Pith. sign in

REVIEW 2 cited by

A Systematic Review of Productivity Factors in Software Development

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1801.06475 v1 pith:WEQY5N7X submitted 2018-01-19 cs.SE

Stefan Wagner , Melanie Ruhe This is my paper · ORCID
classification cs.SE
keywords factorsproductivitysoftwareanalysisbeendevelopmentengineeringlist
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

Analysing and improving productivity has been one of the main goals of software engineering research since its beginnings. A plethora of studies has been conducted on various factors that resulted in several models for analysis and prediction of productivity. However, productivity is still an issue in current software development and not all factors and their relationships are known. This paper reviews the large body of available literature in order to distill a list of the main factors influencing productivity investigated so far. The measure for importance here is the number of articles a factor is mentioned in. Special consideration is given to soft or human-related factors in software engineering that are often not analysed with equal detail as more technical factors. The resulting list can be used to guide further analysis and as basis for building productivity models.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. The Impact of LLM-Assistants on Software Developer Productivity: A Systematic Review and Mapping Study

    cs.SE 2025-07 conditional novelty 6.0 of 10

    A systematic review of 39 studies shows LLM coding assistants generally improve perceived speed and reduce online search, while code quality outcomes remain inconsistent and long-term team effects are understudied.

  2. Developer Productivity With and Without GitHub Copilot: A Longitudinal Mixed-Methods Case Study

    cs.SE 2025-09 unverdicted novelty 4.0 of 10

    A longitudinal mixed-methods case study in a large public-sector IT organization found no statistically significant increase in commit activity after GitHub Copilot adoption, despite pre-existing activity differences ...

Pith tools