Communications of the ACM
Automatic Debugging of Software
Researchers at Singapore Management University have developed a new automated approach for debugging software.
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Singapore Management University (SMU) researchers have developed Adaptive Multimodal Bug Localization (AML), an adaptable, automated approach for debugging software that combines elements of previous solutions.
AML collects debugging hints from both bug reports and test cases, and then performs statistical analysis to pinpoint program elements that are likely to contain bugs.
"While most past studies only demonstrate the applicability of similar solutions for small programs and 'artificial bugs' [bugs that are intentionally inserted into a program for testing purposes], our approach can automate the debugging process for many real bugs that impact large programs," says SMU researcher David Lo.
AML has been successfully evaluated on programs with more than 300,000 lines of code. Automatically identifying buggy code will help developers save time and enable them to redirect their debugging efforts to designing new software features.
The researchers also want to develop an Internet-scale software analytics solution, which would involve analyzing massive amounts of data that passively exist in online repositories. Lo says the technique would transform manual, painstaking, and error-prone software engineering tasks into automated activities that can be performed efficiently and reliably.
From Singapore Management University (Singapore)
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