LEADER 05127nam 22005775 450 001 996465445703316 005 20200702115059.0 010 $a3-030-30701-8 024 7 $a10.1007/978-3-030-30701-1 035 $a(CKB)4900000000505188 035 $a(DE-He213)978-3-030-30701-1 035 $a(MiAaPQ)EBC6005634 035 $a(PPN)242848257 035 $a(EXLCZ)994900000000505188 100 $a20200103d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aParallel Agile ? faster delivery, fewer defects, lower cost$b[electronic resource] /$fby Doug Rosenberg, Barry Boehm, Matt Stephens, Charles Suscheck, Shobha Rani Dhalipathi, Bo Wang 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (XIX, 221 p. 120 illus.) 311 $a3-030-30700-X 327 $a1. Parallel Agile Concepts -- 2. Inside Parallel Agile -- 3. CodeBots: From Domain Model to Executable Architecture -- 4. Parallel Agile by Example: CarmaCam -- 5. Taking the Scream Out of Scrum -- 6. Test Early, Test Often -- 7. Managing Parallelism: Faster Delivery, Fewer Defects, Lower Cost -- 8. Large-Scale Parallel Development -- 9. Parallel Agile for Machine Learning -- Appendix A. The Scream Guide -- Appendix B. Architecture Blueprints. 330 $aFrom the beginning of software time, people have wondered why it isn?t possible to accelerate software projects by simply adding staff. This is sometimes known as the ?nine women can?t make a baby in one month? problem. The most famous treatise declaring this to be impossible is Fred Brooks? 1975 book The Mythical Man-Month, in which he declares that ?adding more programmers to a late software project makes it later,? and indeed this has proven largely true over the decades. Aided by a domain-driven code generator that quickly creates database and API code, Parallel Agile (PA) achieves significant schedule compression using parallelism: as many developers as necessary can independently and concurrently develop the scenarios from initial prototype through production code. Projects can scale by elastic staffing, rather than by stretching schedules for larger development efforts. Schedule compression with a large team of developers working in parallel is analogous to hardware acceleration of compute problems using parallel CPUs. PA has some similarities with and differences from other Agile approaches. Like most Agile methods, PA "gets to code early" and uses feedback from executable software to drive requirements and design. PA uses technical prototyping as a risk-mitigation strategy, to help sanity-check requirements for feasibility, and to evaluate different technical architectures and technologies. Unlike many Agile methods, PA does not support "design by refactoring," and it doesn't drive designs from unit tests. Instead, PA uses a minimalist UML-based design approach (Agile/ICONIX) that starts out with a domain model to facilitate communication across the development team, and partitions the system along use case boundaries, which enables parallel development. Parallel Agile is fully compatible with the Incremental Commitment Spiral Model (ICSM), which involves concurrent effort of a systems engineering team, a development team, and a test team working alongside the developers. The authors have been researching and refining the PA process for several years on multiple test projects that have involved over 200 developers. The book?s example project details the design of one of these test projects, a crowdsourced traffic safety system. 606 $aSoftware engineering 606 $aManagement information systems 606 $aComputer science 606 $aSoftware Engineering/Programming and Operating Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I14002 606 $aManagement of Computing and Information Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I24067 615 0$aSoftware engineering. 615 0$aManagement information systems. 615 0$aComputer science. 615 14$aSoftware Engineering/Programming and Operating Systems. 615 24$aManagement of Computing and Information Systems. 676 $a005.1 700 $aRosenberg$b Doug$4aut$4http://id.loc.gov/vocabulary/relators/aut$0745423 702 $aBoehm$b Barry$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aStephens$b Matt$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aSuscheck$b Charles$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aDhalipathi$b Shobha Rani$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aWang$b Bo$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465445703316 996 $aParallel Agile ? faster delivery, fewer defects, lower cost$92106226 997 $aUNISA LEADER 01425oam 2200433 a 450 001 9910704447003321 005 20130514074705.0 035 $a(CKB)5470000002441225 035 $a(OCoLC)796829170 035 $a(EXLCZ)995470000002441225 100 $a20120626d2012 ua 0 101 0 $aeng 135 $aurmn||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDistrict of Columbia$b[electronic resource] $e2010 : population and housing unit counts 210 1$a[Washington, D.C.] :$cU.S. Dept. of Commerce, Economics and Statistics Administration, U.S. Census Bureau,$d[2012] 215 $a1 online resource (various pagings) $ccolor illustrations, maps 300 $aTitle from title screen (viewed June 26, 2012). 300 $a"2010 census of population and housing"--Cover. 300 $a"Issued June 2012." 300 $a"CPH-2-10." 517 $aDistrict of Columbia 606 $aDemographic surveys$zWashington (D.C.) 607 $aWashington (D.C.)$xPopulation$vStatistics 607 $aUnited States$vCensus, 2010 608 $aStatistics.$2lcgft 615 0$aDemographic surveys 712 02$aU.S. Census Bureau. 801 0$bCBU 801 1$bCBU 801 2$bOCLCO 801 2$bOCLCQ 801 2$bGPO 906 $aBOOK 912 $a9910704447003321 996 $aDistrict of Columbia$93218602 997 $aUNINA