Fault detection power of unit and system testing in Java open source projects

Abstract

Testing is one of the most crucial steps in providing quality for software products. Two key and heavily used testing levels are unit and system testing, each level hav ing different benefits and drawbacks. For their testing process a software team needs to decide where the focus and effort should be put, often by creating a strategy for testing. Because the resources are limited, a critical question is “what is a good trade-off between different levels of testing in order to maximize the effect, i.e. qual ity improvement and assurance while using as few resources as possible”. There are a lot of factors to consider for this trade-off, from costs to time and knowledge of testers, but in this study we focus on a critical one: the fault-finding ability and behaviour of tests on different levels. To evaluate the fault finding behaviour of unit and system tests, a reliable method for test level categorization is needed. Based on the attributes found in the common definitions for the testing levels, a framework for categorization was developed and applied to analyse the usage of unit and system level testing on selected Java open source projects from the Defects4j framework. Furthermore, using information pro vided by the Defects4j tool the fault detection level of different tests and, ultimately, of the different levels can be determined. The 16 analysed projects contained 25477 tests, where 78.4% of tests were categorized as low level and 21.56% as high level. The results indicate that lower, unit level tests are used more in the investigated Java open source projects. Looking at fault finding ability, from the 25477 tests, only 998 tests were able to uncover bugs. From these 998 tests, 65.73% of tests were categorized as low level and 34.27% were categorized as high level. It should be mentioned that this result can be attributed to the fact that there was a higher number of low level tests in the sample. Considering the rate of bug discoverability from the total number of tests on the respective levels, the high level performed better, with a discoverability rate of 6.23% while the low level had a rate of 3.28%. The major contribution of this paper is a framework for test categorization on a low to a high-level scale, based on concrete and objective metrics that can be practically applied on projects that subscribe to the object-oriented paradigm. Additionally, backed on empirical data, we found out that high level tests have a higher rate of discovering bugs.