Compositional Specification of Commercial Contracts

Size: px
Start display at page:

Download "Compositional Specification of Commercial Contracts"

Transcription

1 Compositional Spcification of Commrcial Contracts Jspr Andrsn, Ebb Elsborg, Fritz Hnglin, Jakob Gru Simonsn, and Christian Stfansn Dpartmnt of Computr Scinc, Univrsity of Copnhagn (DIKU) Univrsittsparkn 1, DK-2100 Copnhagn Ø Dnmark Abstract. W prsnt a dclarativ languag for compositional spcification of contracts govrning th xchang of rsourcs. It xtnds Ebr and Pyton Jons s dclarativ languag for spcifying financial contracts to th xchang of mony, goods and srvics amongst multipl partis and complmnts McCarthy s Rsourcs/Evnts/Agnts (REA) accounting modl with a viw-indpndnt formal contract modl that supports dfinition of usr-dfind contracts, automatic monitoring undr xcution, and usr-dfinabl analysis of thir stat bfor, during and aftr xcution. W provid svral ralistic xampls of commrcial contracts and thir analysis. A varity of (ral) contracts can b xprssd in such a fashion as to support thir intgration, managmnt and analysis in an oprational nvironmnt that rgistrs vnts. 1 Introduction Whn ntrprnurs ntr contractual rlationships with a larg numbr of othr partis, ach with possibl variations on standard contracts, thy ar confrontd with th intrconnctd problms of spcifying contracts, monitoring thir xcution for prformanc 1, analyzing thir ramifications for planning, pricing and othr purposs prior to and during xcution, and intgrating this information with accounting, workflow managmnt, supply chain managmnt, production planning, tax rporting, dcision support tc. 1.1 Problms with Informal Contract Managmnt Typical problms that can aris in connction with informal modling and rprsntation of contracts and thir xcution includ: (i) disagrmnt on what a contract actually rquirs; (ii) agrmnt on contract, but disagrmnt on what vnts hav actually happnd (vnt history); (iii) agrmnt on contract and vnt history, but disagrmnt on rmaining contractual obligations; (iv) brach or malxcution of contract; (v) ntring bad or undsirabl contracts/missd opportunitis; (vi) bad coordination of contractual obligations with production planning and supply chain managmnt; (vii) impossibility, slownss or costlinss in valuating stat of company affairs. Ancdotal vidnc suggsts that costs associatd with ths problms can b considrabl. Ebr stimats that a major Frnch invstmnt bank has costs of about 50 mio. Euro pr yar attributabl to (i) and (iv) abov, with about half du to lgal costs in connction with contract disputs and th othr half du to malxcution of financial contracts [Eb02]. In summary, capturing contractual obligations prcisly and managing thm conscintiously is important for a company s planning, valuation, and rporting to managmnt, sharholdrs, tax authoritis, rgulatory bodis, potntial buyrs, and othrs. W argu that a dclarativ domain-spcific (spcification) languag (DSL) for compositional spcification of commrcial contracts (dfining contracts by combining subcontracts in various, wll-dfind ways) with an associatd prcis oprational smantics is idally suitd to allviating th abov problms. 1 Prformanc in contract lingo rfrs to complianc with th promiss (contractual commitmnts) stipulatd in a contract; nonprformanc is also trmd brach of contract.

2 1.2 Contributions W (i) xtnd th contract languag of Pyton-Jons, Ebr and Sward for two-party financial contracts in a viw-indpndnt fashion to multi-party commrcial contracts with itration and first-ordr rcursion. Thy involv xplicit agnts and transfrs of arbitrary rsourcs (mony, goods and srvics, or vn pics of information), not only currncis. Our contract languag is stratifid into a pluggabl bas languag for atomic contracts (commitmnts) and a combinator languag for composing commitmnts into structurd contracts. In addition, w (ii) provid a natural contract smantics basd on an inductiv dfinition for whn a trac a finit squnc of vnts constituts a succssful ( prforming ) compltion of a contract. This inducs a dnotational smantics, which compositionally maps contracts to trac sts as in Hoar s Communicating Squntial Procsss (CSP). W (iii) systmatically dvlop thr oprational smantics in a stpwis fashion, starting from th dnotational smantics: A rduction smantics with dfrrd matching of vnts to spcific commitmnts in a contract; an agr matching smantics in which vnts ar matchd nondtrministically against commitmnts; and finally an agr matching smantics whr an vnt is quippd with xplicit control information that routs it dtrministically to a particular commitmnt. Finally, w (iv) validat applicability of our languag by ncoding a varity of xisting contracts in it, and illustrat analyzability of contracts by providing xampls of compositional analysis. Our work builds on a prvious languag dsign by Andrsn and Elsborg [AE03] and is inspird by Pyton Jons and Ebr s compositional spcification of financial contracts, th REA accounting modl and CSP-lik procss algbras. S Sction 7 for a comparison with that work. 2 Modling Commrcial Contracts A contract is an agrmnt btwn two or mor partis which crats obligations to do or not do th spcific things that ar th subjct of that agrmnt. A commrcial contract is a contract whos subjct is th xchang of scarc rsourcs (mony, goods, and srvics). Exampls of commrcial contracts ar sals ordrs, srvic agrmnts, and rntal agrmnts. Adopting trminology from th REA accounting modl [McC82] w shall also call obligations commitmnts and partis agnts. 2.1 Contract Pattrns In its simplst form a contract commits two contract partis to an xchang of rsourcs such as goods for mony or srvics for mony; that is to a pair of transfrs of rsourcs from on party to th othr, whr on transfr is in considration of th othr. Th sals ordr tmplat in Figur 1 commits th two partis (sllr, buyr) to a pair of transfrs, of goods from sllr to buyr and of mony from buyr to sllr. Many commrcial contracts ar of this simpl quid-pro-quo kind, but far from all. Considr th lgal srvics agrmnt tmplat in Figur 2. Hr commitmnts for rndring of a monthly lgal srvic ar rpatd, and ach monthly srvic consists of a standard srvic part and an optional srvic part. Mor gnrally, a contract may allow for altrnativ xcutions, any on of which satisfis th givn contract. W can discrn th following basic contract pattrns for composing commrcial contracts from subcontracts (a subcontract is a contract usd as part of anothr contract): a commitmnt stipulats th transfr of a rsourc or st of rsourcs btwn two partis; it constitus an atomic contract; a contract may rquir squntial xcution of subcontracts; a contract may rquir concurrnt xcution of subcontracts, that is xcution of all subcontracts, whr individual commitmnts may b intrlavd in arbitrary ordr;

3 a contract may rquir xcution of on of a numbr of altrnativ subcontracts; a contract may rquir rpatd xcution of a subcontract. In th rmaindr of this papr w shall xplor a dclarativ contract spcification languag basd on ths contract pattrns. Fig. 1 Agrmnt to Sll Goods Sction 1. (Sal of goods) Sllr shall sll and dlivr to buyr (dscription of goods) no latr than (dat). Sction 2. (Considration) In considration hrof, buyr shall pay (amount in dollars) in cash on dlivry at th plac whr th goods ar rcivd by buyr. Sction 3. (Right of inspction) Buyr shall hav th right to inspct th goods on arrival and, within (days) businss days aftr dlivry, buyr must giv notic (dtaild-claim) to sllr of any claim for damags on goods. Fig. 2 Agrmnt to Provid Lgal Srvics Sction 1. Th attorny shall provid, on a non-xclusiv basis, lgal srvics up to (n) hours pr month, and furthrmor provid srvics in xcss of (n) hours upon agrmnt. Sction 2. In considration hrof, th company shall pay a monthly f of (amount in dollars) bfor th 8th day of th following month and (rat) pr hour for any srvics in xcss of (n) hours 40 days aftr th rcival of an invoic. Sction 3. This contract is valid 1/1-12/31, Compositional Contract Languag In this sction w prsnt a cor contract spcification languag that rflcts th contract composition pattrns of Sction 2.1. This is a cursory prsntation, with no proofs givn. S th tchnical rport [AEH + 04] for a full prsntation. 3.1 Syntax Our contract languag C P is dfind inductivly by th infrnc systm for driving judgmnts of th forms Γ ; c : Contract and D : Γ. Hr Γ and rang ovr maps from idntifirs to contract tmplat typs and to bas typs, rspctivly. Th -oprator on maps is dfind as follows: { (m m m )(x) = (x) if x domain(m ) m(x) othrwis Th languag is built on top of a typd bas languag P dfind by a : τ that dfins xprssions dnoting agnts, rsourcs, tim, othr basic typs and prdicats (Boolan xprssions) ovr thos. P provids th possibility of rfrring to obsrvabls [JES00,JE03]. Th languag is paramtric in P, and w shall introduc suitabl bas languag xprssions on an ad hoc basis in our xampls for illustrativ purposs. Th languag C P is dfind by th infrnc systm in Figur 3. If judgmnt Γ ; c : Contract is drivabl, w say that c is a wll-dfind contract givn typ assumptions Γ and. Succss dnots th trivial or (succssfully) compltd contract: it carris no obligations on

4 Fig. 3 Syntax for contract spcifications Γ ; Succss : Contract Γ ; Failur : Contract Γ (f) = τ Contract Γ ; f(a) : Contract a : τ = {A 1 : Agnt, A 2 : Agnt, R : Rsourc, T : Tim} Γ ; c : Contract P : Boolan Γ ; transmit(a 1, A 2, R, T P ). c : Contract Γ ; c 1 : Contract Γ ; c 2 : Contract Γ ; c 1 + c 2 : Contract Γ ; c 1 : Contract Γ ; c 2 : Contract Γ ; c 1 ; c 2 : Contract Γ ; c 1 : Contract Γ ; c 2 : Contract Γ ; c 1 c 2 : Contract Γ = {f i τ i1... τ ini Contract} m i=1 Γ ; {X i1 : τ i1,..., X ini : τ ini } c i : Contract {f i [X i ] = c i } m i=1 : Γ {f i [X i ] = c i } m i=1 : Γ Γ ; c : Contract ltrc {f i[x i] = c i} m i=1 in c : Contract anybody. Failur dnots th inconsistnt or faild contract; it signifis brach of contract or a contract that is impossibl to fulfill. Th nvironmnt D = {f i [X i ] = c i } m i=1 contains namd contract tmplats. A contract tmplat nds to b instantiatd with actual argumnts from th bas languag. Th contract xprssion transmit(a 1, A 2, R, T P ). c rprsnts a contract whr th commitmnt transmit(a 1, A 2, R, T P ) must b satisfid first. Not that A 1, A 2, R, T ar binding variabl occurrncs whos scop is P and c. Th commitmnt must b matchd by a (transfr) vnt = transmit(a 1, a 2, r, t) of rsourc r from agnt a 1 to agnt a 2 at tim t whr P (a 1, a 2, r, t) holds. Aftr matching, th rsidual contract is c in which A 1, A 2, R, T ar bound to a 1, a 2, r, t, rspctivly. In this fashion, th subsqunt contractual obligations xprssd by c may dpnd on th actual valus in vnt. Th contract combinators +, and ; compos subcontracts according to th contract pattrns w hav discrnd: by altrnation, concurrntly, and squntially, rspctivly. A contract consists of a finit st of namd contract tmplats and a contract body. Not that contract tmplats may b (mutually) rcursiv, which, in particular, lts us captur rptition of subcontracts. In th following w shall adopt th convntion that A 1, A 2, R, T must not b bound in nvironmnt. If a variabl from or any xprssion a only involving variabls bound in occurs as an argumnt of a transmit, w intrprt this as an abbrviation;.g., transmit((a, A 2, R, T P )). c abbrviats transmit((a 1, A 2, R, T P A 1 = a)). c whr A 1 is a nw (agnt-typd) variabl not bound in and diffrnt from A 2, R and T. W abbrviat transmit(a 1, A 2, R, T P ). Succss to transmit(a 1, A 2, R, T P ). Exampls ncoding th contracts from Figurs 1 and 2 ar prsntd in Sction Evnt Tracs and Contract Satisfaction A contract spcifis a st of altrnativ prforming vnt squncs (contract xcutions), ach of which satisfis th obligations xprssd in th contract and concluds it. In this sction w mak ths notions prcis for our languag. A bas structur is a tupl (R, T, A) of sts of rsourcs R, agnts A and a totally ordrd st (T, T ) of dats (or tim points), plus othr sts for othr typs, as ndd. A (transfr) vnt is a trm transmit(a 1, a 2, r, t), whr a 1, a 2 A, r R and t T. An (vnt) trac s is a finit squnc of vnts that is chronologically ordrd; that is, for s = 1... n th tim points in 1... n occur in ascnding ordr. W adopt th following notation: dnots th mpty squnc; a trac consisting of a singl vnt is dnotd by itslf; concatnation of tracs

