Staffing Level Estimation In Software Engineering
• Allows probability level of estimates, staffing and schedule constraints to be input as independent variables. • Within the last ten years this technique has been applied successfully in the context of software engineering estimation models. Mar 21, 2010 Often, the staffing level is not changed continuously in a project and approximations of the Rayleigh curve are used: assigning a few people at the start, having the peak team during the coding phase, and then leaving a few people for integration and system testing.
Directory of EntryLevel Pharmaceutical, Medical Device, Life Science, Biotechnology Biopharmaceutical Job Listings. Review of ArchiOffice Software system overview, features, price and cost information. Get free demos and compare to similar programs. Specializes in enterprise integration, ebusiness, and ERP enhancement initiatives. Includes client list. Collarini Energy Staffing offers professional staffing services to EPC and EP companies.
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MPI Research Mattawan, MIResearch Associate LBA Development. MSBSBAExp 0 2 yrs. This position is responsible for following established methods to quantify chemical entities according to applicable Standard Operating Procedures SOPs andor Gx. P regulations. This individual demonstrates proficiency in the use of instrumentation and laboratory techniques. This individual contributes to the department by completing assigned projects on time, participating in process improvement initiatives, and communicating effectively with others. MPI Research Mattawan, MIResearch Associate 1 Clinical Pathology.
Effort Estimation In Software Engineering
BSExp 0 2 yrs. This position is responsible for providing humane care to all laboratory animals and to perform assigned technical and administrative functions within the guidelines requirements outlined in a protocol or Standard Operating Procedure SOP, thus producing sound, reliable data from which to evaluate the efficacy or toxicity of a test compound.
Novavax, Inc. Gaithersburg, MDSenior Research Associate.
MS in biological science, molecular biology, immunology. Background It is uncertain whether lower levels of staffing by nurses at hospitals are associated with an increased risk that patients will have complications or die. The Putnam model is an empirical software effort estimation model. The original paper by Lawrence H. Putnam published in 1978 is seen as pioneering work in the field.
Software design is a phase in software engineering, in which a blueprint is developed to serve as a base for constructing the software system. Design Systems, Inc. Provides engineering solutions, offering complete Concept to Commission services for the automotive, food and beverage, pharmaceutical, package.
This individual will play an important role testing clinical samples as well as in assay development and validation. Qualified individuals are expected to generate and qualify cell banks virus banks to perform ELISAs cell based assays for clinical testing, in addition to training new technicians and leading a group of technicians in high throughput clinical testing. Novavax, Inc. Gaithersburg, MDManufacturing Specialist IMSExp 0 yr.
Risk mitigation planning is the process of developing options and actions to enhance opportunities and reduce threats to project objectives. This position will have a wide range of responsibilities to support GMP manufacturing. In addition to a strong technical background, the ideal candidate will have significant experience with continuous improvement initiatives, problem solving, and project management. Novavax, Inc. Gaithersburg, MDAssociate Senior Associate, Analytical Development, Critical Reagents ContractorMS in biological science or biochemistry. Exp 0 yr The candidate is responsible for coordination and hands on execution of development, optimization, and qualification of Reference Standard and Critical Reagents that will be used for vaccine products.
The qualified individual should have general knowledge and experience on analytical techniques commonly used in biotechnology industry such as immunoassays, chromatographic and electrophoretic methods and maintaining database using Excel. Nurix Inc San Francisco, CAResearch AssociateSenior Research Associate BS in immunology, cancer biology or related field. This individual will work closely with our drug discovery project scientists on late stage lead optimization of novel compounds to support dose and schedule optimization, execution of pharmacodynamic biomarker assays, in vivo efficacy, and characterization of ex vivo immune cell function. The candidate must be self driven, organized, able to work well with project scientists, and able to thrive in an exciting environment in a rapidly growing company. Ocular Therapeutix, Inc. Bedford, MAEngineerScientist I, R DBSMS in Chemistry, Bio Medical Engineering, Material Science or related field.
Execute research and development activities as assigned by management, including routine prototype product and processes and documentation. Work with management and project team members to design and implement research or product development program plans. Omeros Seattle, WATemporary Clinical Data Associate. In this role, you will be responsible for supporting the data management study team leads in data cleaning and database testing activities on studies, assisting in ensuring complete, accurate and consistent clinical data output.
