scholarly journals Beyond evolutionary algorithms for search-based software engineering

2018 ◽  
Vol 95 ◽  
pp. 281-294 ◽  
Author(s):  
Jianfeng Chen ◽  
Vivek Nair ◽  
Tim Menzies
Keyword(s):  
Software Engineering ◽  
Evolutionary Algorithms ◽  
Search Based Software Engineering

scholarly journals Performance Evaluation Metrics for Multi-Objective Evolutionary Algorithms in Search-Based Software Engineering: Systematic Literature Review

2021 ◽  
Vol 11 (7) ◽  
pp. 3117
Author(s):  
Jamal Abdullahi Nuh ◽  
Tieng Wei Koh ◽  
Salmi Baharom ◽  
Mohd Hafeez Osman ◽  
Si Na Kew
Keyword(s):  
Systematic Review ◽  
Software Engineering ◽  
Evolutionary Algorithms ◽  
Software Verification ◽  
Performance Metrics ◽  
Scientific Evidence ◽  
Engineering Problem ◽  
Software Project ◽  
Search Based Software Engineering ◽  
Multi Objective

Many recent studies have shown that various multi-objective evolutionary algorithms have been widely applied in the field of search-based software engineering (SBSE) for optimal solutions. Most of them either focused on solving newly re-formulated problems or on proposing new approaches, while a number of studies performed reviews and comparative studies on the performance of proposed algorithms. To evaluate such performance, it is necessary to consider a number of performance metrics that play important roles during the evaluation and comparison of investigated algorithms based on their best-simulated results. While there are hundreds of performance metrics in the literature that can quantify in performing such tasks, there is a lack of systematic review conducted to provide evidence of using these performance metrics, particularly in the software engineering problem domain. In this paper, we aimed to review and quantify the type of performance metrics, number of objectives, and applied areas in software engineering that reported in primary studies—this will eventually lead to inspiring the SBSE community to further explore such approaches in depth. To perform this task, a formal systematic review protocol was applied for planning, searching, and extracting the desired elements from the studies. After considering all the relevant inclusion and exclusion criteria for the searching process, 105 relevant articles were identified from the targeted online databases as scientific evidence to answer the eight research questions. The preliminary results show that remarkable studies were reported without considering performance metrics for the purpose of algorithm evaluation. Based on the 27 performance metrics that were identified, hypervolume, inverted generational distance, generational distance, and hypercube-based diversity metrics appear to be widely adopted in most of the studies in software requirements engineering, software design, software project management, software testing, and software verification. Additionally, there are increasing interest in the community in re-formulating many objective problems with more than three objectives, yet, currently are dominated in re-formulating two to three objectives.

scholarly journals Quality Indicators in Search-based Software Engineering

2020 ◽  
Vol 29 (2) ◽  
pp. 1-29
Author(s):  
Shaukat Ali ◽  
Paolo Arcaini ◽  
Dipesh Pradhan ◽  
Safdar Aqeel Safdar ◽  
Tao Yue
Keyword(s):  
Software Engineering ◽  
Quality Indicators ◽  
Search Based Software Engineering

A Cooperative Parallel Search-Based Software Engineering Approach for Code-Smells Detection

2014 ◽  
Vol 40 (9) ◽  
pp. 841-861 ◽  
Author(s):  
Wael Kessentini ◽  
Marouane Kessentini ◽  
Houari Sahraoui ◽  
Slim Bechikh ◽  
Ali Ouni
Keyword(s):  
Software Engineering ◽  
Parallel Search ◽  
Code Smells ◽  
Search Based Software Engineering ◽  
Engineering Approach ◽  
Cooperative Parallel Search
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