PPT on Basics of Software Project Management

1. Software Project Planning
1
Presentation By :-
Shantam Gupta
Akshat Sachan
Bhavya Gururani
Shaurya Gupta

2. The Four P’s
2
Product
Process
Project
People

3. The People: The Stakeholders
• Five categories of stakeholders
– Senior managers who define the business issues that often have
significant influence on the project.
– Project (technical) managers who must plan, motivate,
organize, and control the practitioners who do software work.
– Practitioners who deliver the technical skills that are necessary
to engineer a product or application.
– Customers who specify the requirements for the software to be
engineered and other stakeholders who have a peripheral
interest in the outcome.
– End-users who interact with the software once it is released for
production use. 3

4. The People: Team Leaders
• Qualities to look for in a team leader
– Motivation. The ability to encourage (by “push or pull”)
technical people to produce to their best ability.
– Organization. The ability to mold existing processes (or invent
new ones) that will enable the initial concept to be translated
into a final product.
– Ideas or innovation. The ability to encourage people to create
and feel creative even when they must work within bounds
established for a particular software product or application.
4

5. The People: The Software Team
• Seven project factors to consider when structuring a software
development team
– the difficulty of the problem to be solved
– the size of the resultant program(s) in lines of code or function
points
– the time that the team will stay together
– the degree to which the problem can be modularized
– the required quality and reliability of the system to be built
– the rigidity of the delivery date
– the degree of sociability required for the project
5

6. The Product Scope
• Scope
• Context. How does the software to be built fit into a larger
system, product, or business context and what constraints
are imposed as a result of the context?
• Information objectives. What customer-visible data objects
are produced as output from the software? What data
objects are required for input?
• Function and performance. What function does the
software perform to transform input data into output? Are
any special performance characteristics to be addressed?
6

7. The Process
• Once a process framework has been established
– Consider project characteristics
– Determine the degree of rigor required
– Define a task set for each software engineering activity
7

8. The Project
• Projects get into trouble when …
– Software people don’t understand their customer’s needs.
– The product scope is poorly defined.
– Changes are managed poorly.
– The chosen technology changes.
– Business needs change
– Deadlines are unrealistic.
– Users are resistant.
– Sponsorship is lost [or was never properly obtained].
– The project team lacks people with appropriate skills.
– Managers avoid best practices and lessons learned.
8

9. Process and Project Metrics
9

10. A Good Manager Measures
10
measurement
What do we
use as a
basis?
• size?
• function?
project metrics
process metrics
process
product
product metrics

11. Why Do We Measure?
• assess the status of an ongoing project
• track potential risks
• uncover problem areas before they go “critical,”
• adjust work flow or tasks,
• evaluate the project team’s ability to control quality of
software work products.
11

12. Process Metrics
• Quality-related
– focus on quality of work products and deliverables
• Productivity-related
– Production of work-products related to effort expended
• Statistical SQA data
– error categorization & analysis
• Defect removal efficiency
– propagation of errors from process activity to activity
• Reuse data
– The number of components produced and their degree of
reusability
12

13. Typical Project Metrics
• Effort/time per software engineering task
• Errors uncovered per review hour
• Scheduled vs. actual milestone dates
• Changes (number) and their characteristics
• Distribution of effort on software engineering tasks
13

14. Typical Size-Oriented Metrics
• errors per KLOC (thousand lines of code)
• defects per KLOC
• $ per LOC
• pages of documentation per KLOC
• errors per person-month
• errors per review hour
• LOC per person-month
• $ per page of documentation
14

15. Typical Function-Oriented Metrics
• errors per FP (thousand lines of code)
• defects per FP
• $ per FP
• pages of documentation per FP
• FP per person-month
15

16. Function-Oriented Metrics
• FP are computed by
FP = count-total * [0.65 + 0.01 * Sum(Fi)]
• count-total is the sum of all FP entries
• The Fi (i = 1 to 14) are "complexity adjustment values" based
on responses to the following questions [ART85]:
1. Does the system require reliable backup and recovery?
2. Are data communications required?
3. Are there distributed processing functions?
4. Is performance critical?
...
• Each of these questions is answered using a scale that ranges from 0 (not
important or applicable) to 5 (absolutely essential). 16