5 s 1 and s 2 is dnotd by juxtaposition: s 1 s 2 ; w writ (s 1, s 2 ) s if s is an intrlaving of th vnts in tracs s 1 and s 2 ; w writ X for th vctor X 1,..., X k with k 0 and whr k can b dducd from th contxt; w writ P [a 1 /A 1, a 2 /A 2, r/r, t/t ] and c[a 1 /A 1, a 2 /A 2, r/r, t/t ] for substitution of xprssions a 1, a 2, r, t for fr variabls A 1, A 2, R, T in Boolan xprssion P and contract xprssion c, rspctivly. 2 W ar now rady to spcify whn a trac satisfis a contract, i.. givs ris to a prforming xcution of th contract. This is don inductivly by th infrnc systm for judgmnts s δ D c in Figur 4, whr D = {f i[x i ] = c i } m i=1 is a finit st of namd contract tmplats and δ is a finit st of bindings of variabls to lmnts of th givn bas structur. A drivabl judgmnt s δ D c xprsss that vnt squnc s satisfis succssfully xcuts and concluds contract c in an nvironmnt whr contract tmplats ar dfind as in D and δ spcifis to which valus th bas variabls in c and D ar bound. Convrsly, if s δ D c is not drivabl thn s dos not satisfy c. Th prmis δ = P [a 1 /A 1, a 2 /A 2, r/r, t/t ] in th 3d rul stipulats that P [a 1 /A 1, a 2 /A 2, r/r, t/t ], with fr variabls bound as in δ, must b tru for an vnt to match th corrsponding commitmnt. Fig. 4 Contract satisfaction δ D Succss s δ D c[a/x] (f[x] = c) D s δ D f(a) δ = P [a 1 /A 1, a 2 /A 2, r/r, t/t ] s δ D c[a 1 /A 1, a 2 /A 2, r/r, t/t ] transmit(a 1, a 2, r, t) s δ D transmit((a 1, A 2, R, T P )). c s 1 δ D c 1 s 2 δ D c 2 (s 1, s 2) s s δ D c 1 c 2 s 1 δ D c 1 s 2 δ D c 2 s 1 s 2 δ D c 1 ; c 2 s δ D c s δ ltrc D in c s δ D c 1 s δ D c 1 + c 2 s δ D c 2 s δ D c 1 + c Contract Monitoring by Rsiduation Extnsionally, contracts classify tracs (vnt squncs) into prforming and nonprforming ons. W dfin th xtnsion of a contract c to b th st of its prforming xcutions: C[[c]] D;δ = {s : s δ D c}. W say c dnots a trac st S in contxt D, δ, if C[[c]]D;δ = S. 3 W ar not only intrstd in classifying complt vnt squncs onc thy hav happnd, though, but in monitoring contract xcution as it unfolds in tim undr th arrival of vnts. Givn a trac st S dnotd by a contract c and an vnt, th rsiduation function / capturs how c can b satisfid if th first vnt is. It is dfind as follows: S/ = {s s S : s = s} Concptually, w can map contracts to trac sts and us th rsiduation function to monitor contract xcution as follows: 2 W hav not spcifid a particular languag of Boolan xprssions; w only rquir that it has a wll-dfind notion of substitution. 3 A variant of C[[c]] D;δ can b charactrizd compositionally, yilding a dnotational smantics; s [AEH + 04].

6 1. Map a givn contract c 0 to th trac st S 0 that it dnots. If S 0 =, stop and output inconsistnt. 2. For i = 0, 1,... do: Rciv mssag i. (a) If i is a transfr vnt, comput S i+1 = S i / i. If S i+1 =, stop and output brach of contract ; othrwis continu. (b) If i is a trminat contract mssag, chck whthr S i. If so, all obligations hav bn fulfilld and th contract can b trminatd. Stop and output succssfully compltd. If S i, output cannot b trminatd now, lt S i+1 = S i and continu to rciv mssags. To mak th concptual algorithm for contract lif cycl monitoring from Sction 3.3 oprational, w nd to rprsnt th rsidual trac sts and provid mthods for dciding tsts for mptinss and failur. In particular, w would lik to us contracts as rprsntations for trac sts. Not all trac sts ar dnotabl by contracts, howvr. In particular, givn a contract c that dnots a trac st S c it is not a priori clar whthr S c / is dnotabl by a contract c. If it is, w call c th rsidual contract of c aftr. 3.4 Nullabl and Guardd Contracts In this sction w charactriz nullability of a contract and introduc guarding, which is a sufficint condition on contracts for nsuring that rsiduation can b prformd by rduction on contracts. Fig. 5 Nullabl contracts D c nullabl (f[x] = c) D D f(a) nullabl D c nullabl D c + c nullabl D c nullabl D c + c nullabl D Succss nullabl D c nullabl D c nullabl D c c nullabl D c nullabl D c nullabl D c; c nullabl Lt us writ D = c nullabl if C[[c]] D;δ for all δ. W call such a contract nullabl (or trminabl): it can b concludd succssfully, but may possibly also b continud. E.g., th contract Succss + transmit(a 1, a 2, r, t P ) is nullabl, as it may b concludd succssfully (lft choic). Not howvr, that it may also b continud (right choic). It is asy to s that nullability is indpndnt of δ: C[[c]] D;δ for som δ if and only if C[[c]] D;δ for any othr δ. Dciding nullability is rquird to implmnt Stp 2b in contract monitoring. Th following proposition xprsss that nullability is charactrizd by th infrnc systm in Figur 5. Proposition 1. D = c nullabl D c nullabl A contract c is (hrditarily) guardd in contxt D if D c guardd is drivabl from Figur 6; intuitivly, guarddnss nsurs that in a contract with mutual rcursion, w do not hav (mutual) rcursions such as {f[x] = g[x], g[x] = f[x]} that caus th rsiduation algorithm to loop infinitly. 3.5 Oprational Smantics I: Dfrrd Matching Rsiduation on trac sts tlls us how to maintain th trac st undr arrival of vnts. In this sction w prsnt a rduction smantics for contracts, which lifts rsiduation on trac sts to contracts and thus provids a monitoring smantics for contract xcution.

7 Fig. 6 Guardd contracts D Succss guardd D transmit(x P ). c guardd D c guardd D c guardd D c + c guardd D Failur guardd D c guardd (f[x] = c) D D f(a) guardd D c guardd D c guardd D c c guardd D c guardd D c guardd D c; c guardd Fig. 7 Dtrministic rduction (dlayd matching) D, δ D Succss δ = P [a/x] D, δ D transmit(x P ). c transmit(a) D, δ D c[a/x] c D, δ D f(a) Failur c[a/x] (f[x] = c) D c D, δ D Failur Failur δ =P [a/x] D, δ D transmit(x P ). c transmit(a) D, δ D c d D, δ D c d D, δ D c + c d + d Failur D, δ D c d D, δ D c d D c nullabl D, δ D c d D, δ D c d D, δ D c c c d + d c D, δ D c; c d; c + d D c nullabl D, δ D c D, δ D c; c d; c d D, δ D c δ D ltrc D in c c ltrc D in c Th ability of rprsnting rsidual contract obligations of a partially xcutd contract and thus any stat of a contract as a bona fid contract carris th advantag that any analysis that is prformd on original contracts automatically xtnds to partially xcutd contracts as wll. E.g., an invstmnt bank that applis valuations to financial contracts bfor offring thm to customrs can apply thir valuations to thir portfolio of contracts undr xcution;.g., to analyz its risk xposur undr currnt markt conditions. Th rduction smantics is prsntd in Figur 7. Th basic matching rul is δ = P [a/x] D, δ D transmit(x P ). c transmit(a) c[a/x]. It matchs an vnt with a spcific commitmnt in a contract. Thr may b multipl commitmnts in a contract that match th sam vnt. Th smantics capturs th possibilitis of matching an vnt against multipl commitmnts by applying all possibl rductions in altrnativs and concurrnt contract forms and forming th sum of thir possibl outcoms (som of which may actually b Failur). Th rul D, δ D c d D, δ D c d D, δ D c + c d + d thus rducs both altrnativs c and c and thn forms th sum of thir rspctiv rsults d, d.

