# Systematic Literature Review on Test Case Selection and Prioritization: A Tertiary Study
## 6 Conclusions  
Our SM adopted quantitative and qualitative analyses to assemble the research findings in the area of TCS&P. The secondary studies (reviews or surveys conducted on primary studies) found in the field of TCS&P were reviewed systematically to obtain an overall picture of the recent findings in the area. This work primarily presented a general data analysis of the papers, and a detailed data analysis of the included studies corresponding to the formulated RQs. The studies were thoroughly analyzed to gather information, and to comprehensively tabulate results and findings. This study can provide a quick guide to researchers working in the area of TCS&P for clear insight into the trends of work undertaken in the area, in addition to the tools, statistical tests, limitations, and probable prospects. One goal of our study was the detailed analysis of the 22 selected secondary studies to find common findings and limitations. Although we identified very few common findings, we tried to compile results and generate conclusions from them. These are stated as follows:  
* Five of the studies [S1, S2, S13, S15, S16] report that programs downloaded from SIR (Software-artifact Infrastructure Repository) are the most commonly used benchmark programs for the evaluation of the techniques in the area. * Four studies [S13, S14, S16, S21] noted that APFD (Average Percentage of Faults Detected) is the most preferred metric in the assessment of techniques in regression TCS&P. * Three studies [S7, S18, S19] recorded that GA (genetic algorithm) is the most commonly used approach employed by the researchers working in the area. * Four studies [S8, S11, S14, S19] concluded that coverage-based selection and prioritization is the most preferred criterion, whereas S15 reports that there is a paradigm shift from coverage-based to nature-inspired or search-based approaches. * S21 reports that a history-based system is the most preferred criterion by researchers working in regression TCS&P. We also identified some common problems, research gaps, or limitations identified by the analysis of the surveys. * The studies S1, S10, and S11 observed that regression TCS&P techniques had been applied to limited and usually small test benches (as reported by [S4]). * The studies S1, S3, and S19 showed that there is a lack of application of regression TCS&P techniques to testing for non-functional requirements. * Two studies, S7 and S16, reported a lack of common tools used in TCS&P. The studies S10 and S16 state that the prioritization techniques available in the literature do not provide the execution order of the prioritized test cases. * S19 and S21 highlight the fact that there is a gap in the literature on how to achieve tighter integration between the regression techniques and debugging techniques. * S7 highlights that most of the regression TCS&P techniques proposed have focused on a particular application domain or are context-specific; hence, assessment of the superiority of a technique over the others is not possible. It also notes the gap in the lack of techniques for mobile applications or web services, and the lack of regression TCS&P techniques for software using GUI or complex domain software. * S10 stated that most of the existing prioritization techniques are evaluated using APFD. This measurement, however, suffers from a large number of constraints in practice. The analysis of the studies enables a collective report of the following prospects of future work in the area, which may also overcome limitations and gaps. * Our analysis indicates a major gap in the usage of statistical tests in regression TCS&P. This opens an opportunity to researchers who could make use of statistical tests for qualitative assessment, validation, and comparison of the techniques used in TCS&P in the future. * S7, S1, and S3 recommended the use of TCS&P techniques for software domains such as SOA, web services, and model-based testing, and embedded, real-time, and safety-critical software.