addition, although a number
of studies have examined software development processes from
different perspectives, none of them have focused on examining
the SPP and SPTO KPAs in the Nigerian context. The current
study examined the level of performance of the SPP and SPTO
practices in the Nigerian software industry based on results
www.ijsrp.org
International Journal of Scientific and Research Publications, Volume 7, Issue 6, June 2017
ISSN 2250-3153
obtained from some randomly selected software companies
within its geographical space.
II. RELATED WORKS
Although a number of studies have focused on software
development companies in Nigeria including Soriyan, Mursu and
Korpela (2000), Soriyan and Heeks (2004), Akinola, Osofisan
and Akinkunmi (2009), Aregbesola and Akinkunmi (2010a;
2010b), Aregbesola et al. (2011), Aregbesola and Onwudebelu
(2011), Akinola and Osofisan (2011), Aregbesola and Oluwade
(2014), and Aregbesola (2017a; 2017b; 2017c; 2017d), none of
them have actually examined the Software Project Planning
(SPP) and Software Project Tracking and Oversight (SPTO) key
process areas (KPA). This section of the study reviewed similar
studies related to SPP and SPTO KPA. This section has been
divided into two subsections, one for each of the discussed
KPAs, SPP and SPTO.
1.1. Software Project Planning
Software Project Planning (SPP) is aimed at establishing
reasonable plans for accomplishing the software engineering
goals and for managing of the software project. It involves
coming up with estimates for the work to be carried out,
establishing the necessary commitments, and outlining the plan
to get the work done (Paulk et al., 1993). Typically beginning
with the statement of work to be performed, SPP is usually
guided by the practices of Requirements Management KPA
(Aregbesola, 2017a). SPP involves iterating through a number of
activities for estimating the size of the software work products as
well as the needed resources. It also involves producing a
schedule, identifying possible risks, assessing the risks, and
negotiating commitments. The established plan forms the basis
for executing and managing the events of the software project's
activities and addressing the commitments to the software
project's customer on the basis of constraints, resources, and
software project capabilities. Paulk et al. (1993) further
explained that the established plans are the necessary foundation
for managing the software project, as described in Software
Project Tracking and Oversight.
Software Project Management (SPM) which is one of the
primary factors to software success or failure cannot be
effectively implemented without realistic plans. Since SPM has
been a bottleneck in software engineering, with software project
planning being one of its most critical activities, a number of
approaches have been developed and applied with the purpose of
improving its project planning practices. For instance, Han et al.
(2015) applied an improved Max–Min Ant System algorithm to
Software Project Planning to develop an appropriate worker-task
assignment in a software project with the aim of maximizing cost
and minimizing duration. The resulting model for software
project planning made use of three important resources, namely
tasks, employees, and skills. While the tasks were the jobs
needed to complete the project, the employees were the workers
with the requisite set of skills for performing the tasks. The
developed model could make a suitable allocation of tasks to
employees based on their skill sets. The experimental results
from the study with regards selected projects yielded feasible
solutions for optimum cost and duration as well as generating the
334
appropriate PERT Graph and Gantt chart of the software project,
thus improving the software project management process.
Rosso-Llopart (2005) discussed the goal of SPP to involve
the establishment of a pragmatic strategy for controlling,
tracking, and monitoring a complex technical project. The
established strategy must deal with the project’s complexity
which is heavily influenced by past experience of the practitioner
and has a strong effect on the project’s overall outcome. It must
also address the project’s size which typically increases in
parallel with the interdependence of the different project
elements. Finally, the established strategy must equally deal with
the degree of structural uncertainty, which is the degree to which
requirements are solidified, as well as the ease of functional
decomposition. The study equally highlighted the need to watch
out for “scope creep” which is a concept that occurs when
customers change requirements mid-cycle. Putting all these
together, the overarching aim of project planning is to guarantee
that the final result is finished on time, within budget, and exudes
quality.
The software engineers, software managers, and other
stakeholders involved in the software project planning are
usually trained in the software estimating and planning
procedures which are applicable to their assigned tasks. Paulk et
al. (1993) identified the three goals of software project planning
to include: documenting software estimates used in planning and
tracking the software project; planning and documenting
software project activities and commitments; and stakeholders
agree to their commitments related to the software project. Some
of the commitments made in software project planning include:
Designation of a project manager to be responsible for
negotiating commitments and developing the project's software
development plan and; The software project follows a written
organizational policy for planning a software project. For
software project planning to be most effective, it must be
initiated at the early stages of the overall project planning process
and in parallel with it.