17. Counting function points
17

18. Object-Oriented Metrics
• Number of scenario scripts (use-cases)
• Number of support classes (required to implement
the system but are not immediately related to the
problem domain)
• Average number of support classes per key class
(analysis class)
• Number of subsystems (an aggregation of classes
that support a function that is visible to the end-user
of a system)
18

19. WebApp Project Metrics
• Number of static Web pages (the end-user has no control over the
content displayed on the page)
• Number of dynamic Web pages (end-user actions result in customized
content displayed on the page)
• Number of internal page links (internal page links are pointers that
provide a hyperlink to some other Web page within the WebApp)
• Number of persistent data objects
• Number of external systems interfaced
• Number of static content objects
• Number of dynamic content objects
• Number of executable functions
19

20. Measuring Quality
• Correctness — the degree to which a program
operates according to specification
• Maintainability—the degree to which a program is
amenable to change
• Integrity—the degree to which a program is
impervious to outside attack
• Usability—the degree to which a program is easy to
use
20

21. Defect Removal Efficiency
21
where:
E is the number of errors found before
delivery of the software to the end-user
D is the number of defects found after
delivery.
DRE = E /(E + D)

22. Estimation for Software
Projects
22

23. Software Project Planning
23
The overall goal of project planning is to establish a
pragmatic strategy for controlling, tracking, and
monitoring a complex technical project.
Why?
So the end result gets done on time, with quality!

24. Project Planning Task Set-I
• Establish project scope
• Determine feasibility
• Analyze risks
• Define required resources
– Determine required human resources
– Define reusable software resources
– Identify environmental resources
24

25. Project Planning Task Set-II
• Estimate cost and effort
– Decompose the problem
– Develop two or more estimates using size, function points,
process tasks or use-cases
– Reconcile the estimates
• Develop a project schedule
– Establish a meaningful task set
– Define a task network
– Use scheduling tools to develop a timeline chart
– Define schedule tracking mechanisms
25

26. Estimation
• Estimation of resources, cost, and schedule
for a software engineering effort requires
– experience
– access to good historical information (metrics)
– the courage to commit to quantitative predictions
when qualitative information is all that exists
• Estimation carries inherent risk and this risk
leads to uncertainty
26

27. Write it Down!
27
Software
Project
Plan
Project Scope
Estimates
Risks
Schedule
Control
strategy

28. What is Scope?
• Software scope describes
– the functions and features that are to be delivered to end-users
– the data that are input and output
– the “content” that is presented to users as a consequence of
using the software
– the performance, constraints, interfaces, and reliability that
bound the system.
• Scope is defined using one of two techniques:
– A narrative description of software scope is developed after
communication with all stakeholders.
– A set of use-cases is developed by end-users.
28

29. Resource Estimation
• Three major categories of software engineering resources
– People
– Development environment
– Reusable software components
• Often neglected during planning but become a paramount concern during
the construction phase of the software process
• Each resource is specified with
– A description of the resource
– A statement of availability
– The time when the resource will be required
– The duration of time that the resource will be applied
29
Time window

30. Categories of Resources
30
People
- Number required
- Skills required
- Geographical location
Development Environment
- Software tools
- Computer hardware
- Network resources
Reusable Software Components
- Off-the-shelf components
- Full-experience components
- Partial-experience components
- New components
The
Project

31. Human Resources
• Planners need to select the number and the kind of people
skills needed to complete the project
• They need to specify the organizational position and job
specialty for each person
• Small projects of a few person-months may only need one
individual
• Large projects spanning many person-months or years require
the location of the person to be specified also
• The number of people required can be determined only after
an estimate of the development effort
31

32. Development Environment
Resources
• A software engineering environment (SEE) incorporates
hardware, software, and network resources that provide
platforms and tools to develop and test software work
products
• Most software organizations have many projects that require
access to the SEE provided by the organization
• Planners must identify the time window required for
hardware and software and verify that these resources will be
available
32

