Raúl A. Santelices

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Lightweight fault-localization techniques use program coverage to isolate the parts of the code that are most suspicious of being faulty. In this paper, we present the results of a study of three types of program coverage—statements, branches, and data dependencies—to compare their effectiveness in localizing faults. The study shows that no(More)
One activity performed by developers during regression testing is test-suite augmentation, which consists of assessing the adequacy of a test suite after a program is modified and identifying new or modified behaviors that are not adequately exercised by the existing test suite and, thus, require additional test cases. In previous work, we proposed MATRIX,(More)
This paper presents a new test-suite augmentation technique for use in regression testing of software. Our technique combines dependence analysis and symbolic evaluation and uses information about the changes between two versions of a program to (1) identify parts of the program affected by the changes, (2) compute the conditions under which the effects of(More)
This paper presents a new technique, called <i>Symbolic Program Decomposition</i> (or SPD), for symbolic execution of multiple paths that is more scalable than existing techniques, which symbolically execute control-flow paths individually. SPD exploits control and data dependencies to avoid analyzing unnecessary combinations of subpaths. SPD can also(More)
Test-suite augmentation for evolving software -- the process of augmenting a test suite to adequately test software changes -- is necessary for any program that undergoes modifications as part of its development and maintenance cycles. Recently, we presented a new technique for test-suite augmentation based on leveraging the propagation conditions for the(More)
Structural testing of software requires monitoring the software's execution to determine which program entities are executed by a test suite. Such monitoring can add considerable overhead to the execution of the program, adversely affecting the cost of running a test suite. Thus, minimizing the necessary monitoring activity lets testers reduce testing time(More)
Developers often make multiple changes to software. These changes are introduced to work cooperatively or to accomplish separate goals. However, changes might not interact as expected or may produce undesired side effects. Thus, it is crucial for software-development tasks to know exactly which changes interact. For example, testers need this information to(More)
We describe DUA-Forensics, our open-source Java-bytecode program analysis and instrumentation system built on top of Soot. DUA-Forensics has been in development for more than six years and has supported multiple research projects on efficient monitoring, test-suite augmentation, fault localization, symbolic execution, and change-impact analysis. Three core(More)
“Change Impact Analysis” is the process of determining the consequences of a modification to software. In theory, change impact analysis should be done during software maintenance, to make sure changes do not introduce new bugs. Many approaches and techniques are proposed to help programmers do change impact analysis automatically. However, it is still an(More)