TU/e - Software of Alessandro Di Bucchianico

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Successful testing processes require excellence in both software testing and management. In order to support well-founded decisions on issues like resource allocation and software release moments, quantitative procedures are indispensable. Since few testing processes have a deterministic course, statistics is very often an appropriate part of such quantitative procedures. Existing tools for software reliability analysis like Casre and Smerfs do not make full use of state-of-the-art statistical methodology or do not conform to best practices in statistics. Thus, these tools cannot fully support sound software reliability analyses. We decided to build a new tool that

uses well-documented state-of-the-art algorithms
is platform independent
encourages to apply best practices from statistics
can easily be extended to incorporate new models.

In order to meet these requirements we decided to use Java for the interface and the statistical programming language R for the statistical computations. R is open-source free software maintained by a group of top-level statisticians and is rapidly becoming the standard programming language within the statistical community. Our tool is a joint project of Eindhoven University of Technology and Refis . The tool development was financially supported by a grant of the Dutch Innovation Platform.

Features of this tool include:

numerically stable algorithms for ML estimation
check for existence of ML estimators
statistically sound workflow
graphical methods (including TTT plot) and trend tests for software reliability growth testing
model selection matrix
model selection wizard
supports both exact data as interval data


Trend tests	Model selection wizard	Analysis results

Available background information

Boon et al, A New Statistical Software Reliability Tool (paper describing the background of SRETool)
Corro Ramos et al, Software Reliability Growth Models: Systematic Descriptions and Implementations (presentation giving a quick introduction to the philosophy behind the SRETool)
Di Bucchianico et al, A Documentation Structure for Software Reliability Growth (paper describing a systematic way to describe software reliability growth models)
Brandt et al, Two Case Studies in Applying Statistical Models in Software Development (paper that describes practical issues in software reliability engineering)

Last modified: March 7, 2017