Software component testing : a standard and the effectiveness of techniques

This portfolio comprises two projects linked by the theme of software component testing, which is also often referred to as module or unit testing. One project covers its standardisation, while the other considers the analysis and evaluation of the application of selected testing techniques to an existing avionics system. The evaluation is based on empirical data obtained from fault reports relating to the avionics system. The standardisation project is based on the development of the BC BSI Software Component Testing Standard and the BCS/BSI Glossary of terms used in software testing, which are both included in the portfolio. The papers included for this project consider both those issues concerned with the adopted development process and the resolution of technical matters concerning the definition of the testing techniques and their associated measures. The test effectiveness project documents a retrospective analysis of an operational avionics system to determine the relative effectiveness of several software component testing techniques. The methodology differs from that used in other test effectiveness experiments in that it considers every possible set of inputs that are required to satisfy a testing technique rather than arbitrarily chosen values from within this set. The three papers present the experimental methodology used, intermediate results from a failure analysis of the studied system, and the test effectiveness results for ten testing techniques, definitions for which were taken from the BCS BSI Software Component Testing Standard. The creation of the two standards has filled a gap in both the national and international software testing standards arenas. Their production required an in-depth knowledge of software component testing techniques, the identification and use of a development process, and the negotiation of the standardisation process at a national level. The knowledge gained during this process has been disseminated by the author in the papers included as part of this portfolio. The investigation of test effectiveness has introduced a new methodology for determining the test effectiveness of software component testing techniques by means of a retrospective analysis and so provided a new set of data that can be added to the body of empirical data on software component testing effectiveness

Empirical Evaluation of Mutation-based Test Prioritization Techniques

We propose a new test case prioritization technique that combines both mutation-based and diversity-based approaches. Our diversity-aware mutation-based technique relies on the notion of mutant distinguishment, which aims to distinguish one mutant's behavior from another, rather than from the original program. We empirically investigate the relative cost and effectiveness of the mutation-based prioritization techniques (i.e., using both the traditional mutant kill and the proposed mutant distinguishment) with 352 real faults and 553,477 developer-written test cases. The empirical evaluation considers both the traditional and the diversity-aware mutation criteria in various settings: single-objective greedy, hybrid, and multi-objective optimization. The results show that there is no single dominant technique across all the studied faults. To this end, \rev{we we show when and the reason why each one of the mutation-based prioritization criteria performs poorly, using a graphical model called Mutant Distinguishment Graph (MDG) that demonstrates the distribution of the fault detecting test cases with respect to mutant kills and distinguishment

An empirical investigation into branch coverage for C programs using CUTE and AUSTIN

Automated test data generation has remained a topic of considerable interest for several decades because it lies at the heart of attempts to automate the process of Software Testing. This paper reports the results of an empirical study using the dynamic symbolic-execution tool. CUTE, and a search based tool, AUSTIN on five non-trivial open source applications. The aim is to provide practitioners with an assessment of what can be achieved by existing techniques with little or no specialist knowledge and to provide researchers with baseline data against which to measure subsequent work. To achieve this, each tool is applied 'as is', with neither additional tuning nor supporting harnesses and with no adjustments applied to the subject programs under test. The mere fact that these tools can be applied 'out of the box' in this manner reflects the growing maturity of Automated test data generation. However, as might be expected, the study reveals opportunities for improvement and suggests ways to hybridize these two approaches that have hitherto been developed entirely independently. (C) 2010 Elsevier Inc. All rights reserved