Software Engineering Productivity Measure
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A Software Engineering Productivity Measure is a software engineering-related measure that is a engineering productivity measure within software engineering processes that aims to quantify software engineering output efficiency and software engineering resource utilization.
- AKA: Software Development Productivity Metric, Engineering Productivity Metric, Software Engineering Efficiency Measure.
- Context:
- It can typically measure Software Engineering Work Output through software engineering deliverable quantitys.
- It can typically track Software Engineering Resource Consumption via software engineering work hours.
- It can typically assess Software Engineering Team Performance through software engineering output-to-input ratios.
- It can typically evaluate Software Engineering Process Efficiency using software engineering cycle time metrics.
- It can typically monitor Software Engineering Quality Balance through software engineering defect-adjusted productivity.
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- It can often indicate Software Engineering Process Maturity via software engineering productivity trends.
- It can often support Software Engineering Planning Decisions through software engineering capacity forecasts.
- It can often enable Software Engineering Benchmarking by software engineering industry comparisons.
- It can often facilitate Software Engineering Optimization through software engineering bottleneck analysis.
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- It can range from being a Simple Software Engineering Productivity Measure to being a Composite Software Engineering Productivity Measure, depending on its software engineering measurement complexity.
- It can range from being an Individual Software Engineering Productivity Measure to being an Organization Software Engineering Productivity Measure, depending on its software engineering measurement scope.
- It can range from being a Traditional Software Engineering Productivity Measure to being a Data-Driven Software Engineering Productivity Measure, depending on its software engineering measurement approach.
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- It can integrate with Engineering Productivity Metric System (EPMS) for software engineering standardized benchmarking.
- It can connect to Software Engineering Tasks for software engineering work measurement.
- It can interface with Software Development Environments for software engineering automated tracking.
- It can communicate with Software Engineering Practices for software engineering methodology assessment.
- It can synchronize with Software Quality Assurance (SQA) Tasks for software engineering quality-adjusted measurement.
- ...
- Example(s):
- Code-Based Software Engineering Productivity Measures, such as:
- Lines of Code Per Developer Hour, measuring software engineering code output rate.
- Function Points Per Person Month, quantifying software engineering functional delivery.
- Story Points Per Sprint, tracking software engineering agile velocity.
- Code Commits Per Developer, assessing software engineering contribution frequency.
- Feature-Based Software Engineering Productivity Measures, such as:
- Features Delivered Per Quarter, measuring software engineering feature throughput.
- User Stories Completed Per Sprint, tracking software engineering requirement completion.
- Bug Fix Rate, quantifying software engineering maintenance productivity.
- Enhancement Delivery Rate, evaluating software engineering improvement velocity.
- Process-Based Software Engineering Productivity Measures, such as:
- Deployment Frequency Metric, measuring software engineering release productivity.
- Lead Time for Changes, tracking software engineering process efficiency.
- Pull Request Throughput, assessing software engineering review productivity.
- Build Success Rate, evaluating software engineering integration efficiency.
- Advanced Software Engineering Productivity Measures, such as:
- DORA Metrics, combining software engineering deployment frequency, software engineering lead time, software engineering change failure rate, and software engineering recovery time.
- Software Development Velocity Measure, quantifying software engineering development speed.
- Developer Experience (DX) Score, measuring software engineering workflow efficiency.
- Engineering Effectiveness Metric, assessing software engineering overall productivity.
- ...
- Code-Based Software Engineering Productivity Measures, such as:
- Counter-Example(s):
- Software Quality Metrics, which measure software correctness rather than engineering productivity.
- Worker Output Productivity Measures, which track general labor productivity rather than software engineering specific output.
- Total Factor Productivity (TFP) Measures, which assess economy-wide productivity rather than software engineering productivity.
- Capital and Labor Substitution Elasticity Measures, which evaluate factor substitution rather than engineering output.
- Work Productivity and Activity Impairment (WPAI) Questionnaires, which measure health impact on productivity rather than engineering performance.
- See: Engineering Productivity Metric System (EPMS), DORA, Software Engineering Task, Software Engineering Practice, Software Development Velocity Measure, Software Development Professional, Software Quality Assurance (SQA) Task.
References
2022
- "How Uber is Measuring Engineering Productivity."
- QUOTE: On Thursday, 4 August, Uber held an All-Hands meeting. Presenting at the event was Uber’s CEO, Dara Khosrowshahi. During the meeting, Dara showcased a new tool for all of engineering: the Eng Metrics Dashboard. It’s a dashboard which shows pull review metrics – which Uber calls ‘diffs’ – code review metrics and focus time stats. This is what it looks like at first glance:
- QUOTE: On Thursday, 4 August, Uber held an All-Hands meeting. Presenting at the event was Uber’s CEO, Dara Khosrowshahi. During the meeting, Dara showcased a new tool for all of engineering: the Eng Metrics Dashboard. It’s a dashboard which shows pull review metrics – which Uber calls ‘diffs’ – code review metrics and focus time stats. This is what it looks like at first glance:
2021
- "Engineering Productivity : Delivering frictionless engineering and excellent products."
- QUOTE: What is Engineering Productivity? We are a data-driven engineering discipline focused on optimizing the engineering process so that Google can deliver amazing experiences to our users, faster.
2010
- "A summary measurement of engineering productivity at the project level." Project Management Institute.
- ABSTRACT: Since 2002, the Construction Industry Institute (CII) has been working to develop a standardized engineering productivity metric system (EPMS) for benchmarking purposes. In this system, engineering productivity is defined as a ratio of direct engineering work hours to the engineering outputs, as measured by issued for construction (IFC) quantities. The EPMS consists of six major engineering disciplines with a number of underlying metrics. Engineering productivity can be accordingly benchmarked at any of these levels; however, there is a lack of project-level engineering productivity. The challenge is that IFC quantities are measured with different units and thus are difficult to advance to the project level. To overcome this barrier, this study examines three approaches for aggregating engineering productivity metrics to the project level, based on 112 heavy industrial projects. The selected project level engineering productivity measurement best summarizes the underlying engineering productivity metrics and provides a macro view of engineering performance; it allows owners and engineering organizations to benchmark engineering productivity at the project level and also lays the foundation for future engineering productivity analysis and research.