33. Reusable Software Resources
• Off-the-shelf components
– Components are from a third party or were developed for a
previous project
– Ready to use; fully validated and documented; virtually no risk
• Full-experience components
– Components are similar to the software that needs to be built
– Software team has full experience in the application area of
these components
– Modification of components will incur relatively low risk
33

34. Reusable Software Resources
• Partial-experience components
– Components are related somehow to the software that needs
to be built but will require substantial modification
– Software team has only limited experience in the application
area of these components
– Modifications that are required have a fair degree of risk
• New components
– Components must be built from scratch by the software team
specifically for the needs of the current project
– Software team has no practical experience in the application
area
– Software development of components has a high degree of risk
34

35. Estimation Techniques
35
• Past (similar) project experience
• Conventional estimation techniques
– task breakdown and effort estimates
– size (e.g., FP) estimates
• Empirical models
• Automated tools

36. Functional Decomposition
36
functional
decomposition
Statement
of
Scope Perform a Grammatical
“parse”

37. Problem-Based Estimation
• Start with a bounded statement of scope
• Decompose the software into problem functions that can
each be estimated individually
• Compute an LOC or FP value for each function
• Derive cost or effort estimates by applying the LOC or FP
values to your baseline productivity metrics (e.g.,
LOC/person-month or FP/person-month)
• Combine function estimates to produce an overall estimate
for the entire project
37

38. Problem-Based Estimation
• In general, the LOC/pm and FP/pm metrics should be
computed by project domain
– Important factors are team size, application area, and
complexity
• LOC and FP estimation differ in the level of detail required for
decomposition with each value
– For LOC, decomposition of functions is essential and should go
into considerable detail (the more detail, the more accurate the
estimate)
– For FP, decomposition occurs for the five information domain
characteristics and the 14 adjustment factors
• External inputs, external outputs, external inquiries, internal
logical files, external interface files
38

39. Problem-Based Estimation
• For both approaches, the planner uses lessons learned to
estimate an optimistic, most likely, and pessimistic size value
for each function or count (for each information domain
value)
• Then the expected size value S is computed as follows:
S = (Sopt + 4Sm + Spess)/6
• Historical LOC or FP data is then compared to S in order to
cross-check it
39

40. Example: LOC Approach
40
Average productivity for systems of this type = 620 LOC/pm.
Burdened labor rate =$8000 per month, the cost per line of code is
approximately $13.
Based on the LOC estimate and the historical productivity data, the
total estimated project cost is $431,000 and the estimated effort is
54 person-months.

41. Example: FP Approach
41
The estimated number of FP is derived:
FPestimated = count-total * [0.65 + 0.01 * Sum(Fi)] (see next)
FPestimated = 375
organizational average productivity = 6.5 FP/pm.
burdened labor rate = $8000 per month, the cost per FP is approximately $1230.
Based on the FP estimate and the historical productivity data, the total estimated
project cost is $461,000 and the estimated effort is 58 person-months.

42. Complexity Adjustment Factor
Factor Value
• Backup and recovery 4
• Data communications 2
• Distributed processing 0
• Performance critical 4
• Existing operating environment 3
• On-line data entry 4
• Input transaction over multiple screens 5
• Master files updated on-line 3
• Information domain values complex 5
• Internal processing complex 5
• Code designed for reuse 4
• Conversion/installation in design 3
• Multiple installations 5
• Application designed for change 5
42
• Answer the factors
using a scale that
ranges from 0 (not
important or applicable)
to 5 (absolutely
essential)
• Sum(Fi)=52

43. Example: FP Approach
43
The estimated number of FP is derived:
FPestimated = count-total * [0.65 + 0.01 * Sum(Fi)]
FPestimated = 375
organizational average productivity = 6.5 FP/pm.
burdened labor rate = $8000 per month, the cost per FP is approximately $1230.
Based on the FP estimate and the historical productivity data, the total estimated
project cost is $461,000 and the estimated effort is 58 person-months.