Omeros Seattle, WAClinical Data Associate. In this role, you will be responsible for supporting the data management study team leads in data cleaning and database testing activities on studies, assisting in ensuring complete, accurate and consistent clinical data output. Omeros Seattle, WARegulatory Affairs SpecialistSr. BSExp 1 5 yrs. Supporting preparation of program annual reports as well as CMC, nonclinical, pharmacovigilance, and clinical regulatory filings. Thermo Fisher Scientific South San Francisco, CAScientist I, Molecular Biology. BS in Biochemistry, Molecular Biology or discipline.
The successful candidate will optimize, integrate and validate reagents, protocols, sequencing chips and instruments to support Ion Torrent product development with the objective of meeting customers requirements for the genetic testing assays. Thermo Fisher Scientific South San Francisco, CABioinformatics and Database Specialist. BS in computer science, bioinformatics, genetics, or a related field. The Bioinformatics R D Group in the Microarray business unit of Thermo Fisher Scientific seeks a talented individual with extensive experience with relational databases and excellent bioinformatics domain knowledge.
The successful candidate will curate data in a large, relational database for genomic research and will drive the acquisition of information from both internal and public sources. Additional duties include the analysis of microarray and genomic data and performing Postgre.
SQL database administration. You will work in an interdisciplinary, dynamic team of scientists and engineers to develop and support a broad array of products for genomic research. Thermo Fisher Scientific Millersburg, PAQuality Assurance Engineer. BS in engineering or science related field. Collect, analyze and present quality data. Establish and optimize test methods and product specifications.
Write and conduct validations IQOQPQ for manufacturing processess and equipment. Ora Andover, MASite Operations Associate. BS in Life Sciences. Assists in organizing research information for clinical projects and ensures with protocol and overall clinical objectives while working under the direction and supervision of the Principal Investigator to assist the Principal Investigator in performing the administrative aspects of a clinical trial. As a member of the clinical team, relies on instructions and pre established guidelines to participate in clinical research activities involving human research subjects while working under immediate supervision of a supervisor or manager to collect basic indications of a subjects health status.
Ora Andover, MASite Operations Associate Per Diem. BS in Life Sciences.
The Site Operations Associate Per Diem is called upon to augment existing staff by assisting in organizing research information for clinical projects, performing administrative aspects of a clinical trial, and ensuring compliance with protocol and overall clinical objectives under the direction and supervision of the Principal Investigator. Demonstrated patient facing skills are required.
Estimation. 1. Software Cost Estimation J. Huang Department of Computer Science University of Houston Houston, TX. On Precision It is the mark of an instructed mind to rest satisfied with the degree of precision which the nature of subject admits, and not to seek exactness when only an approximation of the truth is possible. Huang 2005 Estimation Slide 2 of 44. An Observation Estimation of resources, cost, and schedule for a software development effort requires experience, access to good historical information, and the courage to commit to quantitative measures when qualitative data are all that exist.©J.
Huang 2005 Estimation Slide 3 of 44. Another Observation Estimation for software project carries inherent risk because of uncertainty in project complexity, project size, and structure (of requirements and problem to be solved).©J. Huang 2005 Estimation Slide 4 of 44.
Major FactorsMajor factors that influence software cost:. product size and complexity. programmer ability. available time. required reliability. level of technology©J.
Huang 2005 Estimation Slide 5 of 44. Three Approaches Estimation can be done by using.
experience and historical data. decomposition techniques. empirical models©J. Huang 2005 Estimation Slide 6 of 44. Decomposition Techniques To obtain an estimation, we can decompose the problem to be solved, or decompose the process.©J. Huang 2005 Estimation Slide 7 of 44. DecompositionDecomposition should be done in such a way that1.
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Size can be properly estimated,2. Cost or effort required for each component can be accurately estimated,3. The teams ability to handle the components is well known, and4. The estimated values will be relatively unaffected by changes to the requirements.©J. Huang 2005 Estimation Slide 8 of 44.
Problem-Based Estimation 1. Based on the software scope, decompose the software into problem functions that can be estimated individually. Estimate LOC or FP of each function.
Make optimistic (sopt), most likely (sm), and pessimistic (spess) estimates for each item. Then compute the expected value: EV = (sopt + 4 sm + spess)/6 4.
Apply baseline productivity metrics to compute estimated cost or effort.©J. Huang 2005 Estimation Slide 9 of 44. Process-Based Estimation1. Decompose the process into a set of tasks or activities.2. Estimate the cost or effort required for each.©J. Huang 2005 Estimation Slide 10 of 44.
Empirical Estimation Models. An estimation model provides empirically derived formulas to predict effort as a function of LOC or FP. The data used to support these models are derived from a limited sample.
