You are provided with the abstract of a scientific paper and the abstracts of the papers it references. Your task is to write a Related Work section for the main paper. This section should concisely summarize and integrate the key points from the cited abstracts, reflecting how they relate to the main paper's contributions and context. In your summary, use numerical citation markers like [1], [2], etc., to refer to the corresponding papers.

Main Abstract:
Regression testing is performed to provide confidence that changes in a part of software do not affect other parts of the software. An execution of all existing test cases is the best way to re-establish this confidence. However, regression testing is an expensive process---there might be insufficient resources (e.g., time, workforce) to allow for the re-execution of all test cases. Regression test prioritization techniques attempt to re-order a regression test suite based on some criteria so that highest priority test cases are executed earlier. In this study, we want to prioritize test cases for regression testing based on the dependency network of faults. In software testing, it is common that some faults are consequences of other faults (leading faults). Moreover, dependent faults can be removed if and only if the leading faults have been removed. Our goal is to prioritize test cases so that test cases that exposed leading faults (the most central faults in the fault dependency network) in the system testing phase, are executed first in regression testing. We present ComReg, a test case prioritization technique based on the dependency network of faults. We model a fault dependency network as a directed graph and identify leading faults to prioritize test cases for regression testing. We use a centrality aggregation technique which considers six network representative centrality metrics to identify leading faults in the fault dependency network. We also discuss the use of fault communities to select an arbitrary percentage of the test cases from a prioritized regression test suite. We conduct a case study that evaluates the effectiveness and applicability of the proposed method.

Cited Abstract(s):
[1]: Test case prioritization techniques have been shown to be beneficial for improving regression-testing activities. With prioritization, the rate of fault detection is improved, thus allowing testers to detect faults earlier in the system-testing phase. Most of the prioritization techniques to date have been code coverage-based. These techniques may treat all faults equally. We build upon prior test case prioritization research with two main goals: (1) to improve user-perceived software quality in a cost effective way by considering potential defect severity and (2) to improve the rate of detection of severe faults during system-level testing of new code and regression testing of existing code. We present a value-driven approach to system-level test case prioritization called the prioritization of requirements for test (PORT). PORT prioritizes system test cases based upon four factors: requirements volatility, customer priority, implementation complexity, and fault proneness of the requirements. We conducted a PORT case study on four projects developed by students in advanced graduate software testing class. Our results show that PORT prioritization at the system level improves the rate of detection of severe faults. Additionally, customer priority was shown to be one of the most important prioritization factors contributing to the improved rate of fault detection.

[2]: Test case prioritization involves scheduling test cases in an order that increases the effectiveness in achieving some performance goals. One of the most important performance goals is the rate of fault detection. Test cases should run in an order that increases the possibility of fault detection and also that detects the most severe faults at the earliest in its testing life cycle. In this paper, we propose to put forth a model for system level test case prioritization (TCP) from software requirement specification to improve user satisfaction with quality software that can also be cost effective and to improve the rate of severe fault detection. The proposed model prioritizes the system test cases based on the six factors: customer priority, changes in requirement, implementation complexity, completeness, traceability and fault impact. The proposed prioritization technique is validated with two different validation techniques and is experimented in three phases with student projects and two sets of industrial projects and the results show convincingly that the proposed prioritization technique improves the rate of severe fault detection.
consider a software's requirements as a basis for prioritization of test cases. [1] prioritized test cases based on four factors: requirements volatility, customer priority, implementation complexity, and fault proneness of the requirements. Krishnamoorthi at al. [2] adopted a similar approach. Their prioritization is based on six factors: customer priority, changes in requirement, implementation complexity, completeness, traceability and fault impact. However, a potential weakness of requirement-based approaches is that requirement properties are subjective and thus estimations might be biased.