44. Process-Based Estimation
• Identify the set of functions that the software needs to
perform as obtained from the project scope
• Identify the series of framework activities that need to be
performed for each function
• Estimate the effort (in person months) that will be required
to accomplish each software process activity for each
function
44

45. Process-Based Estimation
• Apply average labor rates (i.e., cost/unit effort) to the effort
estimated for each process activity
• Compute the total cost and effort for each function and
each framework activity (See table in Pressman, p. 655)
• Compare the resulting values to those obtained by way of
the LOC and FP estimates
– If both sets of estimates agree, then your numbers are highly
reliable
– Otherwise, conduct further investigation and analysis
concerning the function and activity breakdown
45
This is the most commonly used of the two estimation
techniques (problem and process)

46. Process-Based Estimation
46
Obtained from “process framework”
application
functions
framework activities
Effort required to
accomplish
each framework
activity for each
application function

47. Process-Based Estimation
Example
47
Based on an average burdened labor rate of $8,000 per month, the
total estimated project cost is $368,000 and the estimated effort is
46 person-months.

48. Tool-Based Estimation
48
project characteristics
calibration factors
LOC/FP data

49. Estimation with Use-Cases
49
Using 620 LOC/pm as the average productivity for systems of this
type and a burdened labor rate of $8000 per month, the cost per
line of code is approximately $13. Based on the use-case estimate
and the historical productivity data, the total estimated project
cost is $552,000 and the estimated effort is 68 person-months.

50. Empirical Estimation Models
50
General form:
effort = tuning coefficient * size
exponent
usually derived
as person-months
of effort required
either a constant or
a number derived based
on complexity of project
usually LOC but
may also be
function point
empirically
derived

51. COCOMO-II
• COCOMO II is actually a hierarchy of estimation
models that address the following areas:
• Application composition model. Used during the early stages of
software engineering, when prototyping of user interfaces,
consideration of software and system interaction, assessment of
performance, and evaluation of technology maturity are
paramount.
• Early design stage model. Used once requirements have been
stabilized and basic software architecture has been established.
• Post-architecture-stage model. Used during the construction of
the software.
51

52. The Software Equation
52
A dynamic multivariable model
E = [LOC x B0.333/P]3 x (1/t4)
where
E = effort in person-months or person-years
t = project duration in months or years
B = “special skills factor”
P = “productivity parameter”

53. Estimation for OO Projects-I
• Develop estimates using effort decomposition, FP analysis, and any other
method that is applicable for conventional applications.
• Using object-oriented analysis modeling (Chapter 8), develop use-cases
and determine a count.
• From the analysis model, determine the number of key classes (called
analysis classes in Chapter 8).
• Categorize the type of interface for the application and develop a
multiplier for support classes:
– Interface type Multiplier
– No GUI 2.0
– Text-based user interface 2.25
– GUI 2.5
– Complex GUI 3.0
53

54. Estimation for OO Projects-II
• Multiply the number of key classes (step 3) by the multiplier
to obtain an estimate for the number of support classes.
• Multiply the total number of classes (key + support) by the
average number of work-units per class. Lorenz and Kidd
suggest 15 to 20 person-days per class.
• Cross check the class-based estimate by multiplying the
average number of work-units per use-case
54

55. The Make-Buy Decision
55

56. Computing Expected Cost
56
(path probability) x (estimated path cost)
i i
For example, the expected cost to build is:
expected cost = 0.30 ($380K) + 0.70 ($450K)
similarly
,
expected cost = $382K
expected cost = $267K
expected cost = $410K
build
reuse
buy
contr
expected cost =
= $429 K

57. Project Scheduling
57

58. Why Are Projects Late?
• An unrealistic deadline established by someone outside the software
development group
• Changing customer requirements that are not reflected in schedule
changes;
• An honest underestimate of the amount of effort and/or the number
of resources that will be required to do the job;
• Predictable and/or unpredictable risks that were not considered when
the project commenced;
• Technical difficulties that could not have been foreseen in advance;
• Human difficulties that could not have been foreseen in advance;
• Miscommunication among project staff that results in delays;
• A failure by project management to recognize that the project is falling
behind schedule and a lack of action to correct the problem
58