8 Finally, th rul D c nullabl D, δ D c D, δ D c; c d; c + d d D, δ D c d capturs that can b matchd in c or, if c is nullabl, in c. Not that, if c is not nullabl, can only b matchd in c, not c, as xprssd by th rul D c nullabl D, δ D c d. D, δ D c; c d; c In this fashion th smantics kps track of th rsults of all possibl matchs in a rduction squnc as xplicit altrnativs (summands) and dfrs th dcision as to which spcific commitmnt is matchd by a particular vnt during contract xctution until th vry nd: By slcting a particular summand in a rsidual contract aftr a numbr of rduction stps that rprsnts Succss (and th contract is thus trminabl) a particular st of matching dcisions is chosn x post. As prsntd, th rduction smantics givs ris to an implmntation in which th multipl rducts of prvious rduction stps ar rducd in paralll, sinc thy ar rprsntd as summands in a singl contract, and th rul for rduction of sums rducs both summands. It is rlativly straightforward to turn this into a backtracking smantics by an asymmtric rduction rul for sums, which dlays rduction of th right summand. Guarddnss is ky to nsuring trmination of contract rsiduation and thus that vry (guardd) contract has a rsidual contract undr any vnt in th rduction smantics of Figur 7. Thorm 1. If c C P is guardd thn for ach vnt thr xists a uniqu c C P such that D, δ D c c. Furthrmor, w hav that c is guardd and D, δ = c/ = c, which mans C[[c]] D;δ / = C[[c ]] D;δ. Using this rduction smantics w can turn our concptual contract monitoring algorithm into a ral algorithm. Proposition 1 provids a syntactic charactrization of nullability, which can asily (not trivially) b turnd into an algorithm. Inconsistncy whthr a contract dnots th mpty trac st or not is not tratd hr; s th full rport [AEH + 04]. 3.6 Oprational Smantics II: Eagr Matching Th dfrrd matching smantics of Figur 7 is flxibl and faithful to th natural notion of contract satisfaction as dfind in Figur 4. But from an accounting practic point of viw it is wird bcaus matching dcisions ar dfrrd. In bookkping standard modus oprandi is that vnts ar matchd against spcific commitmnts agrly; that is onlin, as vnts arriv. 4 W shall turn th dfrrd matching smantics of Figur 7 into an agr matching smantics (Figur 8). Th ida is simpl: Rprsnt hr-and-now choics as altrnativ ruls (mta-lvl) as opposd to altrnativ contracts (objct lvl). Spcifically, w split th ruls for rducing altrnativs and concurrnt subcontracts into multipl ruls, and w captur th possibility of rducing in th scond componnt of a squntial contract by adding τ- transitions, which spontanously (without a driving xtrnal vnt) rduc a contract of th form Succss; c to c. For this to b sufficint w hav to mak sur that a nullabl contract indd can b rducd to Succss, not just a contract that is quivalnt with Succss, such as Succss Succss. This is don by nsuring that τ-transitions ar strong nough to guarant rduction to Succss as rquird. 4 Thr ar standard accounting practics for changing such dcisions, but both dfault and standard concptual modl ar that matching dcisions ar mad as arly as possibl. In gnral, it sms rprsnting and dfrring choics and applying hypothtical rasoning to thm appars to b a rathr unusual phnomnon in accounting.

9 Fig. 8 Nondtrministic rduction (agr matching) D, δ N Succss δ = P [a/x] D, δ N transmit(x P ). c transmit(a) Failur c[a/x] D, δ N Failur Failur δ =P [a/x] D, δ N transmit(x P ). c transmit(a) Failur (f[x] = c) D D, δ N f(a) τ c[a/x] D, δ N c + c τ c D, δ N c + c τ c D, δ N c λ d D, δ N c c λ d c λ D, δ N c d D, δ N c c λ c d D, δ N Succss c τ c D, δ N c Succss τ c D, δ N Succss; c τ c D, δ N c λ d D, δ N c; c λ d; c D, δ N c δ N ltrc D in c c ltrc D in c Basd on ths considrations w arriv at th rduction smantics in Figur 8, whr mta-variabl λ rangs ovr vnts and th intrnal vnt τ. Not that it is nondtrministic and not vn conflunt: A contract c can b rducd to two diffrnt contracts by th sam vnt. Considr.g., c = a; b + a; b whr a, b, b ar commitmnts with suitabl D, δ, no two of which match th sam vnt. For vnt matching a w hav D, δ N c b and D, δ N c b, but nithr b nor b can b rducd to Succss or any othr contract by th sam vnt squnc. In rducing c w hav not only rsolvd it against, but also mad a dcision: whthr to apply it to th first altrnativ of c or to th scond. Tchnically, th rduction smantics is not closd undr rsiduation: Givn c and it is not always possibl to find c such that D, δ N c c and D; δ = c/ = c. It is sound, howvr, in th sns that th rduct always dnots a subst of th rsidual trac st: Proposition If D, δ N c c thn D, δ = c c/. 2. If D, δ N c τ c thn D, δ = c c. Evn though individual agr rductions do not prsrv rsiduation, th st of all rductions dos so: Proposition 3. If D, δ D c c thn thr xist contracts c 1,..., c n for som n 1 such that D, δ N c τ c i c i for all i = 1... n and D, δ = c n i=1 c τ i. Th notation indicats any numbr 0 of τ-transitions. As a corollary, Propositions 2 and 3 combind yild that th objct-lvl nondtrminism (xprssd as contract altrnativs) in th dfrrd matching smantics is faithfully rflctd in th mta-lvl nondtrminism (xprssd as multipl applicabl ruls) of th agr matching smantics. 3.7 Oprational Smantics III: Eagr Matching with Explicit Routing Considr th following xcution modl for contracts: Two or mor partis ach hav a copy of th contract thy hav prviously agrd upon and monitor its xcution undr th arrival of vnts. Evn though thy agr on prior contract stat and th nxt vnt, th partis may

10 arriv at diffrnt rsidual contracts and thus diffrnt xpctations as to th futur vnts allowd undr th contract. This is bcaus of nondtrminacy in contract xcution with agr matching;.g., a paymnt of $50 may match multipl paymnt commitmnts, and th partis may mak diffrnt matchs. W can rmdy this by making control of contract rduction with agr matching xplicit in ordr to mak rduction dtrministic: vnts ar accompanid by control information that unambiguously prscribs how a contract is to b rducd. In this fashion partis that agr on what vnts hav happnd and on thir associatd control information, will rduc thir contract idntically. S th full tchnical rport for dtails [AEH + 04]. 4 Exampl Contracts For th purpos of dmonstration w will afford ourslvs a fairly advancd prdicat languag with basic arithmtic, logical connctivs, lists and basic functions. Th syntax is standard and straightforward, and th dtails will b obvious from th xampls. Considr th validity priod spcifid in Sction 3 of th Agrmnt to Provid Lgal Srvics (Figur 2). Takn litrally, it would imply, that th attorny shall rndr srvics in th month of Dcmbr, but rciv no f in considration sinc January 2005 is outsid th validity priod. Surly, this is not th intntion; in fact, considration will dfat most dadlins as is clarly th intnt hr. In th coding of th Agrmnt to Provid Lgal Srvics th xpiration dat nd has to b pushd down on all transmits dspit its global natur to mak sur that considration would not b cut off. Th Agrmnt to Provid Lgal Srvics fails to spcify who dcids if lgal srvics should b rndrd. In th coding it is simply assumd that th attorny is th initiator and that all srvics rndrd ovr a month can b modlld as on vnt. Furthrmor, th attorny is assumd to giv th notic nowork if no work was don for th past month. This is an artifact introducd to guard th rcursiv call to lgal. Fig. 9 Softwar Dvlopmnt Agrmnt Sction 1. Th Dvlopr shall dvlop softwar as dscribd in Exhibit A (Rquirmnts Spcification) according th schdul st forth in Exhibit B (Projct Schdul and Dlivrabls). Spcifically, th Dvlopr shall b rsponsibl for th timly compltion of th dlivrabls idntifid in Exhibit B. Sction 2. Th Clint shall provid writtn approval upon th compltion of ach dlivrabl idntifid in Exhibit B. Sction 3. In th vnt of any dlay by th Clint, all th Dvlopr s rmaining dadlins shall b xtndd by th gratr of th two following: (i) fiv working days, (ii) two tims th dlay inducd by th Clint. Th Clint s dadlins shall b unchangd. Sction 4. In considration of srvics rndrd th Clint shall pay USD $ du on 7/1. Sction 5. If th Clint wishs to add to th ordr, or if upon writtn approval of a dlivrabl, th Clint wishs to mak modifications to th dlivrabl, th Clint and th Dvlopr shall ntr into a Chang Ordr. Upon mutual agrmnt th Chang Ordr shall b attachd to this contract. Sction 6. Th Dvlopr shall rtain all intllctual rights associatd with th softwar dvlopd. Th Clint may not copy or transfr th softwar to any third party without th xplicit, writtn consnt of th Dvlopr. Exhibit A. (omittd) Exhibit B. Dadlins for dlivrabls and approval: (i) 1/1, 1/15; (ii) 3/1, 3/15, (final dadlin) 7/1, 7/15. Now considr th mor laborat Softwar Dvlopmnt Agrmnt in Figur 9. Whn coding th contract, on notics that th contract fails to spcify th ramifications of th clint s

11 Fig. 10 Spcification of Softwar Dvlopmnt Agrmnt not that w assum (asily dfind) abbrviations for max(x,y) and allow subtraction on th domain Tim. ltrc dlivrabls (dv, clint, paymnt, dliv1, dadlin1, approv1, dliv2, dadlin2, approv2, dlivf, dadlinf, approvf) = transmit(dv, clint, dliv1, T1 T1 <= dadlin1)). transmit(clint, dv, "ok", T). transmit(dv, clint, dliv2, T2 T2 <= dadlin2 + max(5d, (T - approv1) * 2)). transmit(clint, dv, "ok", T). transmit(dv, clint, dlivf, Tf Tf <= dadlinf + max(5d, (T - approv2) * 2)). transmit(clint, dv, "ok", T). transmit(dv, clint, "don", T). Succss softwar (dv, clint, paymnt, paymntdadlin, ds) = dlivrabls (dv, clint, dliv1, dadlin1, approv1, dliv2, dadlin2, approv2, dlivf, dadlinf, approvf) transmit(clint, dv, paymnt, T T <= paymntdadlin) in softwar ("M", "Clint", , , d1, , , d2, , , final, , ) non-approval of a dlivrabl. On also ss that th contract dos not spcify what to do if du to dlay, som approval dadlin coms bfor th postpond dlivry dat. In th currnt cod, this is takn to man furthr dlay on th clint s part vn if th clint gav approval at th sam tim as th dlivrabl was transmittd. It sms that contract coding is a halthy procss in th sns that it will oftn unvil undrspcification and rrors in th natural languag contract bing codd. Th Chang Ordr dscribd in Sction 5 of th contract and th intllctual rights dscribd in Sction 6 ar not codd du to crtain limitations in our languag. W will postpon th discussion of this this papr s Sction 6. 5 Contract Analysis Th formal groundwork in ordr, w can bgin to ask ourslvs qustions about contracts such as: What is my first ordr of businss? Whn is th nxt dadlin? How much of a particular rsourc will I gain from my portfolio and at what tims? What is th montary valu of my portfolio? Will contract fulfillmnt rquir mor than th x units I currntly hav in stock? Th attmpt to answr such qustions is broadly rfrrd to as contract analysis. Th rsiduation proprty allows a contract analysis to b applid at any tim (i.. to any rsidual contract), and w can thus continuously monitor th xcution of th contracts in our portfolio. Rcall that our contract spcification languag is paramtrizd ovr th languag of prdicats and arithmtic. Thr is a clar trad-off in play hr: a sophisticatd languag buys xprssivnss, but rndrs most of th analyss undcidabl. Thr is anothr sourc of difficultis. Variabls may b bound to componnts of an vnt that is unknown at th tim of analysis. An xprssion lik transmit(a 1, a 2, R, T tru). offrs littl insight into th natur of R unlss furnishd with a probability vctor ovr all rsourcs.