Han et al. (2015) explained that project plan development
typically involves activities with tasks; cost estimation and;
schedule with a completion finish date. I addition, SPP typically
involves Risk Management, which comprises the anticipation of
potential problems, mitigating or avoiding the problems, and
tracking existing and potential problems. SPP also involves
incremental release process model providing periodic
demonstrations, reaching short-term goals, and checking progress
towards long-term goals. Three general software project planning
approaches were equally identified to include past experience,
standard guidelines, and support tools. It was observed that
experienced managers depended on their past experiences as well
as the experiences of successful managers in creating plans.
Documentations of past completed projects are usually adopted
as models for project plans. A number of studies including those
of requirements Alba and Chicano (2007), Chang et al. (2001;
2008), and Xiao, Ao and Tang (2013) reiterated that software
project planning among other things consists of establishing a
worker-task schedule for a software project. It was emphasized
that employee skills and remunerations should be considered in
assigning them to project tasks on the basis of task requirements.
1.2. Software Project Tracking and Oversight:
www.ijsrp.org
International Journal of Scientific and Research Publications, Volume 7, Issue 6, June 2017
ISSN 2250-3153
Software Project Tracking and Oversight (SPTO) is aimed
at establishing adequate visibility into the projects progress,
enabling management to respond effectively when the
performance of the software project diverges considerably from
the software project plans. A software development plan, the
output from the activities of the Software Project Planning KPA,
is a prerequisite for Software Project Tracking and Oversight
(Paulk et al., 1993). The SPTO at the CMMI maturity Level 2
emphasizes tracking the project and taking necessary corrective
actions. This is more or less of a reactionary approach on the part
of management to the actual problems. This reactionary approach
is much unlike the proactive approach of the Integrated Software
Management KPA (Aregbesola, 2017b) at maturity level 3, a
higher maturity level of the SEI CMMI maturity scale. This is
because at maturity level 3, the software process of the project is
completely defined with well-established relationship among the
different activities, tasks and work products of the software
project. SPTO involves tracking and reviewing the software
achievements and outcomes against documented plans,
estimations, and commitments, and making necessary
adjustments based on the projects current accomplishments
(Nalbant, 2004; Olson, Reizer and Over, 1994; Nair and
Annamalai, 2013). Progress is typically determined by making
comparisons between the values in the documented plan and the
actual software cost, schedule, size, and effort at selected
milestones and when selected software work products are
completed (Paulk et al., 1993; Hjalmarsson, 2013; Futrell, Shafer
and Safer,2002). Corrective actions are taken when it becomes
obvious that the software project's plans are not being met. Such
corrective actions may typically include adjusting the software
development plan to reflect the actual accomplishments or taking
steps to improve the project performance or making adjustments
to the remaining tasks (Amid and Moradi, 2013; Alwin, 2001;
Dreon, 2000; Paulk et al., 1993; Olson et al. 1993).
The General Accounting Office (1999) in studying their
organization observed that no software quality assurance group
existed, and that there were therefore no reviews and/or audits of
the activities and work products for SPTO. A weak performance
was equally observed for a large portion of the KPAs associated
with SPTO. As such, it was further explained that effective
SPTO among other things should include: Designation of a
project software manager who will be responsible for the
project’s software activities and outcomes; Establishment of a
documented software development plan on the basis of which
status monitoring and tracking of software activities are
performed; Establishment
and adherence to written
organizational policy for managing projects; Periodic reviews of
current project status and accomplishments against the software
development plan; Tracking all risks associated with the software
project; Explicit assignment of responsibility for software
activities and work products; Keeping track of the sizes of the
software work products or accompanying changes and making
335
necessary modifications as required and; Regular review of the
SPTO activities with senior management.
