Developer experience · Systematic literature review

Opinion Mining for Software Development: A Systematic Literature Review

ACM Transactions on Software Engineering and Methodology · 2022

Bin Lin, Nathan Cassee, Alexander Serebrenik, Gabriele Bavota, Nicole Novielli, Michele Lanza

Summary

Maps software-development opinion-mining activities, methods, datasets, tool evaluations, and recurring application concerns; provides guidance for selecting and customizing tools.

For your marketing

Possible founder application

Use structured sentiment/opinion mining on issue trackers, reviews, and developer communications to prioritize product and developer-experience improvements, with validation against labeled data.

Reported result

What the study found

Maps software-development opinion-mining activities, methods, datasets, tool evaluations, and recurring application concerns; provides guidance for selecting and customizing tools.

Research question

What the authors investigated

How does the study’s stated design explain its reported outcome in this setting?

Design

Systematic literature review

Sample and setting

185 papers on opinion mining in software-development activities

Scope and transfer

Limitations to keep in view

Review findings depend on included studies and tool-evaluation quality; it is not a causal meta-analysis of developer outcomes.

Research sources

full_text

Study strength

4/5 Research record provides a clear design and context; apply the finding within its stated limits.

How this was assessed

The 1–5 evidence-check score is a practical reading aid, not a formal peer review or a probability that a conclusion is true. It combines design strength (2 points), sample reporting (1), comparison/control clarity (1), and how much of the paper could be checked (1). Access affects how confidently this directory can assess a study, not the study's underlying quality. Blinding is reported separately because it is not relevant to every design.

Design transparency · 2/2

Based on the reported study design in the retrieved source.

Sample and setting · 1/1

The sample context is stated; a numerical count is preserved only when reported.

Outcome clarity · 1/1

The finding is summarized from publisher or article metadata.

Access for checking · 1/1

Full text was identified.

Double-blind? The retrieved publisher record does not establish whether participants or outcome assessors were blinded.

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