12 Hr w will circumvnt ths problms by making do with a rstrictd prdicat languag and accpting that analyss may not giv answrs on all input (but will giv corrct answrs). Th prdicat languag is pluggd in at two locations. In function application f(a) whr all componnts of th vctor a must chckd according to th ruls of th prdicat languag, and in transmit(a 1, a 2, r, t P ) whr P must hav th typ Boolan. As prviously w rquir that a 1, a 2, r, and t ar ithr variabls (bound or unbound) or constants. If som componnts ar bound variabls or constants, thy must b qual to th corrsponding componnts of an incoming vnt (a 1, a 2, r, t ) for a match to occur. Considr th syntax providd in figur 11. In addition to th typs Agnt, Rsourc, and Tim, th languag has th fundamntal typs Int and Boolan. Tak τ to rang ovr {Int, Tim}, tak σ to rang ovr τ {Agnt, Rsourc}, and assum that constants can b uniquly typd (.g. tim constants ar in ISO format, and agnt and rsourc constants ar known). Th languag allows arithmtic on intgrs, simpl propositional logic, and manipulation of th two abstract typs Rsourc and Tim. Givn a tim (dat) t w may add an intgral numbr of yars, months or days. For xampl d + 1y yilds Rsourcs prmit a projction on a namd componnt (fild) and all filds ar of typ Int. E.g. to xtract th total amount from an information rsourc namd invoic w writ #(invoic, total, t) whr t is som dat 5. Th filds of rsourcs may chang ovr tim; hnc th third Tim paramtr. Obsrvabls can now b undrstood simply as filds of a ubiquitous rsourc namd obs. An Int may doubl for a Rsourc in which cas th Int is undrstood to b a currncy amount. Fig. 11 Exampl syntax for prdicat languag (var) = σ var : σ typ(const) = σ const : σ 1 : Int 2 : Int op {+,,, /} 1 op 2 : Int t : Tim : Int f {y, m, d} op {+, } t op f : Tim r : Rsourc t : Tim f filds(r) #(r, f, t) : Int : Tim f {y, m, d} #f : Int : Int : Rsourc 1 : τ 2 : τ 1 < 2 : Boolan 1 : σ 2 : σ 1 = 2 : Boolan b 1 : Boolan b 2 : Boolan op {and, or} b 1 op b 2 : Boolan b : Boolan not b : Boolan Idally, a contract analysis can b prformd compositionally, i.. can b implmntd by rcursivly valuating subcontracts. This sction contains a simpl analysis with this proprty. Spac considrations prvnt a walkthrough of mor involvd xampls, but th basic ida should b clar. W will assum for simplicity that rcursivly dfind contracts ar guardd. Th analyss ar prsntd using infrnc systms dfind by induction on syntax, mphasizing th dclarativ and compositional natur of th analyss. 5 Whn a rsourc is introducd into th systm through a match, it must b dynamically chckd that it posssss th rquird filds. Th st of rquird filds can b statically dtrmind by a routin typ chck annotating rsourcs with fild nams à la {dat, total, paymntdadlin}rsourc. To kp things simpl w omit this typ xtnsion hr.

13 5.1 Exampl: Nxt Point of Intrst and Task List Givn a contract or a portfolio of contracts it is trmndously important for an agnt to know whn and how to act. To this nd w dmonstrat how a vry simpl task list can b compild. Considr th dfinition givn in Figur 12. Th function givs a structurd rspons to rflct th dcision structur (th task list) of th contract. It oprats on a vry simpl subst of th prdicat languag that, howvr, is indicativ of th bulk of tmporal constraints in contracts: only intrval conditions of th form a T andt b with T th tim variabl in th nclosing transmit commitmnt ar admittd. Such a condition is abbrviatd to [a; b]. It is important to notic that th rsult of th analysis may b incomplt. A task is only addd if th agnts agr (i.. a = a1), but if a1 is not bound at th tim of analysis, th task is simply skippd. A mor laborat dataflow analysis might rval that in fact a1 is always bound to a. Also notic th cas for application f(a). W xpand th body of th namd contract f givn argumnts a but only onc. This masur nsurs trmination of th analysis, but rducs th function s look-ahad horizon. Hnc, any task or point of intrst mor than on rcursiv unfolding away is not dtctd. This is unlikly to hav practical significanc for two rasons: (1) rcursivly dfind contracts ar guardd and so a transmit must b matchd bfor a nw unfold can occur. This transmit thrfor is prsumably mor rlvant than any othr transmits furthr down th lin; (2) it would b grossly unidiomatic that som transmit t 1 was rquird to b matchd bfor anothr transmit t 2, but nvrthlss had a latr dadlin than that of t 2. Fig. 12 Task list analysis D, δ, a, t Succss : [] D, δ, a, t Failur : [] = a a 1 X = (a 1, A, R, T ) D, δ, a, t transmit(x [x; y]). c : do [] = t / [x; y] D, δ, a, t transmit(x [x; y]). c : do [] = a = a 1 X = (a 1, A, R, T ) t [x; y] D, δ, a, t transmit(x [x; y]) : do [transmit(x [x; y])] D, δ, a, t c 1 : l 1 D, δ, a, t c 2 : l 2 D, δ, a, t c 1 + c 2 : choos[l 1, l 2] D c 1 nullabl D, δ, a, t c 1 : l 1 D, δ, a, t c 2 : l 2 D, δ, a, t c 1; c 2 : choos[l 1, l 2] D c 1 nullabl D, δ, a, t c 1 : l 1 D, δ, a, t c 1 ; c 2 : l 1 D, δ, a, t c 1 : l 1 D, δ, a, t c 2 : l 2 D, δ, a, t c 1 c 2 : l l 2 (f[x] = c) D D, δ, a, t f(a) : l D, δ, a, t c : l Th xampls givn abov, in thir simplicity, may b xtndd givn knowldg of th problm domain. In particular, knowldg of or forcasting about probabl vnt squncs may b usd in a mannr orthogonal to th coding of analyss by appropriat function calls. Analyss that ar possibl to implmnt in this way includ rsourc flow forcasting (supply rquirmnts); trminability by agnt; latst trmination; arlist trmination; and valuation, or simply put: What is th valu to an agnt of a givn contract?

14 6 Discussion and Futur Work Th Softwar Dvlopmnt Agrmnt (Figur 9) provids a good stting to obsrv th limitations to our approach and th ramifications of th dsign choics mad. Th Chang Ordr is not codd. It might b clvrly codd in th currnt languag, again using constraints on th vnts passd around, but a mor natural way would b using highrordr contracts, i.. contracts taking contracts as argumnts. Thus, a Chang Ordr would simply b th passing back and forth of a contract followd by an instantiation upon agrmnt. Contracts oftn spcify crtain things that ar not to b don (.g. not copying th softwar). Such rstrictions should intrsct all othr outstanding contracts and limit thm appropriatly. A highr-ordr languag or prdicats that could guard all transmits of an ntir subcontract might amliorat this in a natural way. A fullr rang of languag constructions that programmrs ar familiar with is also dsirabl; in th prsnt incarnation of th contract languag, svral standard constructions hav bn lft out in ordr to mphasiz th cor vnt modl. In practic, conditionals and various sorts of lambda abstractions would mak th languag asir to us, though not strictly mor xprssiv, as thy can b ncodd through vnts, albit in a non-intuitiv way. A conditional that is not drivn by vnts (i.. an if-thn-ls) sms to b ndd for natural coding in many ral-world contracts. Also, a catch-throw mchanism for unxpctd vnts would mak contracts mor robust. Convrsly, crtain faturs of th languag appar to b almost too strong for th domain; th inclusion of full rcursion mans that contracts activ for an unlimitd priod of tim, say lass, ar asy to cod, but mak contract analysis significantly hardr. In practic, contracts running for unlimitd tim priods oftn hav xtrnal constraints (usually local lgislation) forcing th contract to b rassssd by its partis, and possibly govrnmnt rprsntativs, from tim to tim. Having only a rstrictd form of rcursion that suffics for most practical applications should simplify contract analysis. Th xprssivity of th contract languag and indd th fasibility of non-trivial contract analysis dpnds havily on th prdicat languag usd. Prdicats rstrictd to th form [a; b] ar surly too limitd, and furthr invstigation into th rquird xprssivnss of th prdicat languag is dsirabl. Whil th languag is paramtrizd ovr th prdicat languag usd, almost all ralworld applications will rquir som modl of tim and timd vnts to b incorporatd. Th currnt vnt modl allows for ncoding through th prdicat languag, but an xtndd st of vnts, with companion smantics, would mak for asir contract programming; timr (or triggr ) vnts appar to b ubiquitous whn ncoding contracts. 7 Rlatd Work Th imptus for this work coms from two dirctions: th REA accounting modl pionrd by McCarthy [McC82] and Pyton Jons, Ebr and Sward s sminal articl on spcification of financial contracts [JES00]. Furthrmor, givn that contracts spcify protocols as to how partis bound by thm ar to intract with ach othr thr ar links to procss and workflow modls. Pyton Jons, Ebr and Sward [JES00] prsnt a compositional languag for spcifying financial contracts. It provids a dcomposition of known standard contracts such as zro coupon bonds, options, swaps, straddls, tc., into individual paymnt commitmnts that ar combind dclarativly using a small st of contract combinators. All contracts ar twoparty contracts, and th partis ar implicit. Th combinators (takn from [JE03], rvisd from [JES00]) corrspond to Succss,, +, transmit( ) of our languag C P ; it has no dirct countrparts to Failur, ; nor, most importantly, rcursion or itration. On th othr hand, it

