Software Quality: How Much Does It Matter?

Abstract

Interconnected computers and software systems have become an indispensable part of people’s lives in the period of digital transformation. Consequently, software quality research is becoming more and more critical. There have been multiple attempts to synthesise knowledge gained in software quality research; however, they were focused mainly on single aspects of software quality and did not structure the knowledge holistically. To fill this gap, we harvested software quality publications indexed in the Scopus bibliographic database. We analysed them using synthetic content analysis which is a triangulation of bibliometrics and content analysis. The search resulted in 15,468 publications. The performance bibliometric analysis showed that the production of research publications relating to software quality is currently following an exponential growth trend and that the software quality research community is growing. The most productive country was the United States, followed by China. The synthetic content analysis revealed that the published knowledge could be structured into six themes, the most important being the themes regarding software quality improvement by enhancing software engineering, advanced software testing and improved defect and fault prediction with machine learning and data mining.

Machine Learning, Mechatronics, and Stretch Forming: A History of Innovation in Manufacturing Engineering

“…Notably, the United States emerges as the leading contributor in this domain. Key areas of focus revolve around optimizing software engineering practices to enhance the overall quality of software, implementing advanced techniques for software testing, and harnessing the power of machine learning and data mining to predict defects and faults more effectively [183].…”

Practical Consequences of Quality Views in Assessing Software Quality

“…The authors declare no conflicts of interest. # the output of the fuzzy model was collected while the inputs were increased by a step # size 5 in the range [0; 100], i.e., 21 steps from 0 to 100 # we have 4 inputs, which result in 194481 rows (21^4 = 194481 rows) df_input5 <-read.csv(INPUT_FILE5, sep = ",") colnames(df_input5) <-c("Accuracy", "Legibility", "Implementation", "Security", "Quality") # checking the data structure and variable types for the data frame str(df_input5) # fitting GAM, number of basis functions for the predictor Security was increased to k=15 # so that we could get appropriate effective degree of freedom (EDF) with gam.check() model_gam5 <-gam(Quality ~s(Accuracy) + s(Legibility) + s(Implementation) + s(Security, k=15), data=df_input5, method="REML") # plotting GAM # shifting the standard errors and the curve with the intercept # to get directly interpretable results with regard to the outcome plot(model_gam5, all.terms = TRUE, pages = 1, se=TRUE, seWithMean = TRUE, shift = coef(model_gam5) [1])…”

“…Software quality has gained more influence in recent years, as evidenced by the exponential growth of the identified publications in this field by a mapping study [1]. Software quality assessment encompasses two major approaches: (1) the measurement and assessment of the processes that result in a software product, and (2) the measurement and assessment of a software product directly [2,3].…”

Advanced Undergraduate Computing Students' Perception of Software Quality Teaching: a Survey in the Brazilian Paraná State

“…For software users, quality is related to the usability and implementation of required functionalities. As for software developers, the most important quality issue is that the software meets the specifications and provides services as previously contracted [Tian 2005, Kokol 2022]. Therefore, quality is subjectively determined by those who interact with the system, whether to solve their problems through software or are responsible for designing, implementing, and testing the solutions, making judgments about the quality of the product [Gillies 2011, Suali et al 2019.…”