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Chapter 12 Evaluating Products, Processes, and Resources

Chapter 12 Evaluating Products, Processes, and Resources

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Page 1: Chapter 12 Evaluating Products, Processes, and Resources

Chapter 12

Evaluating Products, Processes, and Resources

Page 2: Chapter 12 Evaluating Products, Processes, and Resources

Review

Software engineering provides a large variety of methods and tools for use by software developers throughout the software life-cycle.

What are some of them?

Page 3: Chapter 12 Evaluating Products, Processes, and Resources

Review of S.E. Methods and Tools

1. Project Management2. Requirements Engineering3. Architectural Design4. Implementation5. Testing6. Maintenance

Page 4: Chapter 12 Evaluating Products, Processes, and Resources

Discussion Question

In a given situation, how do developers decide which method or tool is the most appropriate to use?

Page 5: Chapter 12 Evaluating Products, Processes, and Resources

Discussion Question

How can developers tell if a change to the development process actually results in improvement?

Page 6: Chapter 12 Evaluating Products, Processes, and Resources

Discussion Question

How can developers evaluate the effectiveness and efficiency of what they are already doing,

so that they can tell if a change to the development process actually results in improvement?

Page 7: Chapter 12 Evaluating Products, Processes, and Resources

Discussion Question

Once a change has been made,

how can developers demonstrate that the products, processes and resources have the desired characteristics (such as improved quality)?

Page 8: Chapter 12 Evaluating Products, Processes, and Resources

Chapter 12 Contents

Approaches to Evaluation Selecting an Evaluation Technique Assessment vs. Prediction Evaluating Products Evaluating Processes Evaluating Resources

Page 9: Chapter 12 Evaluating Products, Processes, and Resources

Approaches to Evaluation

Measure key aspects of product, processes, and resources

and use this information to

Determine whether we have met goals for productivity, performance, quality, and other desire attributes

Page 10: Chapter 12 Evaluating Products, Processes, and Resources

Four Categories of Evaluation Techniques

Feature analysis rate and rank attributes

Surveys document relationships and outcomes

Case studies compare with situation with another

Formal experiments rigorous, controlled investigation

Page 11: Chapter 12 Evaluating Products, Processes, and Resources

Feature Analysis Example:

Buying a Project Scheduling Tool List five key attributes that the tool

should have Identify three possible tools and rate each

on the criterion Examine the scores, creating a total score

based on the importance of each criterion Based on the score, select the tool with

the highest score

Page 12: Chapter 12 Evaluating Products, Processes, and Resources

Buying a Project Scheduling Tool

Features Tool 1:MS

Project

Tool 2:Visio

Tool 3:Rational

Rose

Importance

Good user interface 4 5 4 3

Easy to learn 5 5 5 5

Consistency checking 5 3 1 3

Report Generation 4 4 4 2

Cost 5 4 5 5

Score 85 77 73

Page 13: Chapter 12 Evaluating Products, Processes, and Resources

Surveys

Retrospective Record data

to determine how project participants reacted to a particular method, tool, or technique

Compare data with other similar situations

Page 14: Chapter 12 Evaluating Products, Processes, and Resources

Case Studies

Compares one situation with another Projects chosen for case study must be

typical within the organization or company

Identify key factors that may affect an activity’s outcome and then document them

Page 15: Chapter 12 Evaluating Products, Processes, and Resources

Case Studies

Involve sequence of steps: conception hypothesis setting design preparation execution analysis dissemination decision making

Page 16: Chapter 12 Evaluating Products, Processes, and Resources

Case Study Types

Sister projects each is typical and has similar values for

the independent variables

Baseline compare single project to organizational

norm

Random selection partition single project into parts

Page 17: Chapter 12 Evaluating Products, Processes, and Resources

Formal Experiments

Control variables Uses methods to reduce bias and

eliminate confounding factors Often replicated

Page 18: Chapter 12 Evaluating Products, Processes, and Resources

Evaluation Steps

Setting the hypothesis deciding what we wish to investigate, expressed

as a hypothesis we want to test Maintaining control over variables:

identify variables that can affect the hypothesis, and decide how much control we have over the variables

Making investigation meaningful: the result of a formal experiment is more

generalizable, while a case study or survey only applies to certain organization

Page 19: Chapter 12 Evaluating Products, Processes, and Resources

Short answer question

How does feature analysis, surveys, case studies, and controlled experiments

differ?

Page 20: Chapter 12 Evaluating Products, Processes, and Resources

Selecting An Evaluation Technique

Formal experiments: research in the small

Case studies: research in the typical

Surveys: research in the large

Page 21: Chapter 12 Evaluating Products, Processes, and Resources

Key Selection Factors

Level of control over the variables Degree to which the task can be

isolated from the rest of the development process

Degree to which we can replicate the basic situation

Page 22: Chapter 12 Evaluating Products, Processes, and Resources

Short answer question

Under which circumstances are feature analysis, surveys, case studies, and controlled experiments

appropriate?

Page 23: Chapter 12 Evaluating Products, Processes, and Resources

Real-world example

Hypothesis:

Extreme programming is more effective than the waterfall model for student capstone S.E. projects

Variables that can affect outcome? Evaluation Technique?

Page 24: Chapter 12 Evaluating Products, Processes, and Resources

Assessment vs. Prediction

Assessment system examines an existing entity by characterizing it numerically

Prediction system predicts characteristic of a future entity; involves a model with associated prediction procedures deterministic prediction (we always get the same

output for an input) stochastic prediction (output varies

probabilistically)