15 provids conditionals and prdicats that ar applicabl to arbitrary contracts, not just commitmnts as in C P, somthing w hav found to b worthwhil also for spcifying commrcial contracts. Our contract languag gnralizs financial paymnt commitmnts to arbitrary transfrs of rsourcs and information, provids xplicit agnts and thus provids th possibility of spcifying multi-party contracts. Disrgarding th structur of vnts and thir tmporal proprtis, C P is basically a procss algbra. It corrsponds to Algbra of Communicating Procsss (ACP) with dadlock (Failur), fr mrg ( ) and rcursion, but without ncapsulation [BW90]. This procss algbra is also part of CSP [BHR84,Hoa85]. Not that contracts ar to b thought as xclusivly ractiv procsss, howvr: thy rspond to xtrnally gnratd vnts, but do not autonomously gnrat thm. Thr ar numrous timd variants of procss algbras and tmporal logics; s.g. Batn and Middlburg [BM02] for timd procss algbras. Thir rlation to our bas languag is not vidnt at this point. This is in part bcaus our bas languag is not fixd yt to accommodat xprssing tmporal (and othr) constraints naturally, in part bcaus th tmporal notions of timd procss languags sm rathr low-lvl and distinct from th notions w hav usd in contract xampls. 8 Acknowldgmnts This work has bn partially fundd by th NEXT Projct, which is a collaboration btwn Microsoft Businss Solutions, Th IT Univrsity of Copnhagn and th Dpartmnt of Computr Scinc at th Univrsity of Copnhagn (DIKU). S for mor information on NEXT. W would lik to thank Simon Pyton Jons, Jan-Marc Ebr, Kaspr Østrby, and Jspr Kihn for valuabl discussions on modling financial contracts and xtnding that work to commrcial contracts basd on th REA accounting modl. Rfrncs [AE03] Jspr Andrsn and Ebb Elsborg. Compositional spcification of commrcial contracts. M.S. trm projct, Dcmbr [AEH + 04] Jspr Andrsn, Ebb Elsborg, Fritz Hnglin, Jakob Gru Simonsn, and Christian Stfansn. Compositional spcification of commrcial contracts. Tchnical rport, DIKU, Univrsity of Copnhagn, Univrsittsparkn 1, DK-2100 Copnhagn, Dnmark, July [BHR84] S. D. Brooks, C. A. R. Hoar, and A. W. Rosco. A thory of communicating squntial procsss. J. ACM, 31(3): , [BM02] J.C.M. Batn and C.A. Middlburg. Procss Algbra with Timing. Springr, [BW90] J.C.M. Batn and W.P. Wijland. Procss Algbra. Numbr 18 in Cambridg Tracts in Thortical Computr Scinc. Cambridg Univrsity Prss, [Eb02] Jan-Marc Ebr. Prsonal communication, Jun [Hoa85] C.A.R. Hoar. Communicating Squntial Procsss. Intrnational Sris in Computr Scinc. Prntic-Hall, [JE03] Simon Pyton Jons and Jan-Marc Ebr. How to writ a financial contract. In Jrmy Gibbons and Og d Moor, ditors, Th Fun of Programming. Palgrav Macmillan, [JES00] Simon Pyton Jons, Jan-Marc Ebr, and Julian Sward. Composing contracts: an advntur in financial nginring (functional parl). In Procdings of th fifth ACM SIGPLAN intrnational confrnc on Functional programming, pags ACM Prss, [McC82] William E. McCarthy. Th REA accounting modl: A gnralizd framwork for accounting systms in a shard data nvironmnt. Th Accounting Rviw, LVII(3): , July 1982.

The example is taken from Sect. 1.2 of Vol. 1 of the CPN book.

The example is taken from Sect. 1.2 of Vol. 1 of the CPN book. Rsourc Allocation Abstract This is a small toy xampl which is wll-suitd as a first introduction to Cnts. Th CN modl is dscribd in grat dtail, xplaining th basic concpts of C-nts. Hnc, it can b rad by popl

More information

Architecture of the proposed standard

Architecture of the proposed standard Architctur of th proposd standard Introduction Th goal of th nw standardisation projct is th dvlopmnt of a standard dscribing building srvics (.g.hvac) product catalogus basd on th xprincs mad with th

More information

Compositional Specification of Commercial Contracts

Compositional Specification of Commercial Contracts Compositional Spcification of Commrcial Contracts Jspr Andrsn, Ebb Elsborg*, Fritz Hnglin, Jakob Gru Simonsn, and Christian Stfansn Dpartmnt of Computr Scinc, Univrsity of Copnhagn (DIKU) Univrsittsparkn

More information

Econ 371: Answer Key for Problem Set 1 (Chapter 12-13)

Econ 371: Answer Key for Problem Set 1 (Chapter 12-13) con 37: Answr Ky for Problm St (Chaptr 2-3) Instructor: Kanda Naknoi Sptmbr 4, 2005. (2 points) Is it possibl for a country to hav a currnt account dficit at th sam tim and has a surplus in its balanc

More information

STATEMENT OF INSOLVENCY PRACTICE 3.2

STATEMENT OF INSOLVENCY PRACTICE 3.2 STATEMENT OF INSOLVENCY PRACTICE 3.2 COMPANY VOLUNTARY ARRANGEMENTS INTRODUCTION 1 A Company Voluntary Arrangmnt (CVA) is a statutory contract twn a company and its crditors undr which an insolvncy practitionr

More information

Adverse Selection and Moral Hazard in a Model With 2 States of the World

Adverse Selection and Moral Hazard in a Model With 2 States of the World Advrs Slction and Moral Hazard in a Modl With 2 Stats of th World A modl of a risky situation with two discrt stats of th world has th advantag that it can b natly rprsntd using indiffrnc curv diagrams,

More information

QUANTITATIVE METHODS CLASSES WEEK SEVEN

QUANTITATIVE METHODS CLASSES WEEK SEVEN QUANTITATIVE METHODS CLASSES WEEK SEVEN Th rgrssion modls studid in prvious classs assum that th rspons variabl is quantitativ. Oftn, howvr, w wish to study social procsss that lad to two diffrnt outcoms.

More information

Remember you can apply online. It s quick and easy. Go to www.gov.uk/advancedlearningloans. Title. Forename(s) Surname. Sex. Male Date of birth D

Remember you can apply online. It s quick and easy. Go to www.gov.uk/advancedlearningloans. Title. Forename(s) Surname. Sex. Male Date of birth D 24+ Advancd Larning Loan Application form Rmmbr you can apply onlin. It s quick and asy. Go to www.gov.uk/advancdlarningloans About this form Complt this form if: you r studying an ligibl cours at an approvd

More information

5 2 index. e e. Prime numbers. Prime factors and factor trees. Powers. worked example 10. base. power

5 2 index. e e. Prime numbers. Prime factors and factor trees. Powers. worked example 10. base. power Prim numbrs W giv spcial nams to numbrs dpnding on how many factors thy hav. A prim numbr has xactly two factors: itslf and 1. A composit numbr has mor than two factors. 1 is a spcial numbr nithr prim

More information

by John Donald, Lecturer, School of Accounting, Economics and Finance, Deakin University, Australia

by John Donald, Lecturer, School of Accounting, Economics and Finance, Deakin University, Australia Studnt Nots Cost Volum Profit Analysis by John Donald, Lcturr, School of Accounting, Economics and Financ, Dakin Univrsity, Australia As mntiond in th last st of Studnt Nots, th ability to catgoris costs

More information

Traffic Flow Analysis (2)

Traffic Flow Analysis (2) Traffic Flow Analysis () Statistical Proprtis. Flow rat distributions. Hadway distributions. Spd distributions by Dr. Gang-Ln Chang, Profssor Dirctor of Traffic safty and Oprations Lab. Univrsity of Maryland,

More information

CPS 220 Theory of Computation REGULAR LANGUAGES. Regular expressions

CPS 220 Theory of Computation REGULAR LANGUAGES. Regular expressions CPS 22 Thory of Computation REGULAR LANGUAGES Rgular xprssions Lik mathmatical xprssion (5+3) * 4. Rgular xprssion ar built using rgular oprations. (By th way, rgular xprssions show up in various languags:

More information

Free ACA SOLUTION (IRS 1094&1095 Reporting)

Free ACA SOLUTION (IRS 1094&1095 Reporting) Fr ACA SOLUTION (IRS 1094&1095 Rporting) Th Insuranc Exchang (301) 279-1062 ACA Srvics Transmit IRS Form 1094 -C for mployrs Print & mail IRS Form 1095-C to mploys HR Assist 360 will gnrat th 1095 s for

More information

Use a high-level conceptual data model (ER Model). Identify objects of interest (entities) and relationships between these objects

Use a high-level conceptual data model (ER Model). Identify objects of interest (entities) and relationships between these objects Chaptr 3: Entity Rlationship Modl Databas Dsign Procss Us a high-lvl concptual data modl (ER Modl). Idntify objcts of intrst (ntitis) and rlationships btwn ths objcts Idntify constraints (conditions) End

More information

WORKERS' COMPENSATION ANALYST, 1774 SENIOR WORKERS' COMPENSATION ANALYST, 1769

WORKERS' COMPENSATION ANALYST, 1774 SENIOR WORKERS' COMPENSATION ANALYST, 1769 08-16-85 WORKERS' COMPENSATION ANALYST, 1774 SENIOR WORKERS' COMPENSATION ANALYST, 1769 Summary of Dutis : Dtrmins City accptanc of workrs' compnsation cass for injurd mploys; authorizs appropriat tratmnt

More information

(Analytic Formula for the European Normal Black Scholes Formula)

(Analytic Formula for the European Normal Black Scholes Formula) (Analytic Formula for th Europan Normal Black Schols Formula) by Kazuhiro Iwasawa Dcmbr 2, 2001 In this short summary papr, a brif summary of Black Schols typ formula for Normal modl will b givn. Usually

More information

A Project Management framework for Software Implementation Planning and Management

A Project Management framework for Software Implementation Planning and Management PPM02 A Projct Managmnt framwork for Softwar Implmntation Planning and Managmnt Kith Lancastr Lancastr Stratgis Kith.Lancastr@LancastrStratgis.com Th goal of introducing nw tchnologis into your company

More information

Basis risk. When speaking about forward or futures contracts, basis risk is the market

Basis risk. When speaking about forward or futures contracts, basis risk is the market Basis risk Whn spaking about forward or futurs contracts, basis risk is th markt risk mismatch btwn a position in th spot asst and th corrsponding futurs contract. Mor broadly spaking, basis risk (also

More information

Category 7: Employee Commuting

Category 7: Employee Commuting 7 Catgory 7: Employ Commuting Catgory dscription This catgory includs missions from th transportation of mploys 4 btwn thir homs and thir worksits. Emissions from mploy commuting may aris from: Automobil

More information

C H A P T E R 1 Writing Reports with SAS

C H A P T E R 1 Writing Reports with SAS C H A P T E R 1 Writing Rports with SAS Prsnting information in a way that s undrstood by th audinc is fundamntally important to anyon s job. Onc you collct your data and undrstand its structur, you nd

More information

Entity-Relationship Model

Entity-Relationship Model Entity-Rlationship Modl Kuang-hua Chn Dpartmnt of Library and Information Scinc National Taiwan Univrsity A Company Databas Kps track of a company s mploys, dpartmnts and projcts Aftr th rquirmnts collction

More information

Lecture 20: Emitter Follower and Differential Amplifiers

Lecture 20: Emitter Follower and Differential Amplifiers Whits, EE 3 Lctur 0 Pag of 8 Lctur 0: Emittr Followr and Diffrntial Amplifirs Th nxt two amplifir circuits w will discuss ar ry important to lctrical nginring in gnral, and to th NorCal 40A spcifically.

