Grant-in-Aid for General Scientific Research (C)
|Allocation Type||Single-year Grants|
|Research Institution||TOTTORI UNIVERSITY(1993)|
YAMADA Shigeru TOTTORI UNIVERSITY, FACULTY OF ENGINEERING PROFESSOR, 工学部, 教授 (50166708)
|Project Period (FY)
1992 – 1993
Completed(Fiscal Year 1993)
|Budget Amount *help
¥1,300,000 (Direct Cost : ¥1,300,000)
Fiscal Year 1993 : ¥600,000 (Direct Cost : ¥600,000)
Fiscal Year 1992 : ¥700,000 (Direct Cost : ¥700,000)
|Keywords||Software reliability / Reliability measurement and assessment / Software reliability growth model / Project management / Testing-process control / Optimal release problem / Reliability data analysis / Software failure and fault / 確率・統計モデル / ソフトウェア故障・エラー|
Software reiability assessment is very important in developing a quality software product effciently. This research investigates the quantitative measurement and assessment of software reliability more practically than before. The techniques are based on the software reliability growth models which are characterized by stochastic processes such as a nonhomogeneous Poissn process. By making the assumptions on which they are based more realistic, the odels discussed here were designed to describe a software fault-detection process or a software failure-occurrence process during the testing phase of software development. Further, based on the above research results, optimal software release problem and testingprocess control were discussed. That is, we studied the following ten usbjects and culd obtain the useful research results :
(1) Summarizing existing software reliability growth models.
(2) Software reliability assessent in imperfect debugging environment.
(3) Stochastic software reliability growth odeling by using a Gompertz curve.
(4) Software reliability growth modeling with fault detectability.
(5) Software reliability growth modeling by using stochastic differential equations.
(6) Quantifying software availability.
(7) Generalizing a delayd S-shaped software reliability growth model.
(8) Software reliability measurement and assessment with testing-effort expenditures and prior-information on initial fault content.
(9) Predicting optimal software release times.
(10) Formulating and solving optimal testing-effort allocation problems.