Software architecture: perspectives on an emerging discipline
Software architecture: perspectives on an emerging discipline
Experiments of the effectiveness of dataflow- and controlflow-based test adequacy criteria
ICSE '94 Proceedings of the 16th international conference on Software engineering
Use of relative code churn measures to predict system defect density
Proceedings of the 27th international conference on Software engineering
Observations and lessons learned from automated testing
Proceedings of the 27th international conference on Software engineering
How Well Do Professional Developers Test with Code Coverage Visualizations? An Empirical Study
VLHCC '05 Proceedings of the 2005 IEEE Symposium on Visual Languages and Human-Centric Computing
Agile Software Testing in a Large-Scale Project
IEEE Software
Future of developer testing: building quality in code
Proceedings of the FSE/SDP workshop on Future of software engineering research
Xest: an automated framework for regression testing of embedded software
WESE '10 Proceedings of the 2010 Workshop on Embedded Systems Education
An evaluation of change-based coverage criteria
Proceedings of the 10th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools
Comparing multi-point stride coverage and dataflow coverage
Proceedings of the 2013 International Conference on Software Engineering
CodeCover: enhancement of CodeCover
ACM SIGSOFT Software Engineering Notes
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Recently, tools for the analysis and visualization of code coverage have become widely available. At first glance, their value in assessing and improving the quality of automated test suites seems to be obvious. Yet, experimental studies as well as experience from projects in industry indicate that their use is not without pitfalls. We found these tools in a number of recent projects quite beneficial. Therefore, we set out to gather code coverage information from one of these projects. In this experience report, first the system under scrutiny as well as our methodology is described. Then, four major questions concerning the impact and benefits of using these tools are discussed. Furthermore, a list of ten lessons learned is derived. The list may help developers judiciously use code coverage tools, in order to reap a maximum of benefits.