diff --git a/.github/workflows/github_ci.yml b/.github/workflows/github_ci.yml
index 5610f33..48a7163 100644
--- a/.github/workflows/github_ci.yml
+++ b/.github/workflows/github_ci.yml
@@ -10,6 +10,8 @@ jobs:
       matrix:
         version:
           - '1.6'
+          - '1.7'
+          - 'nightly'
         os:
           - ubuntu-latest
           - macOS-latest
diff --git a/src/LifeContingencies.jl b/src/LifeContingencies.jl
index c1d704f..44ff180 100644
--- a/src/LifeContingencies.jl
+++ b/src/LifeContingencies.jl
@@ -5,7 +5,7 @@ using MortalityTables
 using Transducers
 using Dates
 using Yields
-    
+
 const mt = MortalityTables
 
 export LifeContingency,
@@ -39,7 +39,7 @@ abstract type Life end
 
 """
     struct SingleLife
-        mort
+        mortality
         issue_age::Int
         alive::Bool
         fractional_assump::MortalityTables.DeathDistribution
@@ -48,44 +48,44 @@ abstract type Life end
 A `Life` object containing the necessary assumptions for contingent maths related to a single life. Use with a `LifeContingency` to do many actuarial present value calculations. 
 
 Keyword arguments:
-- `mort` pass a mortality vector, which is an array of applicable mortality rates indexed by attained age
+- `mortality` pass a mortality vector, which is an array of applicable mortality rates indexed by attained age
 - `issue_age` is the assumed issue age for the `SingleLife` and is the basis of many contingency calculations.
 - `alive` Default value is `true`. Useful for joint insurances with different status on the lives insured.
 - `fractional_assump`. Default value is `Uniform()`. This is a `DeathDistribution` from the `MortalityTables.jl` package and is the assumption to use for non-integer ages/times.
 
 # Examples
     using MortalityTables
-    mort = MortalityTables.table("2001 VBT Residual Standard Select and Ultimate - Male Nonsmoker, ANB")
+    mortality = MortalityTables.table("2001 VBT Residual Standard Select and Ultimate - Male Nonsmoker, ANB")
 
     SingleLife(
         mort       = mort.select[30], 
         issue_age  = 30          
     )
 """
-struct SingleLife <: Life
-    mort
-    issue_age
-    alive
-    fractional_assump
+struct SingleLife{M,D} <: Life
+    mortality::M
+    issue_age::Int
+    alive::Bool
+    fractional_assump::D
 end
 
-function SingleLife(;mort,issue_age=nothing,alive=true,fractional_assump = mt.Uniform())
-    return SingleLife(mort;issue_age,alive,fractional_assump)
+function SingleLife(; mortality, issue_age = nothing, alive = true, fractional_assump = mt.Uniform())
+    return SingleLife(mortality; issue_age, alive, fractional_assump)
 end
 
-function SingleLife(mort;issue_age=nothing,alive=true,fractional_assump = mt.Uniform())
+function SingleLife(mortality; issue_age = nothing, alive = true, fractional_assump = mt.Uniform())
     if isnothing(issue_age)
-        issue_age = firstindex(mort)
+        issue_age = firstindex(mortality)
     end
 
-    if !(eltype(mort) <: Real)
-        # most likely case is that mort is an array of vectors
+    if !(eltype(mortality) <: Real)
+        # most likely case is that mortality is an array of vectors
         # use issue age to select the right one (assuming indexed with issue age
-        return SingleLife(mort[issue_age],issue_age,alive,fractional_assump)
+        return SingleLife(mortality[issue_age], issue_age, alive, fractional_assump)
     else
-        return SingleLife(mort,issue_age,alive,fractional_assump)
+        return SingleLife(mortality, issue_age, alive, fractional_assump)
     end
-        
+
 end
 
 """ 
@@ -99,7 +99,7 @@ abstract type JointAssumption end
 """ 
     Frasier()
 
-The assumption of independnt lives in a joint life calculation.
+The assumption of independent lives in a joint life calculation.
 Is a subtype of `JointAssumption`.
 """
 struct Frasier <: JointAssumption end
@@ -144,14 +144,14 @@ Keyword arguments:
 