As a result of its high level of relevance, SPTO as a process
area is common to a majority of the software process
improvement models and plays a significant role aimed at
delivering quality products within budget and schedule. The
work of Baruah, Ashima and Barbaruah (2013) discussed various
software process models developed to help different software
organization compete favorably in the changing market
environment and produce quality product. The focus was on
exploring the methods commonly employed in SPTO in different
small and medium scale enterprises in India. The different
software models that were studied included the Capability
Maturity Model CMM (Paulk et al., 1993), CMM Integration
(CMMI Product Team, 2006), Personal Software Process PSP
(Humphrey, 2005), Team Software Process TSP (Davis and
McHale, 2003), Six Sigma (Brue and Launsby, 2003; Eckes,
2001), People Capability Maturity Model PCMM (Vakaslahti,
1997), ISO 9000 (Stelzer, Mellis and Herzwurm, 1997), ISO
9001:1994 (TickIT, 1995), ISO/IEC 12207 (Singh, 1996), SPICE
(Rout and Terence , 1995), BOOTSTRAP (Kuvaja, 1994), IEEE
1220 (Doran, 2006), IDEAL model (Gremba and Myers, 1997),
Process Improvement for Small to Medium Enterprises PRISMS
(Allen, Ramachandran and Abushama, 2003), K-model (Hwang,
2010) and TRISO (Li, 2007).
Although the study of General Accounting Office (1999)
revealed that the projects evaluated exhibited some level of
SPTO practice strengths (such as the documentation of software
development plans and the respective designation of
responsibilities to a project software manager), the projects
collectively had many weaknesses. One of the significant
weaknesses identified was that none of the projects studied
followed a written organizational policy for managing the
software projects. This increases the risk of key tracking and
oversight activities not being performed as effectively as
required. As observed in the study, the increased risk was evident
in the project manager’s failing to: periodically review project
status and accomplishments against the software development
plan; track all risks associated with the software project;
explicitly assign responsibilities to individuals for software
activities and work products; keep track of the sizes of the
software work products or accompanying changes and making
necessary modifications as required, and regularly review the
SPTO activities with senior management. To further buttress the
points raised, Table 1 which is from the study of Lowe and Cox
(1996) shows the assessment results from the SPTO KPA at
some point in Hewlett-Packard’s journey towards its attainment
of the SEI CMM maturity Level 2, a level which it has however
since surpassed. The results in Table 1 show a combined average
of 54.2% for both full and partial performance of the listed
practices.
www.ijsrp.org
International Journal of Scientific and Research Publications, Volume 7, Issue 6, June 2017
ISSN 2250-3153
336
Table 1: Assessment results for the software project tracking and oversight key process area.
Table I
Assessment Results for Software Project
Tracking and Oversight
Percent of Survey
Respondents
Survey Questions
Fully
Partial
Not
Are the project’s planned activities and deliverables tracked (e.g., schedule, effort,
and tests)?
43
24
33
Are the actual results compared to your estimates throughout the project?
10
19
71
If there is a variance, does someone take corrective action or explain why the
variance has occurred?
14
38
48
Are changes to the activities, deliverables, and schedule discussed with the people
who will be affected?
19
58
23
Does someone review the project results regularly with your section and lab
managers?
18
18
64
Source: Lowe and Cox (1996)
III. RESEARCH METHODOLOGY
A survey on the level of performance of the different
practices associated with the Software Project Planning (SPP)
and the Software Project Tracking and Oversight (SPTO) key
process areas was conducted. The research was performed on 30
software companies within the federal republic of Nigeria using
an abridged version of the verified SEI Maturity Questionnaire
(Zubrow et al., 1994). The abridged version of the SEI Maturity
Questionnaire was adopted as the research instrument for
eliciting required information for the study. The questionnaire
consisted of two major sections. The first sections comprised of
questions regarding software process key practices within the
organisation. The second section which was the response section
consisted of four response options namely “Yes”, “No”, “NA”
for Not Applicable and “DK” for Don’t Know. These four
options were the possible responses available to each respondent
with regards to the organizations performance of the respective
key practices in the given section. A total of twenty six (26) (i.e.
86.67%) of the 30 selected companies eventually participated in
the study.
Further studies, using the action research approach, was
carried out on some of the selected companies to ascertain the
veracity of the collected data. A direct observation and actual
participation in the organizational software development
activities were adopted as a means of getting firsthand
information about the practices of some of the organizations, and
thereafter reconciling such information with the collected data.
Measurement of process-related phenomena was also performed.
Print and electronic documentation were equally explored as
sources of useful details about the companies and their
operations. Both structured and unstructured interviews were also
employed in the information elicitation process.
