Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 126 tok/s
Gemini 2.5 Pro 45 tok/s Pro
GPT-5 Medium 29 tok/s Pro
GPT-5 High 32 tok/s Pro
GPT-4o 127 tok/s Pro
Kimi K2 183 tok/s Pro
GPT OSS 120B 425 tok/s Pro
Claude Sonnet 4.5 38 tok/s Pro
2000 character limit reached

Generating Class-Level Integration Tests Using Call Site Information (2001.04221v4)

Published 13 Jan 2020 in cs.SE

Abstract: Search-based approaches have been used in the literature to automate the process of creating unit test cases. However, related work has shown that generated unit-tests with high code coverage could be ineffective, i.e., they may not detect all faults or kill all injected mutants. In this paper, we propose CLING, an integration-level test case generation approach that exploits how a pair of classes, the caller and the callee, interact with each other through method calls. In particular, CLING generates integration-level test cases that maximize the Coupled Branches Criterion (CBC). Coupled branches are pairs of branches containing a branch of the caller and a branch of the callee such that an integration test that exercises the former also exercises the latter. CBC is a novel integration-level coverage criterion, measuring the degree to which a test suite exercises the interactions between a caller and its callee classes. We implemented CLING and evaluated the approach on 140 pairs of classes from five different open-source Java projects. Our results show that (1) CLING generates test suites with high CBC coverage, thanks to the definition of the test suite generation as a many-objectives problem where each couple of branches is an independent objective; (2) such generated suites trigger different class interactions and can kill on average 7.7% (with a maximum of 50%) of mutants that are not detected by tests generated at the unit level; (3) CLING can detect integration faults coming from wrong assumptions about the usage of the callee class (32 for our subject systems) that remain undetected when using automatically generated unit-level test suites.

Citations (3)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Open Problems

We haven't generated a list of open problems mentioned in this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.