 # Examples
     using MortalityTables
-    mort = MortalityTables.table("2001 VBT Residual Standard Select and Ultimate - Male Nonsmoker, ANB")
+    mortality = MortalityTables.table("2001 VBT Residual Standard Select and Ultimate - Male Nonsmoker, ANB")
 
     l1 = SingleLife(
-        mort       = mort.select[30], 
+        mortality       = mortality.select[30], 
         issue_age  = 30          
     )
     l2 = SingleLife(
-        mort       = mort.select[30], 
+        mortality       = mortality.select[30], 
         issue_age  = 30          
     )
 
@@ -161,19 +161,19 @@ Keyword arguments:
         joint_assumption = Frasier()
     )
 """
-Base.@kwdef struct JointLife <: Life
+Base.@kwdef struct JointLife{C<:Contingency,J<:JointAssumption} <: Life
     lives::Tuple{SingleLife,SingleLife}
-    contingency::Contingency = LastSurvivor()
-    joint_assumption::JointAssumption = Frasier()
+    contingency::C = LastSurvivor()
+    joint_assumption::J = Frasier()
 end
 
 """
     struct LifeContingency
         life::Life
 """
-struct LifeContingency
-    life::Life
-    int
+struct LifeContingency{L,Y}
+    life::L
+    int::Y
 end
 
 Base.broadcastable(lc::LifeContingency) = Ref(lc)
@@ -204,11 +204,11 @@ function mt.omega(lc::LifeContingency)
 end
 
 function mt.omega(l::SingleLife)
-    return mt.omega(l.mort) - l.issue_age + 1    
+    return mt.omega(l.mortality) - l.issue_age + 1
 end
 
 function mt.omega(l::JointLife)
-    return minimum( omega.(l.lives) )    
+    return minimum(omega.(l.lives))
 end
 
 
@@ -222,7 +222,7 @@ end
 ``D_x`` is a retrospective actuarial commutation function which is the product of the survival and discount factor.
 """
 function D(lc::LifeContingency, to_time)
-    return discount(lc.int, to_time) * survival(lc,to_time)
+    return discount(lc.int, to_time) * survival(lc, to_time)
 end
 
 
@@ -231,8 +231,8 @@ end
 
 ``l_x`` is a retrospective actuarial commutation function which is the survival up to a certain point in time. By default, will have a unitary basis (ie `1.0`), but you can specify `basis` keyword argument to use something different (e.g. `1000` is common in the literature.)
 """
-function l(lc::LifeContingency, to_time; basis=1.0)
-    return survival(lc.life,to_time) * basis
+function l(lc::LifeContingency, to_time; basis = 1.0)
+    return survival(lc.life, to_time) * basis
 end
 
 """
@@ -241,8 +241,8 @@ end
 ``C_x`` is a retrospective actuarial commutation function which is the product of the discount factor and the difference in `l` (``l_x``).
 """
 function C(lc::LifeContingency, to_time)
-    discount(lc.int, to_time+1) * (l(lc,to_time) - l(lc, to_time+1))
-    
+    discount(lc.int, to_time + 1) * (l(lc, to_time) - l(lc, to_time + 1))
+
 end
 
 """
@@ -252,7 +252,8 @@ end
 """
 function N(lc::LifeContingency, from_time)
     range = from_time:(omega(lc)-1)
-    return foldxt(+,Map(from_time->D(lc, from_time)), range)
+    vals = Iterators.map(from_time -> D(lc, from_time), range)
+    return sum(vals)
 end
 
 """
@@ -263,10 +264,11 @@ Issue age is based on the issue_age in the LifeContingency `lc`.
 """
 function M(lc::LifeContingency, from_time)
     range = from_time:omega(lc)-1
-    return foldxt(+,Map(from_time->C(lc, from_time)), range)
+    vals = Iterators.map(from_time -> C(lc, from_time), range)
+    return sum(vals)
 end
 
-E(lc::LifeContingency, t, x) = D(lc,x + t) / D(lc,x)
+E(lc::LifeContingency, t, x) = D(lc, x + t) / D(lc, x)
 
 
 ##################
@@ -275,24 +277,28 @@ E(lc::LifeContingency, t, x) = D(lc,x + t) / D(lc,x)
 
 abstract type Insurance end
 
-LifeContingency(ins::Insurance) = LifeContingency(ins.life,ins.int)
+function LifeContingency(ins::I) where {I<:Insurance}
+    LifeContingency(ins.life, ins.int)
+end
 
-struct WholeLife <: Insurance
-    life
-    int
+struct WholeLife{L,Y} <: Insurance
+    life::L
+    int::Y
 end
 