Thus no model is appropriate for all classes of software.©J. Huang 2005 Estimation Slide 11 of 44. Structure of Estimation Model E = A + BXC where A, B, and C are empirically derived constants, E is the effort in person months, and X is the estimation variable, either in LOC or FP.©J. Huang 2005 Estimation Slide 12 of 44. LOC-based ModelWalston-Felix Model E = 5.2(KLOC)0.91Bailey-Basili Model E = 5.5+0.73(KLOC)1.16Boehm Model (simple) E = 3.2(KLOC)1.05Doty Model for KLOC 9 E = 5.288(KLOC)1.047 ©J.
Huang 2005 Estimation Slide 13 of 44. FP-based model Albrecht and Gaffney Model E = -13.39 + 0.0545(FP) Kemerer Model E = 60.62 + 7.728(FP)310-8 Matson, Barnett & Mellichamp Model E = 585.7 + 15.12(FP)©J.
Huang 2005 Estimation Slide 14 of 44. COCOMOThe COnstructive COst MOdelIt is LOC-based.There are three models: basic, intermediate, and advanced.©J. Huang 2005 Estimation Slide 15 of 44.
Three Classes of Software Project. Organic - a relatively small simple project in which small teams with good application experience work to a set of less than rigid requirements. Semi-detached - an intermediate project in which teams with mixed experience must meet a mix of rigid and less than rigid requirements. Embedded - a project that must meet tight hardware, software, and operational constraints.©J. Huang 2005 Estimation Slide 16 of 44.
The COCOMO (continued)The basic equations E = a(KLOC)b T = cEd where E is the effort required in person-months, T is the required development time in chronological months, KLOC is the estimated size of software in thousand lines of delivered source code. The constants a, b, c, and d are listed below:©J. Huang 2005 Estimation Slide 17 of 44. The COCOMO Model (continued) type of project a b c dorganic 2.4 1.05 2.5 0.38semi-detached 3.0 1.12 2.5 0.35embedded 3.6 1.20 2.5 0.32 ©J. Huang 2005 Estimation Slide 18 of 44. The COCOMO (continued) Effort equation for the intermediate model: E = a(KLOC)b(EAF) where EAF is the effort adjustment factor that ranges from 0.9 to 1.4, and constants a and b are©J. Huang 2005 Estimation Slide 19 of 44.
The COCOMO (continued) type of project a b organic 3.2 1.05 semi-detached 3.0 1.12 embedded 2.8 1.20©J. Huang 2005 Estimation Slide 20 of 44. The Software EquationE = ((LOC)B0.333/P)3(1/t4)where E = effort in person-months t = project duration in months B = special skill factor ranging from 0.16 to 0.39 P = productivity parameter (ref. Huang 2005 Estimation Slide 21 of 44. The Software EquationE = ((LOC)B0.333/P)3(1/t4)where E= effort in person-months t= project duration in months B= special skill factor ranging from 0.16 to 0.39 P = productivity parameter that reflects. overall process maturity and management practices. the extent to which good SE practices are used.
the level of programming language used. the state of software environment. the skill and experience of the software team. the complexity of the application©J. Huang 2005 Estimation Slide 22 of 44. Major FactorsMajor factors that influence software cost:. product size and complexity.
programmer ability. available time. required reliability. level of technology©J. Huang 2005 Estimation Slide 23 of 44.
Product ComplexityThree categories of products: Application programs: those developed in the environment by a language compiler, such as C. Utility programs: those written to provide user processing environments and make sophisticated use of the operating system facilities. System programs: those interact directly with hardware, and often involve concurrent processing with time constraints. Huang 2005 Estimation Slide 24 of 44.
Required Effort Given KDSI, thousand lines of deliverable code, Required programmer-months: application programs: PM = 2.4 x (KDSI)1.05 utility programs: PM = 3.0 x (KDSI)1.12 system programs: PM = 3.6 x (KDSI)1.20©J. Huang 2005 Estimation Slide 25 of 44. Required Development TimeRequired development time: application programs: TDev = 2.5 x (PM)0.38 utility programs: TDev = 2.5 X (PM)0.35 system programs: TDev = 2.5 x (PM)0.32©J. Huang 2005 Estimation Slide 26 of 44. Unit cost vs.
Size (assuming $5,000/PM) 80 sy stem 70 Dollars per line of source code 60 50 40 utility 30 20 application 10 0 1 1 10 2 100 1000 3 10000 4 Sof tware size in 1,000 lines of code©J. Huang 2005 Estimation Slide 27 of 44. Required development time vs. Size 60 application 50 Required dev elopment time in months utility 40 sy stem 30 20 10 0 0 1 1 10 100 2 1000 3 10000 4 Sof tware size in 1,000 lines of source code©J. Huang 2005 Estimation Slide 28 of 44. Productivity vs.