More information

Development of Financial Management Reporting in MPLS

Development of Financial Management Reporting in MPLS 1 Dvlopmnt of Financial Managmnt Rporting in MPLS 1. Aim Our currnt financial rports ar structurd to dlivr an ovrall financial pictur of th dpartmnt in it s ntirty, and thr is no attmpt to provid ithr

More information

Important Information Call Through... 8 Internet Telephony... 6 two PBX systems... 10 Internet Calls... 3 Internet Telephony... 2

Important Information Call Through... 8 Internet Telephony... 6 two PBX systems... 10 Internet Calls... 3 Internet Telephony... 2 Installation and Opration Intrnt Tlphony Adaptr Aurswald Box Indx C I R 884264 03 02/05 Call Duration, maximum...10 Call Through...7 Call Transportation...7 Calls Call Through...7 Intrnt Tlphony...3 two

More information

In the previous two chapters, we clarified what it means for a problem to be decidable or undecidable.

In the previous two chapters, we clarified what it means for a problem to be decidable or undecidable. Chaptr 7 Computational Complxity 7.1 Th Class P In th prvious two chaptrs, w clarifid what it mans for a problm to b dcidabl or undcidabl. In principl, if a problm is dcidabl, thn thr is an algorithm (i..,

More information

New Basis Functions. Section 8. Complex Fourier Series

New Basis Functions. Section 8. Complex Fourier Series Nw Basis Functions Sction 8 Complx Fourir Sris Th complx Fourir sris is prsntd first with priod 2, thn with gnral priod. Th connction with th ral-valud Fourir sris is xplaind and formula ar givn for convrting

More information

Performance Evaluation

Performance Evaluation Prformanc Evaluation ( ) Contnts lists availabl at ScincDirct Prformanc Evaluation journal hompag: www.lsvir.com/locat/pva Modling Bay-lik rputation systms: Analysis, charactrization and insuranc mchanism

More information

Incomplete 2-Port Vector Network Analyzer Calibration Methods

Incomplete 2-Port Vector Network Analyzer Calibration Methods Incomplt -Port Vctor Ntwork nalyzr Calibration Mthods. Hnz, N. Tmpon, G. Monastrios, H. ilva 4 RF Mtrology Laboratory Instituto Nacional d Tcnología Industrial (INTI) Bunos irs, rgntina ahnz@inti.gov.ar

More information

Enforcing Fine-grained Authorization Policies for Java Mobile Agents

Enforcing Fine-grained Authorization Policies for Java Mobile Agents Enforcing Fin-graind Authorization Policis for Java Mobil Agnts Giovanni Russllo Changyu Dong Narankr Dulay Dpartmnt of Computing Imprial Collg London South Knsington London, SW7 2AZ, UK {g.russllo, changyu.dong,

More information

Foreign Exchange Markets and Exchange Rates

Foreign Exchange Markets and Exchange Rates Microconomics Topic 1: Explain why xchang rats indicat th pric of intrnational currncis and how xchang rats ar dtrmind by supply and dmand for currncis in intrnational markts. Rfrnc: Grgory Mankiw s Principls

More information

Constraint-Based Analysis of Gene Deletion in a Metabolic Network

Constraint-Based Analysis of Gene Deletion in a Metabolic Network Constraint-Basd Analysis of Gn Dltion in a Mtabolic Ntwork Abdlhalim Larhlimi and Alxandr Bockmayr DFG-Rsarch Cntr Mathon, FB Mathmatik und Informatik, Fri Univrsität Brlin, Arnimall, 3, 14195 Brlin, Grmany

More information

Mathematics. Mathematics 3. hsn.uk.net. Higher HSN23000

Mathematics. Mathematics 3. hsn.uk.net. Higher HSN23000 hsn uknt Highr Mathmatics UNIT Mathmatics HSN000 This documnt was producd spcially for th HSNuknt wbsit, and w rquir that any copis or drivativ works attribut th work to Highr Still Nots For mor dtails

More information

Sci.Int.(Lahore),26(1),131-138,2014 ISSN 1013-5316; CODEN: SINTE 8 131

Sci.Int.(Lahore),26(1),131-138,2014 ISSN 1013-5316; CODEN: SINTE 8 131 Sci.Int.(Lahor),26(1),131-138,214 ISSN 113-5316; CODEN: SINTE 8 131 REQUIREMENT CHANGE MANAGEMENT IN AGILE OFFSHORE DEVELOPMENT (RCMAOD) 1 Suhail Kazi, 2 Muhammad Salman Bashir, 3 Muhammad Munwar Iqbal,

More information

CPU. Rasterization. Per Vertex Operations & Primitive Assembly. Polynomial Evaluator. Frame Buffer. Per Fragment. Display List.

CPU. Rasterization. Per Vertex Operations & Primitive Assembly. Polynomial Evaluator. Frame Buffer. Per Fragment. Display List. Elmntary Rndring Elmntary rastr algorithms for fast rndring Gomtric Primitivs Lin procssing Polygon procssing Managing OpnGL Stat OpnGL uffrs OpnGL Gomtric Primitivs ll gomtric primitivs ar spcifid by

More information

June 2012. Enprise Rent. Enprise 1.1.6. Author: Document Version: Product: Product Version: SAP Version: 8.81.100 8.8

June 2012. Enprise Rent. Enprise 1.1.6. Author: Document Version: Product: Product Version: SAP Version: 8.81.100 8.8 Jun 22 Enpris Rnt Author: Documnt Vrsion: Product: Product Vrsion: SAP Vrsion: Enpris Enpris Rnt 88 88 Enpris Rnt 22 Enpris Solutions All rights rsrvd No parts of this work may b rproducd in any form or

More information

EFFECT OF GEOMETRICAL PARAMETERS ON HEAT TRANSFER PERFORMACE OF RECTANGULAR CIRCUMFERENTIAL FINS

EFFECT OF GEOMETRICAL PARAMETERS ON HEAT TRANSFER PERFORMACE OF RECTANGULAR CIRCUMFERENTIAL FINS 25 Vol. 3 () January-March, pp.37-5/tripathi EFFECT OF GEOMETRICAL PARAMETERS ON HEAT TRANSFER PERFORMACE OF RECTANGULAR CIRCUMFERENTIAL FINS *Shilpa Tripathi Dpartmnt of Chmical Enginring, Indor Institut

More information

REPORT' Meeting Date: April 19,201 2 Audit Committee

REPORT' Meeting Date: April 19,201 2 Audit Committee REPORT' Mting Dat: April 19,201 2 Audit Committ For Information DATE: March 21,2012 REPORT TITLE: FROM: Paul Wallis, CMA, CIA, CISA, Dirctor, Intrnal Audit OBJECTIVE To inform Audit Committ of th rsults

More information

User-Perceived Quality of Service in Hybrid Broadcast and Telecommunication Networks

User-Perceived Quality of Service in Hybrid Broadcast and Telecommunication Networks Usr-Prcivd Quality of Srvic in Hybrid Broadcast and Tlcommunication Ntworks Michal Galtzka Fraunhofr Institut for Intgratd Circuits Branch Lab Dsign Automation, Drsdn, Grmany Michal.Galtzka@as.iis.fhg.d

More information

Question 3: How do you find the relative extrema of a function?

Question 3: How do you find the relative extrema of a function? ustion 3: How do you find th rlativ trma of a function? Th stratgy for tracking th sign of th drivativ is usful for mor than dtrmining whr a function is incrasing or dcrasing. It is also usful for locating

More information

Lecture 3: Diffusion: Fick s first law

Lecture 3: Diffusion: Fick s first law Lctur 3: Diffusion: Fick s first law Today s topics What is diffusion? What drivs diffusion to occur? Undrstand why diffusion can surprisingly occur against th concntration gradint? Larn how to dduc th

More information

Rural and Remote Broadband Access: Issues and Solutions in Australia

Rural and Remote Broadband Access: Issues and Solutions in Australia Rural and Rmot Broadband Accss: Issus and Solutions in Australia Dr Tony Warrn Group Managr Rgulatory Stratgy Tlstra Corp Pag 1 Tlstra in confidnc Ovrviw Australia s gographical siz and population dnsity

More information

Parallel and Distributed Programming. Performance Metrics

Parallel and Distributed Programming. Performance Metrics Paralll and Distributd Programming Prformanc! wo main goals to b achivd with th dsign of aralll alications ar:! Prformanc: th caacity to rduc th tim to solv th roblm whn th comuting rsourcs incras;! Scalability:

More information

Combinatorial Analysis of Network Security

Combinatorial Analysis of Network Security Combinatorial Analysis of Ntwork Scurity Stvn Nol a, Brian O Brry a, Charls Hutchinson a, Sushil Jajodia a, Lynn Kuthan b, and Andy Nguyn b a Gorg Mason Univrsity Cntr for Scur Information Systms b Dfns

More information

Continuity Cloud Virtual Firewall Guide

Continuity Cloud Virtual Firewall Guide Cloud Virtual Firwall Guid uh6 Vrsion 1.0 Octobr 2015 Foldr BDR Guid for Vam Pag 1 of 36 Cloud Virtual Firwall Guid CONTENTS INTRODUCTION... 3 ACCESSING THE VIRTUAL FIREWALL... 4 HYPER-V/VIRTUALBOX CONTINUITY

More information

Upper Bounding the Price of Anarchy in Atomic Splittable Selfish Routing

Upper Bounding the Price of Anarchy in Atomic Splittable Selfish Routing Uppr Bounding th Pric of Anarchy in Atomic Splittabl Slfish Routing Kamyar Khodamoradi 1, Mhrdad Mahdavi, and Mohammad Ghodsi 3 1 Sharif Univrsity of Tchnology, Thran, Iran, khodamoradi@c.sharif.du Sharif

More information

Business Systems Analysis with Ontologies

Business Systems Analysis with Ontologies Businss Systms Analysis with Ontologis Ptr Grn Univrsity of Qunsland, Australia Michal Rosmann Qunsland Univrsity of Tchnology, Australia IDEA GROUP PUBLISHING Hrshy London Mlbourn Singapor Acquisitions

More information

Expert-Mediated Search

Expert-Mediated Search Exprt-Mdiatd Sarch Mnal Chhabra Rnsslar Polytchnic Inst. Dpt. of Computr Scinc Troy, NY, USA chhabm@cs.rpi.du Sanmay Das Rnsslar Polytchnic Inst. Dpt. of Computr Scinc Troy, NY, USA sanmay@cs.rpi.du David

More information

CARE QUALITY COMMISSION ESSENTIAL STANDARDS OF QUALITY AND SAFETY. Outcome 10 Regulation 11 Safety and Suitability of Premises

CARE QUALITY COMMISSION ESSENTIAL STANDARDS OF QUALITY AND SAFETY. Outcome 10 Regulation 11 Safety and Suitability of Premises CARE QUALITY COMMISSION ESSENTIAL STANDARDS OF QUALITY AND SAFETY Outcom 10 Rgulation 11 Safty and Suitability of Prmiss CQC Rf 10A 10A(1) Lad Dirctor / Lad Officr Rspons Impact Liklihood Lvl of Concrn