-struct Term <: Insurance
-    life
-    int
-    n
+struct Term{L,Y} <: Insurance
+    life::L
+    int::Y
+    term::Int
 end
 
 """
-    Insurance(lc::LifeContingency; n=nothing)
-    Insurance(life,interest; n=nothing)
+    Insurance(lc::LifeContingency, term)
+    Insurance(life,interest, term)
+    Insurance(lc::LifeContingency)
+    Insurance(life,interest)
 
-Life insurance with a term period of `n`. If `n` is `nothing`, then whole life insurance.
+Life insurance with a term period of `term`. If `term` is `nothing`, then whole life insurance.
 
 Issue age is based on the `issue_age` in the LifeContingency `lc`.
 
@@ -300,44 +306,57 @@ Issue age is based on the `issue_age` in the LifeContingency `lc`.
 
 ```
 ins = Insurance(
-    SingleLife(mort = UltimateMortality([0.5,0.5]),issue_age = 0),
+    SingleLife(mortality = UltimateMortality([0.5,0.5]),issue_age = 0),
     Yields.Constant(0.05),
-    n = 1
+    1           # 1 year term
 ) 
 ```
 """
-Insurance(lc::LifeContingency; n=nothing) = Insurance(lc.life,lc.int;n)
+Insurance(lc::LifeContingency, term) = Insurance(lc.life, lc.int, term)
+Insurance(lc::LifeContingency) = Insurance(lc.life, lc.int)
 
-function Insurance(lc,int;n=nothing)
-    if isnothing(n)
-        return WholeLife(lc,int)
-    elseif n < 1
-        return ZeroBenefit(lc,int)
-    else
-        Term(lc,int,n)
-    end
+function Insurance(life, int, term::Int)
+    term < 1 && return ZeroBenefit(life, int)
+    return Term(life, int, term)
 end
+function Insurance(life, int)
+    return WholeLife(life, int)
+end
+
+abstract type AnnuityKind end
+struct Due <: AnnuityKind end
+struct Immediate <: AnnuityKind end
 
-struct Due end
-struct Immediate end
+abstract type AnnuityPayable end
+abstract type AnnuityCertain <: AnnuityPayable end
 
-struct Annuity <: Insurance
-    life
-    int
-    payable
-    n
-    start_time
-    certain
-    frequency
+struct TermCertain <: AnnuityCertain
+    term::Int
+    certain::Int
+end
+struct LifeCertain <: AnnuityCertain
+    certain::Int
+end
+struct TermAnnuity <: AnnuityPayable
+    term::Int
 end
+struct LifeAnnuity <: AnnuityPayable end
 
-struct ZeroBenefit <: Insurance
-    life
-    int
+struct Annuity{L,Y,K<:AnnuityKind,P<:AnnuityPayable} <: Insurance
+    life::L
+    int::Y
+    kind::K
+    payable::P
+    start_time::Int
+    frequency::Int
+end
+struct ZeroBenefit{L,Y} <: Insurance
+    life::L
+    int::Y
 end
 
-function ZeroBenefit(lc::LifeContingency) 
-    return ZeroBenefit(lc.life,lc.int)
+function ZeroBenefit(lc::LifeContingency)
+    return ZeroBenefit(lc.life, lc.int)
 end
 
 """
@@ -350,67 +369,92 @@ Annuity due with the benefit period starting at `start_time` and ending after `n
 
 ```
 ins = AnnuityDue(
-    SingleLife(mort = UltimateMortality([0.5,0.5]),issue_age = 0),
+    SingleLife(mortality = UltimateMortality([0.5,0.5]),issue_age = 0),
     Yields.Constant(0.05),
-    n = 1
+    1, # term of policy
 ) 
 ```
-
+#TODO update docs
 """
-function AnnuityDue(life, int; n=nothing,start_time=0,certain=nothing,frequency=1) 
-    if ~isnothing(n) && n < 1
-        return ZeroBenefit(life,int)
+function AnnuityDue(life, int, term; certain = nothing, start_time = 0, frequency = 1)
+    term < 1 && return ZeroBenefit(life, int)
+    if isnothing(certain)
+        Annuity(life, int, Due(), TermAnnuity(term), start_time, frequency)
     else
-        Annuity(life,int,Due(),n,start_time,certain,frequency)
+        Annuity(life, int, Due(), TermCertain(term, certain), start_time, frequency)
     end
 end
 
