A Baseline Evaluation Method Based on Principal Component Analysis for Software Test Case Design

Software has been widely applied in the field of aerospace telemetry telecontrol & communication (TT&C). Testing is one of the most important means to ensure the quality of TT&C software, and one of the most critical links of software testing is test case design. The adequacy of test case design determines the effectiveness of testing. This paper proposes a baseline evaluation method for test cases of space TT&C software based on principal component analysis. This method extracts the principal components of the factors (software key level, program circle complexity, interface complexity, etc.) that affect test case design in the test project of historical space TT&C software, builds a regression evaluation model, and forms a standard baseline for evaluating the adequacy of test case design. This baseline evaluation method is applied to a real case. The validity of this method is illustrated in one practical case.

[1]  Mark Harman,et al.  Regression testing minimization, selection and prioritization: a survey , 2012, Softw. Test. Verification Reliab..

[2]  César Roberto de Souza A Tutorial on Principal Component Analysis with the Accord.NET Framework , 2012, ArXiv.

[3]  Youqing Wang,et al.  Two-step principal component analysis for dynamic processes , 2017, 2017 6th International Symposium on Advanced Control of Industrial Processes (AdCONIP).

[4]  Guo Y.-F.,et al.  Optimization of aerospace software test cases based on requirement coverage , 2014 .

[5]  Boris Beizer,et al.  Software testing techniques (2. ed.) , 1990 .

[6]  Lionel C. Briand,et al.  A Systematic Review of the Application and Empirical Investigation of Search-Based Test Case Generation , 2010, IEEE Transactions on Software Engineering.

[7]  Gregg Rothermel,et al.  A Static Approach to Prioritizing JUnit Test Cases , 2012, IEEE Transactions on Software Engineering.

[8]  Gregg Rothermel,et al.  Test Case Prioritization: A Family of Empirical Studies , 2002, IEEE Trans. Software Eng..

[9]  Paolo Tonella,et al.  Automated Test Case Generation as a Many-Objective Optimisation Problem with Dynamic Selection of the Targets , 2018, IEEE Transactions on Software Engineering.

[10]  I. Jolliffe Principal Component Analysis , 2002 .

[11]  Chao Chen,et al.  Path generation algorithm for UML graphic modeling of aerospace test software , 2018 .

[12]  Hanli Qiao Discriminative Principal Component Analysis: A REVERSE THINKING , 2019, ArXiv.

[13]  哈清华 Ha Qing-hua,et al.  Test case generation of aerospace software based on modeling requirements , 2016 .

[14]  A. von Mayrhauser,et al.  The Sleuth approach to aerospace software testing , 1995, 1995 IEEE Aerospace Applications Conference. Proceedings.

[15]  James A. Whittaker,et al.  A Markov Chain Model for Statistical Software Testing , 1994, IEEE Trans. Software Eng..

[16]  Gregg Rothermel,et al.  Prioritizing test cases for regression testing , 2000, ISSTA '00.

[17]  Francisco J. Cazorla,et al.  Dynamic software randomisation: Lessons learnec from an aerospace case study , 2017, Design, Automation & Test in Europe Conference & Exhibition (DATE), 2017.