METRICS FOR SMALL ORGANIZATIONS
4.8 METRICS FOR SMALL ORGANIZATIONS
The vast majority of software development organizations have fewer than 20 soft- ware people. It is unreasonable, and in most cases unrealistic, to expect that such
If you’re just starting organizations will develop comprehensive software metrics programs. However, it to collect software
metrics, remember to is reasonable to suggest that software organizations of all sizes measure and then keep it simple. If you
use the resultant metrics to help improve their local software process and the qual- bury yourself with
ity and timeliness of the products they produce. Kautz [KAU99] describes a typical data, your metrics
scenario that occurs when metrics programs are suggested for small software orga- effort will fail.
nizations: Originally, the software developers greeted our activities with a great deal of skepticism,
but they eventually accepted them because we kept our measurements simple, tailored them to each organization, and ensured that they produced valuable information. In the end, the programs provided a foundation for taking care of customers and for planning and carrying out future work.
What Kautz suggests is a commonsense approach to the implementation of any soft- ware process related activity: keep it simple, customize to meet local needs, and be sure it adds value. In the paragraphs that follow, we examine how these guidelines
? relate to metrics for small shops.
How do I
derive a set
“Keep it simple” is a guideline that works reasonably well in many activities. But
of “simple”
software metrics? how do we derive a “simple” set of software metrics that still provides value, and how can we be sure that these simple metrics will meet the needs of a particular software
organization? We begin by focusing not on measurement but rather on results. The software group is polled to define a single objective that requires improvement. For example, “reduce the time to evaluate and implement change requests.” A small orga- nization might select the following set of easily collected measures:
• Time (hours or days) elapsed from the time a request is made until evalua- tion is complete, t queue .
• Effort (person-hours) to perform the evaluation, W eval . • Time (hours or days) elapsed from completion of evaluation to assignment of
change order to personnel, t eval .
• Effort (person-hours) required to make the change, W change . • Time required (hours or days) to make the change, t change . • Errors uncovered during work to make change, E change . • Defects uncovered after change is released to the customer base, D change .
Once these measures have been collected for a number of change requests, it is pos- sible to compute the total elapsed time from change request to implementation of the change and the percentage of elapsed time absorbed by initial queuing, evalua- tion and change assignment, and change implementation. Similarly, the percentage of effort required for evaluation and implementation can be determined. These met- rics can be assessed in the context of quality data, E change and D change . The percent- ages provide insight into where the change request process slows down and may lead to process improvement steps to reduce t queue ,W eval ,t eval ,W change , and/or
E change . In addition, the defect removal efficiency can be computed as DRE = E change / (E change +D change ) DRE can be compared to elapsed time and total effort to determine the impact of
quality assurance activities on the time and effort required to make a change. For small groups, the cost of collecting measures and computing metrics ranges from 3 to 8 percent of project budget during the learning phase and then drops to less than 1 percent of project budget after software engineers and project managers have become familiar with the metrics program [GRA99]. These costs can show a sub- stantial return on investment if the insights derived from metrics data lead to mean- ingful process improvement for the software organization.
Parts
» The Concurrent Development Model
» SUMMARY Software engineering is a discipline that integrates process, methods, and tools for
» PEOPLE In a study published by the IEEE [CUR88], the engineering vice presidents of three
» THE PROCESS The generic phases that characterize the software process—definition, development,
» THE PROJECT In order to manage a successful software project, we must understand what can go
» METRICS IN THE PROCESS AND PROJECT DOMAINS
» Extended Function Point Metrics
» METRICS FOR SOFTWARE QUALITY
» INTEGRATING METRICS WITHIN THE SOFTWARE PROCESS
» METRICS FOR SMALL ORGANIZATIONS
» ESTABLISHING A SOFTWARE METRICS PROGRAM
» Obtaining Information Necessary for Scope
» An Example of LOC-Based Estimation
» QUALITY CONCEPTS 1 It has been said that no two snowflakes are alike. Certainly when we watch snow
» SUMMARY Software quality assurance is an umbrella activity that is applied at each step in the
» R diagram 1.4 <part-of> data model; data model <part-of> design specification;
» SYSTEM MODELING Every computer-based system can be modeled as an information transform using an
» Facilitated Application Specification Techniques
» Data Objects, Attributes, and Relationships
» Entity/Relationship Diagrams
» Hatley and Pirbhai Extensions
» Creating an Entity/Relationship Diagram
» SUMMARY Design is the technical kernel of software engineering. During design, progressive
» Data Modeling, Data Structures, Databases, and the Data Warehouse
» Data Design at the Component Level
» A Brief Taxonomy of Styles and Patterns
» Quantitative Guidance for Architectural Design
» Isolate the transform center by specifying incoming and outgoing
» SUMMARY Software architecture provides a holistic view of the system to be built. It depicts the
» The User Interface Design Process
» Defining Interface Objects and Actions
» D E S I G N E VA L U AT I O N
» Testing for Real-Time Systems
» Organizing for Software Testing
» Criteria for Completion of Testing
» The Transition to a Quantitative View
» The Attributes of Effective Software Metrics
» Architectural Design Metrics
» Component-Level Design Metrics
» SUMMARY Software metrics provide a quantitative way to assess the quality of internal product
» Encapsulation, Inheritance, and Polymorphism
» Identifying Classes and Objects
» The Common Process Framework for OO
» OO Project Metrics and Estimation
» Event Identification with Use-Cases
» SUMMARY Object-oriented analysis methods enable a software engineer to model a problem by
» Partitioning the Analysis Model
» Designing Algorithms and Data Structures
» Program Components and Interfaces
» SUMMARY Object-oriented design translates the OOA model of the real world into an
» Testing Surface Structure and Deep Structure
» Deficiencies of Less Formal Approaches 1
» What Makes Cleanroom Different?
» Design Refinement and Verification
» SUMMARY Cleanroom software engineering is a formal approach to software development that
» Structural Modeling and Structure Points
» Describing Reusable Components
» SUMMARY Component-based software engineering offers inherent benefits in software quality,
» Guidelines for Distributing Application Subsystems
» Middleware and Object Request Broker Architectures
» An Overview of a Design Approach
» Consider expert Web developer will create a complete design, but time and cost can be appropriate
» A Software Reengineering Process Model
» Reverse Engineering to Understand Data
» Forward Engineering for Client/Server Architectures
» SUMMARY Reengineering occurs at two different levels of abstraction. At the business level,
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