Establishing Qualitative Software Metrics in Department of the Navy Programs

2015 ◽  
Author(s):  
Chris Johnson ◽  
Ritesh Patel ◽  
Deyanira Radcliffe ◽  
Paul Lee ◽  
John Nguyen
Keyword(s):  
Software Metrics ◽  
Department Of The Navy

Neural Network Model to Calculate the Creep Data Using Size

2017 ◽  
Vol 7 (8) ◽  
pp. 257
Author(s):  
Seetharam .K ◽  
Sharana Basava Gowda ◽  
. Varadaraj
Keyword(s):  
Neural Network ◽  
Risk Factors ◽  
Software Engineering ◽  
Network Model ◽  
Neural Network Model ◽  
Software Metrics ◽  
Creep Data ◽  
Engineering Software ◽  
Function Points ◽  
Different Levels

In Software engineering software metrics play wide and deeper scope. Many projects fail because of risks in software engineering development[1]t. Among various risk factors creeping is also one factor. The paper discusses approximate volume of creeping requirements that occur after the completion of the nominal requirements phase. This is using software size measured in function points at four different levels. The major risk factors are depending both directly and indirectly associated with software size of development. Hence It is possible to predict risk due to creeping cause using size.

A Literature Review Study of Software Defect Prediction using Machine Learning Techniques

2018 ◽  
Vol 6 (6) ◽  
pp. 300 ◽  
Author(s):  
Feidu Akmel ◽  
Ermiyas Birihanu ◽  
Bahir Siraj
Keyword(s):  
Machine Learning ◽  
Software Metrics ◽  
Quality Standard ◽  
Machine Learning Techniques ◽  
Software Systems ◽  
Health Care Insurance ◽  
Software Defect ◽  
Learning Techniques ◽  
Software Product

Software systems are any software product or applications that support business domains such as Manufacturing,Aviation, Health care, insurance and so on.Software quality is a means of measuring how software is designed and how well the software conforms to that design. Some of the variables that we are looking for software quality are Correctness, Product quality, Scalability, Completeness and Absence of bugs, However the quality standard that was used from one organization is different from other for this reason it is better to apply the software metrics to measure the quality of software. Attributes that we gathered from source code through software metrics can be an input for software defect predictor. Software defect are an error that are introduced by software developer and stakeholders. Finally, in this study we discovered the application of machine learning on software defect that we gathered from the previous research works.

Computation of External view based Software Metrics: Java Based Tool

2017 ◽  
Vol 5 (8) ◽  
pp. 33-43
Author(s):  
P.L. Powar ◽  
M.P. Singh ◽  
Jawwad Wasat Shareef ◽  
Bharat Solanki
Keyword(s):  
Software Metrics ◽  
External View

BETHLEHEM LUKENS PLATE HPS-70W

Alloy Digest ◽  
2000 ◽  
Vol 49 (12) ◽  
Keyword(s):  
Fracture Toughness ◽  
Corrosion Resistance ◽  
Tensile Properties ◽  
High Performance ◽  
Iron And Steel ◽  
Cooperative Agreement ◽  
Federal Highway ◽  
High Performance Steel ◽  
Department Of The Navy ◽  
Steel Institute

Abstract BETHLEHEM LUKENS PLATE HPS-70W is a high-performance steel (HPS) developed through a cooperative agreement among the Federal Highway Administration (FHWA), the American Iron and Steel Institute (AISI), and the Department of the Navy. This steel is an improved version of ASTM A 709 grade 70W. This datasheet provides information on composition and tensile properties as well as fracture toughness. It also includes information on corrosion resistance as well as forming and joining. Filing Code: SA-506. Producer or source: Bethlehem Lukens Plate.

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