More information

ITIL & Service Predictability/Modeling. 2006 Plexent

ITIL & Service Predictability/Modeling. 2006 Plexent ITIL & Srvic Prdictability/Modling 1 2 Plxnt Th Company 2001 Foundd Plxnt basd on an Expandd ITIL Architctur, CMMI, ISO, and BS15000 - itdna 2003 Launchd itdna Srvic Offring 2003 John Groom, past Dirctor

More information

Analyzing Failures of a Semi-Structured Supercomputer Log File Efficiently by Using PIG on Hadoop

Analyzing Failures of a Semi-Structured Supercomputer Log File Efficiently by Using PIG on Hadoop Intrnational Journal of Computr Scinc and Enginring Opn Accss Rsarch Papr Volum-2, Issu-1 E-ISSN: 2347-2693 Analyzing Failurs of a Smi-Structurd Suprcomputr Log Fil Efficintly by Using PIG on Hadoop Madhuri

More information

Key Management System Framework for Cloud Storage Singa Suparman, Eng Pin Kwang Temasek Polytechnic {singas,engpk}@tp.edu.sg

Key Management System Framework for Cloud Storage Singa Suparman, Eng Pin Kwang Temasek Polytechnic {singas,engpk}@tp.edu.sg Ky Managmnt Systm Framwork for Cloud Storag Singa Suparman, Eng Pin Kwang Tmask Polytchnic {singas,ngpk}@tp.du.sg Abstract In cloud storag, data ar oftn movd from on cloud storag srvic to anothr. Mor frquntly

More information

A Multi-Heuristic GA for Schedule Repair in Precast Plant Production

A Multi-Heuristic GA for Schedule Repair in Precast Plant Production From: ICAPS-03 Procdings. Copyright 2003, AAAI (www.aaai.org). All rights rsrvd. A Multi-Huristic GA for Schdul Rpair in Prcast Plant Production Wng-Tat Chan* and Tan Hng W** *Associat Profssor, Dpartmnt

More information

AP Calculus AB 2008 Scoring Guidelines

AP Calculus AB 2008 Scoring Guidelines AP Calculus AB 8 Scoring Guidlins Th Collg Board: Conncting Studnts to Collg Succss Th Collg Board is a not-for-profit mmbrship association whos mission is to connct studnts to collg succss and opportunity.

More information

SPECIAL VOWEL SOUNDS

SPECIAL VOWEL SOUNDS SPECIAL VOWEL SOUNDS Plas consult th appropriat supplmnt for th corrsponding computr softwar lsson. Rfr to th 42 Sounds Postr for ach of th Spcial Vowl Sounds. TEACHER INFORMATION: Spcial Vowl Sounds (SVS)

More information

SOFTWARE ENGINEERING AND APPLIED CRYPTOGRAPHY IN CLOUD COMPUTING AND BIG DATA

SOFTWARE ENGINEERING AND APPLIED CRYPTOGRAPHY IN CLOUD COMPUTING AND BIG DATA Intrnational Journal on Tchnical and Physical Problms of Enginring (IJTPE) Publishd by Intrnational Organization of IOTPE ISSN 077-358 IJTPE Journal www.iotp.com ijtp@iotp.com Sptmbr 015 Issu 4 Volum 7

More information

A Theoretical Model of Public Response to the Homeland Security Advisory System

A Theoretical Model of Public Response to the Homeland Security Advisory System A Thortical Modl of Public Rspons to th Homland Scurity Advisory Systm Amy (Wnxuan) Ding Dpartmnt of Information and Dcision Scincs Univrsity of Illinois Chicago, IL 60607 wxding@uicdu Using a diffrntial

More information

Asset set Liability Management for

Asset set Liability Management for KSD -larning and rfrnc products for th global financ profssional Highlights Library of 29 Courss Availabl Products Upcoming Products Rply Form Asst st Liability Managmnt for Insuranc Companis A comprhnsiv

More information

ME 612 Metal Forming and Theory of Plasticity. 6. Strain

ME 612 Metal Forming and Theory of Plasticity. 6. Strain Mtal Forming and Thory of Plasticity -mail: azsnalp@gyt.du.tr Makin Mühndisliği Bölümü Gbz Yüksk Tknoloji Enstitüsü 6.1. Uniaxial Strain Figur 6.1 Dfinition of th uniaxial strain (a) Tnsil and (b) Comprssiv.

More information

GOAL SETTING AND PERSONAL MISSION STATEMENT

GOAL SETTING AND PERSONAL MISSION STATEMENT Prsonal Dvlopmnt Track Sction 4 GOAL SETTING AND PERSONAL MISSION STATEMENT Ky Points 1 Dfining a Vision 2 Writing a Prsonal Mission Statmnt 3 Writing SMART Goals to Support a Vision and Mission If you

More information

Analyzing the Economic Efficiency of ebaylike Online Reputation Reporting Mechanisms

Analyzing the Economic Efficiency of ebaylike Online Reputation Reporting Mechanisms A rsarch and ducation initiativ at th MIT Sloan School of Managmnt Analyzing th Economic Efficincy of Baylik Onlin Rputation Rporting Mchanisms Papr Chrysanthos Dllarocas July For mor information, plas

More information

A copy of the Consultation Paper is in the Members Library and further details are available at www.scotland~qov.umpublications/2012/12/5980

A copy of the Consultation Paper is in the Members Library and further details are available at www.scotland~qov.umpublications/2012/12/5980 To: CORPORATE SERVICES COMMITTEE NORTH LANARKSHIRE COUNCIL REPORT Subjct: CONSULTATION: CIVIL LAW OF DAMAGES - ISSUES IN PERSONAL INJURY From: HEAD OF LEGAL SERVICES Dat: 30 JANUARY 2013 Rf: AL LE CSN

More information

Lecture notes: 160B revised 9/28/06 Lecture 1: Exchange Rates and the Foreign Exchange Market FT chapter 13

Lecture notes: 160B revised 9/28/06 Lecture 1: Exchange Rates and the Foreign Exchange Market FT chapter 13 Lctur nots: 160B rvisd 9/28/06 Lctur 1: xchang Rats and th Forign xchang Markt FT chaptr 13 Topics: xchang Rats Forign xchang markt Asst approach to xchang rats Intrst Rat Parity Conditions 1) Dfinitions

More information

Data warehouse on Manpower Employment for Decision Support System

Data warehouse on Manpower Employment for Decision Support System Data warhous on Manpowr Employmnt for Dcision Support Systm Amro F. ALASTA, and Muftah A. Enaba Abstract Sinc th us of computrs in businss world, data collction has bcom on of th most important issus du

More information

OPTIONS AND FUTURES: A TECHNICAL APPRAISAL

OPTIONS AND FUTURES: A TECHNICAL APPRAISAL Pag 15 OPTIONS AND FUTURES: A TECHNICAL APPRAISAL by David J.S. Rutldg Papr prsntd to Sminar on Trading in Options: Opportunitis in th Intrnational Markt sponsord by Th Sydny Stock Exchang and Th Scuritis

More information

Electronic Commerce. and. Competitive First-Degree Price Discrimination

Electronic Commerce. and. Competitive First-Degree Price Discrimination Elctronic Commrc and Comptitiv First-Dgr Pric Discrimination David Ulph* and Nir Vulkan ** Fbruary 000 * ESRC Cntr for Economic arning and Social Evolution (ESE), Dpartmnt of Economics, Univrsity Collg

More information

Meerkats: A Power-Aware, Self-Managing Wireless Camera Network for Wide Area Monitoring

Meerkats: A Power-Aware, Self-Managing Wireless Camera Network for Wide Area Monitoring Mrkats: A Powr-Awar, Slf-Managing Wirlss Camra Ntwork for Wid Ara Monitoring C. B. Margi 1, X. Lu 1, G. Zhang 1, G. Stank 2, R. Manduchi 1, K. Obraczka 1 1 Dpartmnt of Computr Enginring, Univrsity of California,

More information

IHE IT Infrastructure (ITI) Technical Framework Supplement. Cross-Enterprise Document Workflow (XDW) Trial Implementation

IHE IT Infrastructure (ITI) Technical Framework Supplement. Cross-Enterprise Document Workflow (XDW) Trial Implementation Intgrating th Halthcar Entrpris 5 IHE IT Infrastructur (ITI) Tchnical Framwork Supplmnt 10 Cross-Entrpris Documnt Workflow (XDW) 15 Trial Implmntation 20 Dat: Octobr 13, 2014 Author: IHE ITI Tchnical Committ

More information

Intermediate Macroeconomic Theory / Macroeconomic Analysis (ECON 3560/5040) Final Exam (Answers)

Intermediate Macroeconomic Theory / Macroeconomic Analysis (ECON 3560/5040) Final Exam (Answers) Intrmdiat Macroconomic Thory / Macroconomic Analysis (ECON 3560/5040) Final Exam (Answrs) Part A (5 points) Stat whthr you think ach of th following qustions is tru (T), fals (F), or uncrtain (U) and brifly

More information

Who uses our services? We have a growing customer base. with institutions all around the globe.

Who uses our services? We have a growing customer base. with institutions all around the globe. not taking xpr Srvic Guid 2013 / 2014 NTE i an affordabl option for audio to txt convrion. Our rvic includ not or dirct trancription rvic from prviouly rcordd audio fil. Our rvic appal pcially to tudnt

More information

FACULTY SALARIES FALL 2004. NKU CUPA Data Compared To Published National Data

FACULTY SALARIES FALL 2004. NKU CUPA Data Compared To Published National Data FACULTY SALARIES FALL 2004 NKU CUPA Data Compard To Publishd National Data May 2005 Fall 2004 NKU Faculty Salaris Compard To Fall 2004 Publishd CUPA Data In th fall 2004 Northrn Kntucky Univrsity was among

More information

Category 1: Purchased Goods and Services

Category 1: Purchased Goods and Services 1 Catgory 1: Purchasd Goods and Srvics Catgory dscription T his catgory includs all upstram (i.., cradl-to-gat) missions from th production of products purchasd or acquird by th rporting company in th

More information

Fleet vehicles opportunities for carbon management

Fleet vehicles opportunities for carbon management Flt vhicls opportunitis for carbon managmnt Authors: Kith Robrtson 1 Dr. Kristian Stl 2 Dr. Christoph Hamlmann 3 Alksandra Krukar 4 Tdla Mzmir 5 1 Snior Sustainability Consultant & Lad Analyst, Arup 2

More information

Section 7.4: Exponential Growth and Decay

Section 7.4: Exponential Growth and Decay 1 Sction 7.4: Exponntial Growth and Dcay Practic HW from Stwart Txtbook (not to hand in) p. 532 # 1-17 odd In th nxt two ction, w xamin how population growth can b modld uing diffrntial quation. W tart

More information

Keywords Cloud Computing, Service level agreement, cloud provider, business level policies, performance objectives.