IV. RESULTS
The results of the current study are as shown in Tables 2
and 3, and equally graphically represented as depicted by Figures
1 and 2. The results are presented in percentages of actual
responses. The averages for each response option are shown in
bold at the last row of each table. Discussions and resultant
conclusions from these results are presented in the subsequent
sections.
Table 2: Key Practices of the Software Project Planning (SPP) KPA
Key Practices
Responses
Yes %
No %
NA %
DK
%
a.
Are estimates (e.g., size, cost, and schedule) documented for use in
planning and tracking the software project?
92.31
7.69
0.00
0.00
b.
Do the software plans document the activities to be performed and
the commitments made for the software project?
61.54
19.23
11.54
7.69
www.ijsrp.org
International Journal of Scientific and Research Publications, Volume 7, Issue 6, June 2017
ISSN 2250-3153
337
c.
Do all affected groups and individuals agree to their commitments
related to the software project?
53.85
46.15
0.00
0.00
d.
Does the project follow a written organizational policy for planning
a software project?
7.69%
65.38
7.69
19.23
e.
Are adequate resources provided for planning the software project
(e.g., funding and experienced individuals)?
26.92
57.69
15.38
0.00
f.
Are measurements used to determine the status of the activities for
planning the software project (e.g., completion of milestones for the
project planning activities as compared to the plan)?
69.23
23.08
3.85
3.85
g.
Does the project manager review the activities for planning the
software project on both a periodic and event-driven basis?
80.77
15.38
0.00
3.85
Average:
56.04
33.52
5.49
4.95
100.00%
90.00%
80.00%
70.00%
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
Yes
No
NA
DK
DK
NA
No
Yes
a.
b.
c.
d.
e.
f.
g.
Figure 1: Performance against Key Practices of the Software Project Planning (SPP) KPA
Table 3: Key Practices of the Software Project Tracking and Oversight (SPTO) KPA
Key Practices
Responses
Yes %
No %
NA %
DK
%
a.
Are the project’s actual results (e.g., schedule, size, and cost)
compared with estimates in the software plans?
46.15
19.23
15.38
19.23
b.
Is corrective action taken when actual results deviate significantly
from the project’s software plans?
69.23
26.92
3.85
0.00
c.
Are changes in the software commitments agreed to by all affected
groups and individuals?
53.85
19.23
23.08
3.85
d.
Does the project follow a written organizational policy for both
26.92
57.69
0.00
15.38
www.ijsrp.org
International Journal of Scientific and Research Publications, Volume 7, Issue 6, June 2017
ISSN 2250-3153
338
tracking and controlling its software development activities?
e.
Is someone on the project assigned specific responsibilities for
tracking software work products and activities (e.g., effort, schedule,
and budget)?
65.38
19.23
15.38
0.00
f.
Are measurements used to determine the status of the activities for
software tracking and oversight (e.g., total effort expended in
performing tracking and oversight activities)?
76.92
15.38
7.69
0.00
g.
Are the activities for software project tracking and oversight
reviewed with senior management on a periodic basis (e.g., project
performance, open issues, risks, and action items)?
73.08
15.38
3.85
7.69
Average:
58.79
24.73
9.89
6.59
80.00%
70.00%
60.00%
Yes
50.00%
No
40.00%
NA
30.00%
DK
20.00%
DK
NA
No
Yes
10.00%
0.00%
a.
b.
c.
d.
e.
f.
g.
Figure 2: Performance against Key Practices of the Software Project Tracking and Oversight (SPTO) KPA
V. DISCUSSION
The results shown in Tables 2 and 3, which are graphically
depicted by the charts in Figures 1 and 2 show relatively high
degrees of performance of the practices associated with the
Software Project Planning (SPP) and Software Project Tracking
and Oversight (SPTO) KPAs, with the performance of the
practices associated with SPTO being somewhat better than the
performance of the practices associated with SPP. These
performances are quite remarkable considering that both KPAs
are associated with software process CMMI maturity level 2
(Managed) while the Nigerian software industry has been said to
be at maturity level 1 according to the studies of Aregbesola and
Akinkunmi (2010a; 2010b), Aregbesola et al. (2011), Aregbesola
and Onwudebelu (2011), and Aregbesola and Oluwade (2014).
