Improving Software Quality by Synergizing Effective Code Inspection and Regression Testin

Many dynamic and static program analysis techniques have been proposed, but testing a program involves substantial cost and risks and inspecting code change is tedious and error-prone. Our research addresses two fundamental problems in dynamic and static techniques. (1) To evaluate a program, developers are typically required to implement test cases and reuse them. As they develop more test cases for verifying new implementations, the execution cost of test cases increases accordingly. After every modification, they periodically conduct regression test to see whether the program executes without introducing new faults in the presence of program evolution. To reduce the time required to perform regression testing, developers should select an appropriate subset of the test suite with a guarantee of revealing faults as running entire test cases. Such regression testing selection techniques are still challenging as these methods also have substantial costs and risks and discard test cases that could detect faults. (2) As a less formal and more lightweight method than running a test suite, developers often conduct code reviews based on tool support; however, understanding context and changes is the key challenge of code reviews. While reviewing code changes---addressing one single issue---might not be difficult, it is extremely difficult to understand complex changes---including multiple issues such as bug fixes, refactorings, and new feature additions. Developers need to understand intermingled changes addressing multiple development issues, finding which region of the code changes deals with a particular issue. Although such changes do not cause trouble in implementation, investigating these changes becomes time-consuming and error-prone since the intertwined changes are loosely related, leading to difficulty in code reviews.;To address the limitations outlined above, our research makes the following contributions. First, we present a model-based approach to efficiently build a regression test suite that facilitates Extended Finite State Machines (EFSMs). Changes to the system are performed at transition level by adding, deleting or replacing transition. Tests are a sequence of input and expected output messages with concrete parameter values over the supported data types. Fully-observable tests are introduced whose descriptions contain all the information about the transitions executed by the tests. An invariant characterizing fully observable tests is formulated such that a test is fully-observable whenever the invariant is a satisfiable formula. Incremental procedures are developed to efficiently evaluate the invariant and to select tests from a test suite that are guaranteed to exercise a given change when the tests run on a modified EFSM. Tests rendered unusable due to a change are also identified. Overlaps among the test descriptions are exploited to extend the approach to simultaneously select and discard multiple tests to alleviate the test selection costs. Although test regression selection problem is NP-hard, the experimental results show the cost of our test selection procedure is still acceptable and economical. Second, to support code review and regression testing, we present a technique, called C hgCutter. It helps developers understand and validate composite changes as follows. It interactively decomposes these complex, composite changes into atomic changes, builds related change subsets using program dependence relationships without syntactic violation, and safely selects only related test cases from the test suite to reduce the time to conduct regression testing. When a code reviewer selects a change region from both original and changed versions of a program, ChgC utter automatically identifies similar change regions based on the dependence analysis and the tree-based code search technique. By automatically applying a change to the identified regions in an original program version, ChgCutter generates a program version, which is a syntactically correct version of program. Given a generated program version, it leverages a testing selection technique to select and run a subset of the test suite affected by a change automatically separated from mixed changes. Based on the iterative change selection process, there can be each different program version that include its separated change. Therefore, ChgC utter helps code reviewers inspect large, complex changes by effectively focusing on decomposed change subsets. In addition to assisting understanding a substantial change, the regression testing selection technique effectively discovers defects by validating each program version that contains a separated change subset. In the evaluation, ChgCutter analyzes 28 composite changes in four open source projects. It identifies related change subsets with 95.7% accuracy, and it selects test cases affected by these changes with 89.0% accuracy. Our results show that ChgC utter should help developers effectively inspect changes and validate modified applications during development. (Abstract shortened by ProQuest.).