Keywords Cloud Computing, Service level agreement, cloud provider, business level policies, performance objectives. Volum 3, Issu 6, Jun 2013 ISSN: 2277 128X Intrnational Journal of Advancd Rsarch in Computr Scinc and Softwar Enginring Rsarch Papr Availabl onlin at: wwwijarcsscom Dynamic Ranking and Slction of Cloud

More information

SPREAD OPTION VALUATION AND THE FAST FOURIER TRANSFORM

SPREAD OPTION VALUATION AND THE FAST FOURIER TRANSFORM RESEARCH PAPERS IN MANAGEMENT STUDIES SPREAD OPTION VALUATION AND THE FAST FOURIER TRANSFORM M.A.H. Dmpstr & S.S.G. Hong WP 26/2000 Th Judg Institut of Managmnt Trumpington Strt Cambridg CB2 1AG Ths paprs

More information

Planning and Managing Copper Cable Maintenance through Cost- Benefit Modeling

Planning and Managing Copper Cable Maintenance through Cost- Benefit Modeling Planning and Managing Coppr Cabl Maintnanc through Cost- Bnfit Modling Jason W. Rup U S WEST Advancd Tchnologis Bouldr Ky Words: Maintnanc, Managmnt Stratgy, Rhabilitation, Cost-bnfit Analysis, Rliability

More information

SCHOOLS' PPP : PROJECT MANAGEMENT

SCHOOLS' PPP : PROJECT MANAGEMENT Rport Schools' PPP Sub Committ 22 April 2004 2 SCHOOLS' PPP : PROJECT MANAGEMENT 1 Rason for Rport To provid Mmbrs with information on th structur of th Schools' PPP Projct Tam 2 Background 21 Dumfris

More information

TIME MANAGEMENT. 1 The Process for Effective Time Management 2 Barriers to Time Management 3 SMART Goals 4 The POWER Model e. Section 1.

TIME MANAGEMENT. 1 The Process for Effective Time Management 2 Barriers to Time Management 3 SMART Goals 4 The POWER Model e. Section 1. Prsonal Dvlopmnt Track Sction 1 TIME MANAGEMENT Ky Points 1 Th Procss for Effctiv Tim Managmnt 2 Barrirs to Tim Managmnt 3 SMART Goals 4 Th POWER Modl In th Army, w spak of rsourcs in trms of th thr M

More information

Stag and Capital Bids in Indian Scenario

Stag and Capital Bids in Indian Scenario SNH/01/4/Info2 CAPITAL INVESTMENT STRATEGY 2001-02 Summary 1. `This information papr provids an ovrviw of th critria and prioritis usd by Managmnt Tam in dtrmining SNH s annual capital programm, as rqustd

More information

Real-Time Evaluation of Email Campaign Performance

Real-Time Evaluation of Email Campaign Performance Singapor Managmnt Univrsity Institutional Knowldg at Singapor Managmnt Univrsity Rsarch Collction L Kong Chian School Of Businss L Kong Chian School of Businss 10-2008 Ral-Tim Evaluation of Email Campaign

More information

Production Costing (Chapter 8 of W&W)

Production Costing (Chapter 8 of W&W) Production Costing (Chaptr 8 of W&W).0 Introduction Production costs rfr to th oprational costs associatd with producing lctric nrgy. Th most significant componnt of production costs ar th ful costs ncssary

More information

Product Overview. Version 1-12/14

Product Overview. Version 1-12/14 Product Ovrviw Vrsion 1-12/14 W ar Grosvnor Tchnology Accss Control Solutions W dvlop, manufactur and provid accss control and workforc managmnt solutions th world ovr. Our product offring ompasss hardwar,

More information

Job Description. Programme Leader & Subject Matter Expert

Job Description. Programme Leader & Subject Matter Expert Job titl: Programm Ladr & Subjct Mattr xprt Arbitration Pathways, ducation and Training Dpartmnt Salary band: 47,500 to 56,500 (dpndnt upon xprinc) Hours: 35 hours a wk Trm: Full Tim, Prmannt Accountabl

More information

Maintain Your F5 Solution with Fast, Reliable Support

Maintain Your F5 Solution with Fast, Reliable Support F5 SERVICES TECHNICAL SUPPORT SERVICES DATASHEET Maintain Your F5 Solution with Fast, Rliabl Support In a world whr chang is th only constant, you rly on your F5 tchnology to dlivr no mattr what turns

More information

Cloud and Big Data Summer School, Stockholm, Aug., 2015 Jeffrey D. Ullman

Cloud and Big Data Summer School, Stockholm, Aug., 2015 Jeffrey D. Ullman Cloud and Big Data Summr Scool, Stockolm, Aug., 2015 Jffry D. Ullman Givn a st of points, wit a notion of distanc btwn points, group t points into som numbr of clustrs, so tat mmbrs of a clustr ar clos

More information

union scholars program APPLICATION DEADLINE: FEBRUARY 28 YOU CAN CHANGE THE WORLD... AND EARN MONEY FOR COLLEGE AT THE SAME TIME!

union scholars program APPLICATION DEADLINE: FEBRUARY 28 YOU CAN CHANGE THE WORLD... AND EARN MONEY FOR COLLEGE AT THE SAME TIME! union scholars YOU CAN CHANGE THE WORLD... program AND EARN MONEY FOR COLLEGE AT THE SAME TIME! AFSCME Unitd Ngro Collg Fund Harvard Univrsity Labor and Worklif Program APPLICATION DEADLINE: FEBRUARY 28

More information

An Broad outline of Redundant Array of Inexpensive Disks Shaifali Shrivastava 1 Department of Computer Science and Engineering AITR, Indore

An Broad outline of Redundant Array of Inexpensive Disks Shaifali Shrivastava 1 Department of Computer Science and Engineering AITR, Indore Intrnational Journal of mrging Tchnology and dvancd nginring Wbsit: www.ijta.com (ISSN 2250-2459, Volum 2, Issu 4, pril 2012) n road outlin of Rdundant rray of Inxpnsiv isks Shaifali Shrivastava 1 partmnt

More information

Version 1.0. General Certificate of Education (A-level) January 2012. Mathematics MPC3. (Specification 6360) Pure Core 3. Final.

Version 1.0. General Certificate of Education (A-level) January 2012. Mathematics MPC3. (Specification 6360) Pure Core 3. Final. Vrsion.0 Gnral Crtificat of Education (A-lvl) January 0 Mathmatics MPC (Spcification 660) Pur Cor Final Mark Schm Mark schms ar prpard by th Principal Eaminr and considrd, togthr with th rlvant qustions,

More information

Cost Benefit Analysis of the etir system Summary, limitations and recommendations

Cost Benefit Analysis of the etir system Summary, limitations and recommendations UNITED NATIONS Cost Bnfit Analysis of th TIR systm Summary, limitations and rcommndations Agnda itm 5 André Scia Informal Ad hoc Exprt Group on Concptual and Tchnical Aspcts of Computrization of th TIR

More information

Factorials! Stirling s formula

Factorials! Stirling s formula Author s not: This articl may us idas you havn t larnd yt, and might sm ovrly complicatd. It is not. Undrstanding Stirling s formula is not for th faint of hart, and rquirs concntrating on a sustaind mathmatical

More information

Teaching Computer Networking with the Help of Personal Computer Networks

Teaching Computer Networking with the Help of Personal Computer Networks Taching Computr Ntworking with th Hlp of Prsonal Computr Ntworks Rocky K. C. Chang Dpartmnt of Computing Th Hong Kong Polytchnic Univrsity Hung Hom, Kowloon, Hong Kong csrchang@comp.polyu.du.hk ABSTRACT

More information

High Interest Rates In Ghana,

High Interest Rates In Ghana, NO. 27 IEA MONOGRAPH High Intrst Rats In Ghana, A Critical Analysis IEA Ghana THE INSTITUTE OF ECONOMIC AFFAIRS A Public Policy Institut High Intrst Rats In Ghana, A Critical Analysis 1 by DR. J. K. KWAKYE

More information

Keynote Speech Collaborative Web Services and Peer-to-Peer Grids

Keynote Speech Collaborative Web Services and Peer-to-Peer Grids Kynot Spch Collaborativ s and Pr-to-Pr Grids Goffry ox 1,2,4, Hasan Bulut 2, Kangsok Kim 2, Sung-Hoon Ko 1, Sangmi L 5, Sangyoon h 2, Shridp Pallickara 1, Xiaohong Qiu 1,3, Ahmt yar 1,3, Minjun Wang 1,3,

More information

Gold versus stock investment: An econometric analysis

Gold versus stock investment: An econometric analysis Intrnational Journal of Dvlopmnt and Sustainability Onlin ISSN: 268-8662 www.isdsnt.com/ijds Volum Numbr, Jun 202, Pag -7 ISDS Articl ID: IJDS20300 Gold vrsus stock invstmnt: An conomtric analysis Martin

More information

A Note on Approximating. the Normal Distribution Function

A Note on Approximating. the Normal Distribution Function Applid Mathmatical Scincs, Vol, 00, no 9, 45-49 A Not on Approimating th Normal Distribution Function K M Aludaat and M T Alodat Dpartmnt of Statistics Yarmouk Univrsity, Jordan Aludaatkm@hotmailcom and

More information

Theoretical aspects of investment demand for gold

Theoretical aspects of investment demand for gold Victor Sazonov (Russia), Dmitry Nikolav (Russia) Thortical aspcts of invstmnt dmand for gold Abstract Th main objctiv of this articl is construction of a thortical modl of invstmnt in gold. Our modl is

More information

Sharp bounds for Sándor mean in terms of arithmetic, geometric and harmonic means

Sharp bounds for Sándor mean in terms of arithmetic, geometric and harmonic means Qian t al. Journal of Inqualitis and Applications (015) 015:1 DOI 10.1186/s1660-015-0741-1 R E S E A R C H Opn Accss Sharp bounds for Sándor man in trms of arithmtic, gomtric and harmonic mans Wi-Mao Qian

More information

Combinatorial Prediction Markets for Event Hierarchies

Combinatorial Prediction Markets for Event Hierarchies Combinatorial rdiction Markts for Evnt Hirarchis Mingyu Guo Duk Univrsity Dpartmnt of Computr Scinc Durham, NC, USA mingyu@cs.duk.du David M. nnock Yahoo! Rsarch 111 W. 40th St. 17th Floor Nw York, NY

More information

Defining Retirement Success for Defined Contribution Plan Sponsors: Begin with the End in Mind

Defining Retirement Success for Defined Contribution Plan Sponsors: Begin with the End in Mind Dfining Rtirmnt Succss for Dfind Contribution Plan Sponsors: Bgin with th End in Mind David Blanchtt, CFA, CFP, AIFA Had of Rtirmnt Rsarch Morningstar Invstmnt Managmnt david.blanchtt@morningstar.com Nathan

More information

CalOHI Content Management System Review

CalOHI Content Management System Review CalOHI Contnt Systm Rviw Tabl of Contnts Documnt Ovrviw... 3 DotNtNuk... 4 Ovrviw... 4 Installation / Maintnanc... 4 Documntation... 5 Usability... 5 Dvlopmnt... 5 Ovrall... 6 CMS Mad Simpl... 6 Ovrviw...

More information