Of course, results from the studies never implied that there were
no software companies within the country with higher maturity
levels. Therefore, software companies within the country with
higher maturity levels could have accounted for the high
performances experienced in the practices associated with both
KPAs despite the industry average. In a similar study carried out
by General Accounting Office (1999), it was equally revealed
that the projects evaluated exhibited some level of strengths in
their SPP and SPTO practices, despite the fact that the
organizations were obvious yet to attain the CMMI maturity
level 2.
The results obtained in the current study were equally
somewhat similar to those of Lowe and Cox (1996) especially
with regards to the performance of the practices associated with
SPTO. While Lowe and Cox (1996) recorded a 54.2%
performance of these practices, the current study recorded 58.8%
performance of similar set of practices. The similarities in the
results of both studies were quite consistent with expectations
because the enterprise under study in Lowe and Cox (1996) were
equally on their journey towards the SEI CMMI maturity level 2
at the time.
Establishing and adhering to written organizational policy for
planning, tracking and controlling software development
activities and projects were major weaknesses for most of the
www.ijsrp.org
International Journal of Scientific and Research Publications, Volume 7, Issue 6, June 2017
ISSN 2250-3153
organizations. Formal documentation of an organizational policy
for SPP and SPTO was a major weakness across board. This
observation was equally consistent with that of General
Accounting Office (1999) which stated that one of the significant
weaknesses identified in its study was that none of the projects
studied followed a written organizational policy for managing the
software projects. It was equally stated that this increased the risk
of key tracking and oversight activities not being performed as
effectively as required. It is therefore easy to see that although
the performance of both KPA considered in this study can be
said to be relative okay, the need still exists for significant
improvement.
REFERENCES
[1]
[2]
[3]
[4]
[5]
VI. CONCLUSION
Considering that more than 40 percent of failed software
projects have been said to be unsuccessful because of ineffective
planning of human resources and project tasks, and that the
reason for this was that unlike other projects, software project
activities were people-intensive and that the related resources
were mostly human resources; it therefore becomes imperative
that training and retraining of the human resources is given
utmost diligence. Also, considering that human resource
allocation has been identified as a complex task, it behooves
senior management to support the project manager in acquiring
effective methodologies and software tools for managing
resource allocation along SPP and SPTO, thereby maximizing
cost and time.
Proper documentation of the entire software process and
securing stakeholder’s commitment have equally been identified
as key factors that must be given kin consideration when it
comes to SPP and SPTO. Besides the software project following
a written organizational policy for SPP and SPTO, another
commitment that is an absolute necessity for success in these
KPAs is the designation of a project manager to be responsible
for negotiating commitments and establishing the project's
software development plan. The appointment of a project
manager is an absolute necessity because he would be
responsible for the majority of all the other commitments. For
software project planning to be most effective, it must be
initiated at the early stages of the overall project planning process
and in parallel with it.
The current study focused on Software Project Planning
(SPP) and Software Project Tracking and Oversight (SPTO).
Existing works on the two KPAs were reviewed and research
result on the level of performance of both KPAs in the Nigerian
software industry was equally presented. By using survey and
action research methods, it was shown that the performance of
the practices associated with the two KPAs was relatively strong
in the Nigerian software industry. There however still exists
plenty of room for improvement in the performance of the
practices in the KPAs. The industry should therefore endeavor
not just to maintain the current performance level, but strive to
bring about significant improvements. Considering the pivotal
role SPP and SPTO KPAs play in the software development
process, it is quite certain that an improvement in the
performance of the practices associated with them will result in
significant productivity enhancements and improved software
process maturity.
339
[6]
[7]
[8]
[9]
[10]
[11]
[12]
[13]
[14]
[15]
[16]
[17]
[18]
[19]
[20]
Alba E. and Chicano F. (2007). “Software project management with gas”,
Information Sciences, vol. 177 no. 1, pp. 2380–2401.
Allen P., Ramachandran M. and Abushama H. (2003). ” PRISMS: an
Approach to Software Process Improvement for Small to Medium
Enterprises”, in Proc. of the Third International Conference On Quality
Software (QSIC’03). pp. 1-4.
Alwin L. F. (2001). Texas Can Benefit From Using a Standard Framework
to Manage Software Development. A Pilot Study Using the Capability
Maturity Model for Software. November. Report No. 02-008.
Amid A., Moradi S. (2013). A Framework for Software Quality
Assessment. Technical Journal of Engineering and Applied Sciences.
Aregbesola M. K. (2017a). Exploring Requirements Management with
Software Subcontract and Configuration Management. Manuscript
submitted for publication.