-function AnnuityDue(lc::LifeContingency; n=nothing,start_time=0,certain=nothing,frequency=1) 
-    return AnnuityDue(lc.life,lc.int;n,start_time,certain,frequency)
+function AnnuityDue(life, int; certain = nothing, start_time = 0, frequency = 1)
+    if isnothing(certain)
+        Annuity(life, int, Due(), LifeAnnuity(), start_time, frequency)
+    else
+        Annuity(life, int, Due(), LifeCertain(certain), start_time, frequency)
+    end
+end
+
+function AnnuityDue(lc::L, term; certain = nothing, start_time = 0, frequency = 1) where {L<:LifeContingency}
+    return AnnuityDue(lc.life, lc.int, term; certain, start_time, frequency)
 end
 
+function AnnuityDue(lc::L; certain = nothing, start_time = 0, frequency = 1) where {L<:LifeContingency}
+    return AnnuityDue(lc.life, lc.int; certain, start_time, frequency)
+end
 
 """
-    AnnuityImmediate(lc::LifeContingency; n=nothing, start_time=0; certain=nothing,frequency=1)
-    AnnuityImmediate(life, interest; n=nothing, start_time=0; certain=nothing,frequency=1)
+    AnnuityImmediate(lc::LifeContingency; term=nothing, start_time=0; certain=nothing,frequency=1)
+    AnnuityImmediate(life, interest; term=nothing, start_time=0; certain=nothing,frequency=1)
 
-Annuity immediate with the benefit period starting at `start_time` and ending after `n` periods with `frequency` payments per year of `1/frequency` amount and a `certain` period with non-contingent payments. 
+Annuity immediate with the benefit period starting at `start_time` and ending after `term` periods with `frequency` payments per year of `1/frequency` amount and a `certain` period with non-contingent payments. 
 
 # Examples
 
 ```
 ins = AnnuityImmediate(
-    SingleLife(mort = UltimateMortality([0.5,0.5]),issue_age = 0),
+    SingleLife(mortality = UltimateMortality([0.5,0.5]),issue_age = 0),
     Yields.Constant(0.05),
-    n = 1
+    1 # term of policy
 ) 
 ```
 
 """
-function AnnuityImmediate(life, int; n=nothing,start_time=0,certain=nothing,frequency=1) 
-    if ~isnothing(n) && n < 1
-        return ZeroBenefit(life,int)
+function AnnuityImmediate(life, int, term; certain = nothing, start_time = 0, frequency = 1)
+    term < 1 && return ZeroBenefit(life, int)
+    if isnothing(certain)
+        Annuity(life, int, Immediate(), TermAnnuity(term), start_time, frequency)
+    else
+        Annuity(life, int, Immediate(), TermCertain(term, certain), start_time, frequency)
+    end
+end
+
+function AnnuityImmediate(life, int; certain = nothing, start_time = 0, frequency = 1)
+    if isnothing(certain)
+        Annuity(life, int, Immediate(), LifeAnnuity(), start_time, frequency)
     else
-        return Annuity(life,int,Immediate(),n,start_time,certain,frequency)
+        Annuity(life, int, Immediate(), LifeCertain(certain), start_time, frequency)
     end
 end
 
-function AnnuityImmediate(lc::LifeContingency; n=nothing,start_time=0,certain=nothing,frequency=1)  
-    return AnnuityImmediate(lc.life,lc.int;n,start_time,certain,frequency)
+function AnnuityImmediate(lc::L, term; certain = nothing, start_time = 0, frequency = 1) where {L<:LifeContingency}
+    return AnnuityImmediate(lc.life, lc.int, term; certain, start_time, frequency)
+end
+
+function AnnuityImmediate(lc::L; certain = nothing, start_time = 0, frequency = 1) where {L<:LifeContingency}
+    return AnnuityImmediate(lc.life, lc.int; certain, start_time, frequency)
 end
 
 
 """
     survival(Insurance)
 
-The survorship vector for the given insurance.
+The survivorship vector for the given insurance.
 """
-function MortalityTables.survival(ins::Insurance)
-    return [survival(ins.life,t-1) for t in timepoints(ins)]
+function MortalityTables.survival(ins::I) where {I<:Insurance}
+    return Iterators.map(t -> survival(ins.life, t - 1), timepoints(ins))
 end
 
 function MortalityTables.survival(ins::Annuity)
-    return [survival(ins.life,t) for t in timepoints(ins)]
+    return Iterators.map(t -> survival(ins.life, t), timepoints(ins))
 end
 