Size Lines of code per prgrammer per day 0,03 30 0,02 20 application (11.8) utility 0,01 10 (5.8) sy stem (2.8) 0,000 0 0 1 1 10 100 2 1000 3 4 10000 Sof tware size in 1,000 lines of source code©J. Huang 2005 Estimation Slide 29 of 44. Major FactorsMajor factors that influence software cost:. product size and complexity. programmer ability. available time. required reliability.
level of technology©J. Huang 2005 Estimation Slide 30 of 44. How programmers spend their time. Writing programs 13% Reading programs and manuals 16% Job communications 32% Personal 13% Miscellaneous 15% Training 6% Mail 5% Based on Bell Lab Study conducted in 1964 on 70 programmers©J.
Huang 2005 Estimation Slide 31 of 44. Programmer’s Ability Variations in programmers abilities worst/best ratioperformance measure program #1 program # 2 debugging hours 28:1 26:1 CPU time 8:1 11:1 coding hours 16:1 25:1 program size 6:1 5:1 run time 5:1 13:1©J. Huang 2005 Estimation Slide 32 of 44. Programmer’s Ability (continued) By eliminating extreme performance in both directions, a variability of 5 to 1 in programmer productivity can be expected.©J.
Huang 2005 Estimation Slide 33 of 44. Available Time Software projects require more total effort if development time is compressed or expanded from the optimal time.©J. Huang 2005 Estimation Slide 34 of 44.
Available Time (continued) According to Putnam, a schedule compression of 0.86 will increase required staff by a factor of 1.82.©J. Free check printing software versacheck. Huang 2005 Estimation Slide 35 of 44. Available Time (continued) It is commonly agreed that there is a limit beyond which a software project cannot reduce its schedule by adding more personnel and equipment. This limit occurs roughly at 75% of the normal schedule.©J. Huang 2005 Estimation Slide 36 of 44.
COCOMO Effort MultipliersProduct attributes Required reliability 0.75 to 1.40 Data-base size 0.94 to 1.16 Product complexity 0.70 to 1.65©J. Huang 2005 Estimation Slide 37 of 44. COCOMO Effort Multipliers (continued)Computer attributes Execution time constraint 1.00 to 1.66 Main storage constraint 1.00 to 1.56 Virtual machine volatility 0.87 to 1.30 Computer turn-around time 0.87 to 1.15©J. Huang 2005 Estimation Slide 38 of 44. COCOMO Effort Multipliers (continued)Personnel attributes Analyst capability 1.46 to 0.71 Programmer capability 1.42 to 0.70 Applications experience 1.29 to 0.82 Virtual machine experience 1.21 to 0.90 Programming language experience 1.14 to 0.95©J. Huang 2005 Estimation Slide 39 of 44. COCOMO Effort Multipliers (continued)Project attributes Use of modern programming practices 1.24 to 0.82 Use of software tools 1.24 to 0.83 Required development schedule 1.23 to 1.00©J.
Huang 2005 Estimation Slide 40 of 44. Staffing Level Estimation A software project typically starts with a small group of capable people to do planning and analysis, a larger, but still small group to do architectural design. The size of required personnel increases in each successive phase, peaks at the implementation and system testing phase, and decreases in the maintenance phase.©J. Huang 2005 Estimation Slide 41 of 44.
Problem Based Estimation In Software Engineering
Staffing-Level Estimation The personnel level of effort required throughout the life cycle of a software product can be approximated by the following equation, which describes a Rayleigh curve:©J. Huang 2005 Estimation Slide 42 of 44. Staffing-Level Estimation (continued) (0.15Tdev+0.7t)2 0.15Tdev+0.7t - FSP = PM( )e 0.5(Tdev)2 0.25(Tdev)2where FSP is the no. Of full-time software personnel required at time t, PM is the estimated programmer-months for product development, excluding planning and analysis, and Tdev is the estimated development time.
Huang 2005 Estimation Slide 43 of 44. Staffing-Level Estimation (continued)FSP Rayleigh curve t ©J.
Huang 2005 Estimation Slide 44 of 44. Skills most lacking in entry level programmers. Express oneself clearly in English. Develop and validate software requirements and specifications. Work within applications area. Perform software maintenance. Perform economic analyses.
Work with project management techniques. Work in group©J. Huang 2005 Estimation Slide 45 of 44.