Aregbesola M. K. (2017b). Integrated Software Management and Product
Engineering. Manuscript submitted for publication. International Journal of
Scientific & Engineering Research (IJSER). In press.
Aregbesola M. K. (2017c). Experiential Appraisal of Organizational
Process Focus and Process Definition in Nigerian Software Companies.
Journal of Scientific and Engineering Research. In press.
Aregbesola M. K. (2017d). Investigating Training Program and Intergroup
Coordination in relation to Peer Review in Nigerian Software Companies.
Journal of Scientific and Engineering Research. In press.
Aregbesola M. K. and Oluwade B. A. An Experimental Evaluation of
Defect Prevention and Change Management in Software Process
Optimization in the Nigerian Software Industry. ARPN Journal of Systems
and Software Vol.4, No.1, 2014, pp. 5-11.
Aregbesola M. Kehinde and B.O. Akinkunmi. (2010a). Software Process
Implementation – A focus on the Nigerian Software Industry. Journal of
Research in Physical Sciences, Vol. 6, No. 2, 2010, pp. 9 – 14.
Aregbesola M. Kehinde, Babatunde O. Akinkunmi and Olalekan S.
Akinola. Process Maturity Assessment of the Nigerian Software Industry.
International Journal of Advances in Engineering and Technology (IJAET),
Vol.1, Issue 4, 2011, pp. 10-25.
Aregbesola M.K. and B.O. Akinkunmi. (2010b). Software Process
Implementation – A focus on the Nigerian Software Industry. International
Research and Development Institute (IRDI), World Congress on Research
and Development, Conference Center, University of Ibadan, 5th - 8th
October 2010. Vol. 5, No. 6, pg.111-116.
Aregbesola M.K. and Onwudebelu U.: Typical Software Quality Assurance
and Quality Management Issues in the Nigerian Software Industry. National
Association for Science, Humanities & Education Research, 8th National
Conference, University of Ado Ekiti, Ado Ekiti, September 14-17, 2011.
Baruah N., Ashima, and Barbaruah K. (2013). Software Project Tracking
and Oversight and Its Different Measures. International Journal of Scientific
and Research Publications, Volume 3, Issue 9.
Brue G. and Launsby R. G. (2003). Design for Six Sigma, McGraw-Hill
Professional.
Chang C. K., Hsin Yi J., Yu D., Dan Z. and Yujia G.(2008). “Time-line
based model for software project scheduling with genetic algorithms”,
Information and Software Technology, vol. 50 no. 11, pp. 1142–1154.
Chang C.K., Christensen M.J., and Zhang T. (2001). “Genetic Algorithms
for Project Management,” Annals of Software Eng., vol. 11, pp. 107- 139.
Chen W. N. and Zhang. J. (2013). “Ant Colony Optimization for Software
Project Scheduling and Staffing with an Event-Based Scheduler,” IEEE
Trans. Software Engineering. Jan. vol. 39, no. 1, pp.1-17.
CMMI Product Team (2006): ‘CMMI for Development, Version 1.2 CMMI-DEV, V1.2’, Software Engineering Institute, Carnegie Mellon
University.
Davis N. and J. McHale,(2003). ”Relating the Team Software
ProcessSM(TSP SM) to the Capability Maturity Model ® for Software(SWCMM®) With Strategy and Overview by Watts S. Humphrey ”,Carnegie
Mellon Software Engineering Institute, Technical Report CMU/SEI-2002TR-008 ESC-TR-2002-008.
www.ijsrp.org
International Journal of Scientific and Research Publications, Volume 7, Issue 6, June 2017
ISSN 2250-3153
[21] Ding R. G. and Jing X. H. (2003). “Five Principles of Project Management
in Software Companies,” Project Management Technology (in Chinese).
vol. 1.
[22] Doran
T.
(2006).
”IEEE
1220:
For
Practical
Systems
Engineering”,Computer,pp.
9294.
ieeexplore.ieee.org/iel5/2/34216/01631953.pdf
[23] Dreon B. E. (2000). CMM Level 3: How Do I Get There from Here? Litton
PRC. version 1.7.
[24] Eckes G. (2001). The Six Sigma Revolution, How General Electric and
Others Turned Process into Profits. USA: John Wiley & Sons, Inc.
