A Systematic Review of Concolic Testing with Aplication of Test Criteria

Abstract

We present in this paper a systematic review, using approach, of methods, techniques and tools regarding to concolic testing with application of test criteria. The test activity is the process of running a program with the intent of discovering defects. The search for test cases to increase the coverage of structural tests is being addressed by approaches that generate test cases using symbolic and concolic execution. Concolic testing is an effective technique for automated software testing, that aims to generate test inputs to locate failures of implementation in a program. Application of a test criterion is very important to ensure the quality of the test cases used. The number of elements exercised provides a measure of coverage that can be used to evaluate the test data set and consider the test activity to be closed.

Assessing test artifact quality—A tertiary study

“…To the best of our knowledge, there is no tertiary study on the quality of test artifacts. Since this topic has been discussed to some extent in secondary studies (e.g., [8,32,74,85,89]) a synthesis of the state of the art in this area would be helpful for researchers as well as for practitioners.…”

“…For each paper, a reviewer first screened its title and abstract against the exclusion criteria to exclude papers which are outside the scope of this review. After that, the reviewers referred to the inclusion criteria to decide 8 Garousi et al's [40] initial set of 121 papers contained 63 informal surveys without research questions. Since we only were targeting systematic studies, these were excluded.…”

Exploratory Review of Hybrid Fuzzing for Automated Vulnerability Detection

“…In 1999, Edvardsson [22] conducted a survey on the use of SE for an automatic test-input generation. Moreover, several meta-studies and reviews [23]- [27] have focused on practical SE/CE, results of evaluations and overview optimizations in SE/CE. Fuzzing has been empirically reviewed as a vulnerability identification technique by Sutton et al [17], and Richard McNally et al [28].…”