STRAIT: A Tool for Automated Software Reliability Growth Analysis

Reliability is an essential attribute of mission-and safety-critical systems. Software Reliability Growth Models (SRGMs) are regression-based models that use historical failure data to predict the reliability-related parameters. At the moment, there is no dedicated tool available that would be able to cover the whole process of SRGMs data preparation and application from issue repositories, discouraging replications and reuse in other projects. In this paper, we introduce STRAIT, a free and open-source tool for automatic software reliability growth analysis which utilizes data from issue repositories. STRAIT features downloading, filtering and processing of data from provided issue repositories for use in multiple SRGMs, suggesting the best fitting SRGM with multiple data snapshots to consider software evolution. The tool is designed to be highly extensible, in terms of additional issue repositories, SRGMs, and new data filtering and processing options. Quality engineers can use STRAIT for the evaluation of their software systems. The research community can use STRAIT for empirical studies which involve evaluation of new SRGMs or comparison of multiple SRGMs.

[1]  Marko Boon,et al.  A new statistical software reliability tool , 2007 .

[2]  Dai Pan,et al.  Architecture-based software reliability modeling , 2006, J. Syst. Softw..

[3]  William H. Farr,et al.  A tool for statistical modeling and estimation of reliability functions for software: SMERFS , 1988, J. Syst. Softw..

[4]  Giancarlo Succi,et al.  Modelling Failures Occurrences of Open Source Software with Reliability Growth , 2010, OSS.

[5]  Domenico Cotroneo,et al.  Debugging‐workflow‐aware software reliability growth analysis , 2017, Softw. Test. Verification Reliab..

[6]  Eila Niemelä,et al.  Survey of reliability and availability prediction methods from the viewpoint of software architecture , 2007, Software & Systems Modeling.

[7]  P. C. Jha,et al.  Software Reliability Growth Models , 2011 .

[8]  Barbora Buhnova,et al.  Failure data collection for reliability prediction models: a survey , 2014, QoSA '14.

[9]  Hironori Washizaki,et al.  Detection of unexpected situations by applying software reliability growth models to test phases , 2015, 2015 IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW).

[10]  J. T. Duane Learning Curve Approach to Reliability Monitoring , 1964, IEEE Transactions on Aerospace.

[11]  Amrit L. Goel,et al.  Time-Dependent Error-Detection Rate Model for Software Reliability and Other Performance Measures , 1979, IEEE Transactions on Reliability.

[12]  Sylvain Metge,et al.  SoRel: A tool for reliability growth analysis and prediction from statistical failure data , 1993, FTCS-23 The Twenty-Third International Symposium on Fault-Tolerant Computing.

[13]  David Chen,et al.  Design Principles and Patterns for Decisional Interoperability , 2005 .

[14]  Robertas Damasevicius,et al.  Quantitative Quality Evaluation of Software Products by Considering Summary and Comments Entropy of a Reported Bug , 2019, Entropy.

[15]  Meng Yue,et al.  REVIEW OF QUANTITATIVE SOFTWARE RELIABILITY METHODS , 2010 .

[16]  Shigeru Yamada,et al.  S-Shaped Reliability Growth Modeling for Software Error Detection , 1983, IEEE Transactions on Reliability.

[17]  Mangey Ram,et al.  Software reliability growth modeling for agile software development , 2017, Int. J. Appl. Math. Comput. Sci..

[18]  Swapna S. Gokhale,et al.  SREPT: software reliability estimation and prediction tool , 1998, Performance evaluation (Print).

[19]  Michael R. Lyu,et al.  Handbook of software reliability engineering , 1996 .

[20]  Heiko Koziolek,et al.  A Large-Scale Industrial Case Study on Architecture-Based Software Reliability Analysis , 2010, 2010 IEEE 21st International Symposium on Software Reliability Engineering.

[21]  P K Kapur,et al.  SOFTWARE RELIABILITY GROWTH MODELS BASED ON NHPP , 1999 .

[22]  Z. Jelinski,et al.  Software reliability Research , 1972, Statistical Computer Performance Evaluation.

[23]  Michael R. Lyu,et al.  CASRE: a computer-aided software reliability estimation tool , 1992, [1992] Proceedings of the Fifth International Workshop on Computer-Aided Software Engineering.

[24]  Hironori Washizaki,et al.  Predicting Release Time for Open Source Software Based on the Generalized Software Reliability Model , 2015, 2015 Agile Conference.

[25]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[26]  George E. Stark A survey of software reliability measurement tools , 1991, Proceedings. 1991 International Symposium on Software Reliability Engineering.

[27]  S. A. Hossain,et al.  Estimating the parameters of a non-homogeneous Poisson-process model for software reliability , 1993 .

[28]  Michael R. Lyu Software Reliability Engineering: A Roadmap , 2007, Future of Software Engineering (FOSE '07).

[29]  Anu G. Aggarwal,et al.  Reliability Growth Analysis for Multi-release Open Source Software Systems with Change Point , 2019 .