[25] Futrell R. T., Shafer D. F. and Safer L. I. (2002). Quality Software Project
Management. Prentice Hall PTR. January 24, 2002.
[26] General Accounting Office (1999). Customs Service Modernization:
Ineffective Software Development Processes Increase Customs System
Develpment Risks. United States General Accounting Office: Report to
Congressional Requesters. GAO/AIMD-99-35. pp 1- 75.
[27] Glazer, Hillel. (2001). Dispelling the Process Myth: Having a Process Does
Not Mean Sacrificing Agility or Creativity. CROSSTALK: The Journal of
Defense Software Engineering.
[28] Glover, Margaret Tanner and Dennie, Debra. (2017). CMMI–Agile Process
Combo: How to be Agile with CMMI. Excellence in Measurement
Technology.
[29] Gremba J. and Myers C. (1997). The IDEAL(SM) Model: A Practical
Guide for Improvement. US:SEI, Carnegie Mellon University.
[30] Han W., Jiang H., Lu T., Zhang X. and Li W. (2015). An Optimized
Resolution for Software Project Planning with Improved Max–Min Ant
System Algorithm. International Journal of Multimedia and Ubiquitous
Engineering. Vol.10, No.6.
[31] Hjalmarsson A. (2013). Software Development Cost Estimation Using
COCOMO II Based Meta Model. Master thesis, ICS, KTH Electrical
Engineering, Stockholm, Sweden.
[32] Humphrey S. W. (2005). “The Personal Software Process: Status and
Trends”, IEEE Software, vol.17, no.6, pp.71-75.
[33] Hurst, Jim. (2017). The Capability Maturity Model and Its Applications.
SANS Software Security with Frank Kim.
[34] Hwang S. M. (2010).”Quality Metrics for Software Process Certification
based on K-Model”in Proc. IEEE 24th International Conference on
Advanced Information. Networking and Applications Workshops, pp. 827830.
[35] Kurien V., Nair R. S. (2014).Software Project Planning and Resource
Allocation Using Ant Colony Optimization with Uncertainty Handling.
International Journal of Innovative Research in Science, Engineering and
Technology. July, Volume 3, Special Issue 5.
[36] Kuvaja P. (1994). Software Process Assessment and Improvement:the
BOOTSTRAP Approach,UK:Blackwell Publishers,Oxford.
[37] Li M. (2007). ”TRISO-Model: A New Approach to Integrated Software
Process Assessment and Improvement”, Software Process Improvement and
Practice, vol.12, issue.5, pp.387-398.
[38] Lowe D. E. and Cox G. M. (1996). Implementing the Capability Maturity
Model for Software Development. Hewlett-Packard Journal. August. pp 111.
[39] Mogre, Anjali, Salunkhe, Sujata. (2014). Effective CMMi Implementation
in Agile environment with fresh team. Atos, Mumbai, India.
[40] Nair P. R. and Annamalai P. (2013). Comparison between ISO 9000 and
CMM Software Quality Standards. International Journal of Engineering,
Business and Enterprise Applications (IJEBEA). pp 10 - 14.
[41] Nalbant S. (2004). An Information System for Streamlining Software
Development Process. MilSOFT Yazılım Teknolojileri A.S. ODTUTeknokent Ikizleri 06531, Ankara-TURKEY. pp 1 - 10.
[42] Nan N. and Harter D. E. (2009). “Impact of Budget and Schedule Pressure
on Software Development Cycle Time and Effort,” IEEE Trans. Software
Eng. Sept./Oct. vol. 35, no. 5, pp. 624-637.
[43] O’Neill Don. (2017). In Search of a Modern Software Life Cycle: Secure
DevOps Foundations for Large-Scale Software Systems. CrossTalk
March/April 2017: Modern Process Trends.
[44] Olson T. G., Linda Parker Gates, Julia L. Mullaney, James W. Over, Neal
R. Reizer, Mark I. Kellner, Richard W. Phillips, Salvatore DiGennaro J.
(1993). A Software Process Framework for the SEI Capability Maturity
Model: Repeatable Level. Sofware Engineering Institutes, Carnegie Mellon
[45]
[46]
[47]
[48]
[49]
[50]
[51]
[52]
[53]
[54]
[55]
[56]
[57]
[58]
[59]
[60]
[61]
[62]
[63]
340
University. Special Report CMU/SEI-93-SR-007. Report. Pittsburgh,
Pennsylvania 15213-3890
Olson T. G., Reizer N. R. and Over J. W. (1994). A Software Process
Framework for the SEI Capability Maturity Model. CMU/SEI-94-HB-01
Handbook, Software Engineering Institute, Carnegie Mellon University,
Pittsburgh, Pennsylvania 15213.
