# Systematic Literature Review on Test Case Selection and Prioritization: A Tertiary Study
## 4 Results and Analysis
### RQ5. What Are the Probable Prospects in TCS&P? **RQ 5.1:**_What are the TCS&P techniques as mentioned in the secondary studies?_  
Here we present categories of TCS&P techniques in a tabular manner (Table 9) to highlight the kinds of techniques available in the area. The second column indicates the studies which mention the technique. The techniques (Coverage-based, History-based, Requirement-based, Model-based, and Fault-based) were categorized into over 10 surveys; however, all of these are old techniques. In addition, we observed that Evolutionary techniques (which include Search-based, GA-based, ACO-based, ABC and BA, and hill climbing) saw a significant rise in development after 2015. Hence, to keep up with the current research, it would be informative to identify the trend in research on evolutionary techniques. The subsequent RQ analyzes and addresses this aspect. \begin{table}
\begin{tabular}{c c c} \hline \hline
**S. No.** & **Category** & **Studies in Which Mentioned** \\ \hline
1 & Coverage-based approach & S1, S5, S6, S7, S10, S12, S13, S14, S17, S20, S21, S22 \\ \hline
2 & Distribution-based approach & S1, S5, S21 \\ \hline
3 & Human-based approach & S1, S5, S21 \\ \hline
4 & Probabilistic approach & S1, S5, S21 \\ \hline
5 & History-based & S1, S5, S6, S8, S12, S13, S14, S17, S21, S22 \\ \hline
6 & Requirement-based & S1, S5, S6, S12, S13, S14, S15, S17, S20, S21, S22 \\ \hline
7 & Model-based & S1, S5, S8, S13, S14, S16, S17, S19, S20, S21 \\ \hline
8 & Component-based & S3 \\ \hline
9 & Cost-aware approach & S5, S14, S15, S17, S21 \\ \hline
10 & Interface-contract mutation & S5 \\ \hline
11 & Relevant slices & S5 \\ \hline
12 & Call tree-paths & S5 \\ \hline
13 & Composite & S6 \\ \hline
14 & Fault-based & S6, S8, S12, S13, S15, S16, S17, S19, S20, S22 \\ \hline
15 & Genetic algorithm-based & S1, S4, S6, S7, S8, S9, S10, S11, S12, S13, S14, S15, \\  & & S17, S18, S19, S20 \\ \hline
16 & AI-based & S8 \\ \hline
17 & Risk-based & S12, S14, S17, S22 \\ \hline
18 & Search-based or evolutionary & S12, S13, S14, S15, S17, S19, S20, S22 \\ \hline
19 & Similarity-based & S13 \\ \hline
20 & Program structure-based & S3, S13 \\ \hline
21 & Oracle-based & S13 \\ \hline
22 & Time aware prioritization & S14, S19 \\ \hline
23 & GUI/Web application-based & S3, S14 \\ \hline
24 & ACO-based & S12, S14, S15, S17, 20 \\ \hline
25 & Clustering & S14 \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Category of TCS&P techniques mentioned in the studies. **RQ 5.2:**_What is the extent of Evolutionary techniques in secondary studies?_  
Recent research has witnessed the advent of many evolutionary techniques, such as GA, ACO, and hill climbing. New evolutionary techniques are continuously being developed and applied to various optimization problems, including software engineering problems [89; 90; 91]. TCS&P is also an optimization problem and hence has benefitted from various evolutionary techniques. Table 10 summarizes the details of the evolutionary techniques used in TCS&P in the 22 secondary studies. Twelve evolutionary techniques were detected as part of the secondary studies. Table 8 shows the details of the studies where they appear, with quick references to the primary studies in which the techniques were applied to TCS&P.