59. Effort and Delivery Time
59

60. Scheduling Principles
60
• “Front End” Activities
– customer communication
– analysis
– design
– review and modification
• Construction Activities
– coding or code
generation
• Testing and Installation
– unit, integration
– white-box, black box
– regression
40-50%
30-40%
15-20%

61. 40-20-40 Distribution of
Effort
• A recommended distribution of effort across the software process is
40% (analysis and design), 20% (coding), and 40% (testing)
• Work expended on project planning rarely accounts for more than 2 -
3% of the total effort
• Requirements analysis may comprise 10 - 25%
– Effort spent on prototyping and project complexity may increase
this
• Software design normally needs 20 – 25%
• Coding should need only 15 - 20% based on the effort applied to
software design
• Testing and subsequent debugging can account for 30 - 40%
– Safety or security-related software requires more time for testing
61

62. Basic Principles for Project
Scheduling
• Interdependency
– The interdependency of each compartmentalized activity,
action, or task must be determined
– Some tasks must occur in sequence while others can occur in
parallel
– Some actions or activities cannot commence until the work
product produced by another is available
• Effort validation
– Every project has a defined number of people on the team
– As time allocation occurs, the project manager must ensure that
no more than the allocated number of people have been
scheduled at any given time
62

63. Basic Principles for Project
Scheduling
• Time allocation
– Each task to be scheduled must be allocated some number of
work units
– In addition, each task must be assigned a start date and a
completion date that are a function of the interdependencies
– Start and stop dates are also established based on whether
work will be conducted on a full-time or part-time basis
• Defined responsibilities
– Every task that is scheduled should be assigned to a specific
team member
63

64. Basic Principles for Project
Scheduling
• Defined outcomes
– Every task that is scheduled should have a defined outcome for
software projects such as a work product or part of a work
product
– Work products are often combined in deliverables
• Defined milestones
– Every task or group of tasks should be associated with a project
milestone
– A milestone is accomplished when one or more work products
has been reviewed for quality and has been approved
64

65. Relationship Between
People and Effort
• Common management myth: If we fall behind schedule, we
can always add more programmers and catch up later in the
project
– This practice actually has a disruptive effect and causes the
schedule to slip even further
– The added people must learn the system
– The people who teach them are the same people who were
earlier doing the work
– During teaching, no work is being accomplished
– Lines of communication (and the inherent delays) increase for
each new person added
65

66. Factors that Influence a
Project’s Schedule
• Size of the project
• Number of potential users
• Mission criticality
• Application longevity
• Stability of requirements
• Ease of customer/developer communication
• Maturity of applicable technology
• Performance constraints
• Embedded and non-embedded characteristics
• Project staff
• Reengineering factors
66

67. Purpose of a Task Network
• Also called an activity network
• It is a graphic representation of the task flow for a project
• It depicts task length, sequence, concurrency, and
dependency
• Points out inter-task dependencies to help the manager
ensure continuous progress toward project completion
• The critical path
– A single path leading from start to finish in a task network
– It contains the sequence of tasks that must be completed on
schedule if the project as a whole is to be completed on
schedule
– It also determines the minimum duration of the project
67

68. Example Task Network
68
Task A
3
Task B
3
Task E
8
Task F
2
Task H
5
Task C
7
Task D
5
Task I
4
Task M
0
Task N
2
Task G
3
Task J
5
Task K
3
Task L
10
Where is the critical path and what tasks are on it?

69. Example Task Network
69
Critical path: A-B-C-E-K-L-M-N
Task A
3
Task B
3
Task E
8
Task F
2
Task H
5
Task C
7
Task D
5
Task I
4
Task M
0
Task N
2
Task G
3
Task J
5
Task K
3
Task L
10

70. Timeline Charts
70
Tasks Week 1 Week 2 Week 3 Week 4 Week n
Task 1
Task 2
Task 3
Task 4
Task 5
Task 6
Task 7
Task 8
Task 9
Task 10
Task 11
Task 12

71. Example Timeline Charts
71