Paulk M. C., Charles V. Weber, Bill Curtis, & Mary Beth Chrissis (1995):
The Capability Maturity Model: Guidelines for Improving the Software
Process. Addison – Wesley, Boston,1995
Paulk M. C., Weber C. V., Garcia S. M., Chrissis M. B., and Bush M.
(1993). “Key Practices of the Capability Maturity ModelSM, Version 1.1”.
Technical Report CMU/SEI-93-TR-025 ESC-TR-93-178, Software
Engineering Institute, Carnegie Mellon University, Pittsburgh,
Pennsylvania. 1993.
Paulk M.C., B. Curtis, M.B. Chrissis, and C.V. Weber. (1993). “Capability
Maturity Model, Version 1.1,” IEEE Software, vol. 10, no. 4, pp. 18-27.
Pikkarainen, Minna. (2008). Towards a Framework for Improving Software
Development Process Mediated with CMMI Goals and Agile Practices.
Academic dissertation at the Department of Information Processing
Science, University of Oulu, Ostrobothnia, Finland.
Rosso-Llopart M. (2005). Project planning and scheduling. Carnegie
Mellon.
Rout and Terence P. (1995). ” SPICE: A Framework for Software Process
Assessment,” Software Process Improvement and Practice, vol. 1, no. 1, pp.
57-66.
Shtub A., Bard J. F., and Globerson S. (2005). Project Management:
Processes, Methodologies, and Economics, second ed. Prentice Hall.
Singh R. (1996). ”International Standard ISO/IEC 12207 Software Life
Cycle Processes”,Software Process Improvement and Practice,vol. 2,no. 1,
pp.35-50.
Soriyan H. A. and Heeks R. (2004): A Profile of Nigeria's Software
Industry. Development Informatics Working Paper No 21, Institute for
Development Policy and Management, University of Manchester, 2004.
Soriyan H. A., Mursu A. and Korpela M. (2000): 'Information system
development methodologies: gender issues in a developing economy', In:
Women, Work and Computerization, E. Balka & R. Smith (eds.), Kluwer
Academic, Boston, MA, 146-154.
Stelzer D. , Mellis W. and Herzwurm G. (1997). “A critical look at ISO
9000 for software quality management,” Software Quality Journal, vol. 6,
no. 2, pp. 65–79.
TickIT (1995). TickIT Guide to Software Quality Management System
Construction and Certification using ISO 9001:1994. Issue 1.0, DISC
TickIT Office.
Vakaslahti P., (1997). ” Process Improvement Frameworks- a Small Case
Study with People Capability Maturity Model”, Software Process
Improvement and Practice, vol. 3, no.4, December, pp.225-234.
Veldman, J. (2011). Process improvement for engineering & maintenance
contractors. University of Groningen, SOM research school, Groningen.
Xiao J., Ao X. T., and Tang Y. (2013). “Solving software project
scheduling problems with ant colony optimization”, Computers and
Operations Research, vol. 40 no. 1, pp. 33–46.
Zubrow D., William H., Jane S. and Dennis G. (1994): ‘Maturity
Questionnaire’. Special Report CMU/SEI-94-SR-7, June 1994.
Akinola S. O., Osofisan A. O., Akinkunmi B. O. (2009). “Industry
Perception of the Software Inspection Process: Nigeria Software Industry as
a Case Study”, African Journal of Computing & ICT (Journal of the IEEE
Nigeria Computer Chapter), Vol. 2, No. 2, pp. 3-11.
Akinola S. O., Osofisan A. O. (2011). “Evaluating Defect Detection
Techniques in a PaperBased Environment – A Multi-Trial Experiment
Report”, African Journal of Computing & ICT (Journal of the IEEE Nigeria
Computer Chapter), Vol. 2, No. 2, pp. 16-30.
AUTHORS
First Author – Aregbesola, Moses Kehinde; Department of
Mathematics and Computer Science, Elizade University, IlaraMokin, Ondo State, Nigeria,
kehinde.aregbesola@elizadeuniversity.edu.ng
www.ijsrp.org