What is the expected effect of Software (LOC-based) Size on Software Productivity?

Research Question

Main question:
What evidence is there for the accuracy/usefulness of the prediction and measurement methods?

Secondary Questions:
1) Is there any measurement that can support  prediction and measurement methods? If so, is it always true for different software processes?

2) Which factors (or drivers or constructs) have been used to define/compose/describe such prediction and measurement  methods?

Search String

(("software process" OR "software development" OR "software engineering processes" OR "business information system" OR "software maintenance" OR "software project" OR "open source project" OR "OSS project") AND (productivity OR efficiency OR "process performance" OR "development performance" OR "software performance" OR "project performance" OR "prediction method" OR "measurement method") AND (measure OR metric OR model OR predict OR estimate OR measurement OR estimation OR prediction) AND (empirical OR validation OR evaluation OR experiment OR example OR simulation OR analysis OR study OR interview))

Inclusion Criteria

• To talk about: Performance, productivity or efficiency of software development, software processes, software projects, software developers, or; Relations between different direct measurements or attributes (like size and effort, or reliability and effort, lead-time and resources, or multivariate relations) that are used to characterize the performance, productivity or efficiency of software development, software processes, software projects or software developers. Proof of concept, experiment, case study, example or other empirical research methods to show its applicability and usefulness/accuracy. It is also reasonable to consider papers that are based on real-world data from software repositories.

Exclusion Criteria

• Productivicty (efficiency) measurement and prediction is not the main focus. Talking about direct measures that are not combined with other measures and thus no claims regarding productivity, efficiency and performance are possible. The synthesis of evidence is based on the primary studies identified by the search. The secondary studies are excluded from the actual synthesis and results. Talking about measures for single techniques, which do not give an indication how well organizations or teams performs on the overall process level or within a development phase. Studies that have not evaluated a solution (be it in an experiment, proof of concept, or a case study) shall be excluded.

• COCOMO II parameters and IDPD: bilateral relevances
• Structural equation modelling of large-scale information system application development productivity: the Hong Kong experience
• Trade-offs between productivity and quality in selecting software development practices
• Software development productivity of European space, military, and industrial applications
• A machine learning technique for predicting the productivity of practitioners from individually developed software projects
• A field study of scale economies in software maintenance
• A software development productivity model for MIS environments
• Total quality in software development: An empirical study of quality drivers and benefits in Indian software projects

• Structural equation modelling of large-scale information system application development productivity: the Hong Kong experience
• Study Type : Observational
• Quality evaluation
• Evidence
• Trade-offs between productivity and quality in selecting software development practices
• Study Type : Non Systematic
• Quality evaluation
• Evidence
• A machine learning technique for predicting the productivity of practitioners from individually developed software projects
• Study Type : Quasi Experiment
• Quality evaluation
• Evidence
• COCOMO II parameters and IDPD: bilateral relevances
• Study Type : Non Systematic
• Quality evaluation
• Evidence
• Total quality in software development: An empirical study of quality drivers and benefits in Indian software projects
• Study Type : Observational
• Quality evaluation
• Evidence
• A field study of scale economies in software maintenance
• Study Type : Observational
• Quality evaluation
• Evidence
• A DEA--Tobit Analysis to Understand the Role of Experience and Task Factors in the Efficiency of Software Engineers
• Study Type : Observational
• Quality evaluation
• A software development productivity model for MIS environments
• Study Type : Non Systematic
• Quality evaluation
• Evidence
• Software development productivity of European space, military, and industrial applications
• Study Type : Observational
• Quality evaluation
• Evidence

• Loc-Based software size affecting Software Productivity
• Evidence based on the paper "Structural equation modelling of large-scale information system application development productivity: the Hong Kong experience"
• Evidence based on the paper "Software development productivity of European space, military, and industrial applications"
• Evidence based on the paper "Total quality in software development: An empirical study of quality drivers and benefits in Indian software projects"
• Evidence based on the paper "Trade-offs between productivity and quality in selecting software development practices"
• Evidence based on the paper "A machine learning technique for predicting the productivity of practitioners from individually developed software projects"
• Evidence based on the paper "COCOMO II parameters and IDPD: bilateral relevances"
• Evidence based on the paper "A field study of scale economies in software maintenance"
• Evidence based on the paper "A software development productivity model for MIS environments"
• Result

Research question

The aggregated evidence refers to research question about  which factors have been used to define/compose/describe software productivity in prediction and measurement methods.

Loc-Based software size affecting Software Productivity

The purpose of this synthesis is to characterize the effect of Loc-Based software size on software productivity from the point of view of SE researchers in the context of factors described/identified on productivity prediction and measurement methods.

This new and aggregated evidence shows that Level of Loc-Based software size has a weakly positive or positive effect on software productivity (belief =96%).