Pub Date : 2002-11-12DOI: 10.1109/ISSRE.2002.1173228
Chin-Yu Huang, J. Lo, S. Kuo, Michael R. Lyu
In this paper, based on software reliability growth models with generalized logistic testing-effort function, we study three optimal resource allocation problems in modular software systems during the testing phase: 1) minimization of the remaining faults when a fixed amount of testing-effort and a desired reliability objective are given; 2) minimization of the required amount of testing-effort when a specific number of remaining faults and a desired reliability objective are given; and 3) minimization of the cost when the number of remaining faults and a desired reliability objective are given. Several useful optimization algorithms based on the Lagrange multiplier method are proposed and numerical examples are illustrated. Our methodologies provide practical approaches to the optimization of testing-resource allocation with a reliability objective. In addition, we also introduce the testing-resource control problem and compare different resource allocation methods. Finally, we demonstrate how these analytical approaches can be employed in the integration testing. Using the proposed algorithms, project managers can allocate limited testing-resource easily and efficiently and thus achieve the highest reliability objective during software module and integration testing.
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Pub Date : 2002-11-12DOI: 10.1109/ISSRE.2002.1173209
G. Lussier, H. Waeselynck
This paper aims at verifying properties of generic fault-tolerance algorithms. Our goal is to enhance the testing process with information extracted from the proof of the algorithm, whether this proof is formal or informal: ideally, testing is intended to focus on the weak parts of the proof (e.g., unproved lemmas or doubtful informal evidence). We use the Fault-Tolerant Rate Monotonic Scheduling algorithm as a case study. This algorithm was proven by informal demonstration, but two faults were revealed afterwards. In this paper, we focus on the analysis of the informal proof, which we restructure in a semiformal proof tree based on natural deduction. From this proof tree, we extract several functional cases and use them for testing a prototype of the algorithm. Experimental results show that a flawed informal proof does not necessarily provide relevant information for testing. It remains to investigate whether formal (partial) proofs allow better connection with potential faults.
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