White Rose University Consortium logo
University of Leeds logo University of Sheffield logo York University logo

Automated Unit Testing of Evolving Software

Shamshiri, Sina (2016) Automated Unit Testing of Evolving Software. PhD thesis, University of Sheffield.

[img] Text (Thesis - Automated Unit Testing of Evolving Software)
thesis.pdf
Restricted until 27 April 2020.

Request a copy

Abstract

As software programs evolve, developers need to ensure that new changes do not affect the originally intended functionality of the program. To increase their confidence, developers commonly write unit tests along with the program, and execute them after a change is made. However, manually writing these unit-tests is difficult and time-consuming, and as their number increases, so does the cost of executing and maintaining them. Automated test generation techniques have been proposed in the literature to assist developers in the endeavour of writing these tests. However, it remains an open question how well these tools can help with fault finding in practice, and maintaining these automatically generated tests may require extra effort compared to human written ones. This thesis evaluates the effectiveness of a number of existing automatic unit test generation techniques at detecting real faults, and explores how these techniques can be improved. In particular, we present a novel multi-objective search-based approach for generating tests that reveal changes across two versions of a program. We then investigate whether these tests can be used such that no maintenance effort is necessary. Our results show that overall, state-of-the-art test generation tools can indeed be effective at detecting real faults: collectively, the tools revealed more than half of the bugs we studied. We also show that our proposed alternative technique that is better suited to the problem of revealing changes, can detect more faults, and does so more frequently. However, we also find that for a majority of object-oriented programs, even a random search can achieve good results. Finally, we show that such change-revealing tests can be generated on demand in practice, without requiring them to be maintained over time.

Item Type: Thesis (PhD)
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Computer Science (Sheffield)
The University of Sheffield > Faculty of Science (Sheffield) > Computer Science (Sheffield)

The University of Sheffield > Faculty of Engineering (Sheffield)
Depositing User: Sina Shamshiri
Date Deposited: 05 May 2017 13:50
Last Modified: 05 May 2017 13:50
URI: http://etheses.whiterose.ac.uk/id/eprint/17066

Actions (repository staff only: login required)