 """
@@ -418,26 +462,26 @@ end
 
 The discount vector for the given insurance.
 """
-function Yields.discount(ins::Insurance)
-    return Yields.discount.(ins.int,timepoints(ins))
+function Yields.discount(ins::I) where {I<:Insurance}
+    return Iterators.map(t -> Yields.discount.(ins.int, t), timepoints(ins))
 end
 
 
 """
     benefit(Insurance)
 
-The unit benefit vector for the given insurance.
+The unit benefit for the given insurance.
 """
-function benefit(ins::Insurance)
-    return ones(length(timepoints(ins)))
+function benefit(ins::I) where {I<:Insurance}
+    return 1.0
 end
 
 function benefit(ins::ZeroBenefit)
-    return zeros(length(timepoints(ins)))
+    return 0.0
 end
 
 function benefit(ins::Annuity)
-    return ones(length(timepoints(ins))) ./ ins.frequency
+    return 1.0 / ins.frequency
 end
 
 
@@ -446,19 +490,29 @@ end
 
 The vector of contingent benefit probabilities for the given insurance.
 """
-function probability(ins::Insurance)
-    return [survival(ins.life,t-1) * decrement(ins.life,t-1,t) for t in timepoints(ins)]
+function probability(ins::I) where {I<:Insurance}
+    # f(t) = survival(ins.life, 0, t) * (1 - survival(lc.life, t - 1, t))
+    # f(t) = (survival(ins.life, 0, t) - survival(ins.life, 0, t) * survival(lc.life, t - 1, t))
+    return Iterators.map(timepoints(ins)) do t
+        survival(ins.life, t - 1) * decrement(ins.life, t - 1, t)
+    end
 end
 
 function probability(ins::ZeroBenefit)
-    return ones(length(timepoints(ins)))
+    return Iterators.repeated(1.0, length(timepoints(ins)))
 end
 
 function probability(ins::Annuity)
-    if isnothing(ins.certain)
-        return  [survival(ins.life,t) for t in timepoints(ins)]
-    else
-        return [t <= ins.certain + ins.start_time ? 1.0 : survival(ins.life,t) for t in timepoints(ins)]
+    return probability(ins.payable, ins)
+end
+
+function probability(ap::AP, ins::Annuity) where {AP<:AnnuityPayable}
+    return Iterators.map(t -> survival(ins.life, t), timepoints(ins))
+end
+
+function probability(ap::AP, ins::Annuity) where {AP<:AnnuityCertain}
+    return Iterators.map(timepoints(ins)) do t
+        t <= ap.certain + ins.start_time ? 1.0 : survival(ins.life, t)
     end
 end
 
@@ -468,8 +522,9 @@ end
 
 The vector of decremented benefit cashflows for the given insurance.
 """
-function cashflows(ins::Insurance)
-   return probability(ins) .* benefit(ins)
+function cashflows(ins::I) where {I<:Insurance}
+    b = benefit(ins)
+    return Iterators.map(p -> p * b, probability(ins))
 end
 
 
@@ -478,41 +533,80 @@ end
 
 The vector of times corresponding to the cashflow vector for the given insurance.
 """
-function timepoints(ins::Insurance)
-    return collect(1:omega(ins.life))
+function timepoints(ins::Insurance)::UnitRange{Int64}
+    return 1:omega(ins.life)
 end
 
-function timepoints(ins::Term)
-    return collect(1:min(omega(ins.life),ins.n))
+function timepoints(ins::Term)::UnitRange{Int64}
+    return 1:min(omega(ins.life), ins.term)
 end
 
 function timepoints(ins::ZeroBenefit)
-    return [0.]
+    return Iterators.repeated(0.0, 1)
 end
 
 function timepoints(ins::Annuity)
-    return timepoints(ins,ins.payable)
+    return timepoints(ins, ins.kind)
 end
 
-function timepoints(ins::Annuity,payable::Due)
-    if isnothing(ins.n)
-        end_time = omega(ins.life)
-    else
-        end_time = ins.n + ins.start_time - 1 / ins.frequency
-    end
+function timepoints(ins::Annuity, kind::K) where {K<:AnnuityKind}
+    return timepoints(ins.payable, ins, kind)
+end
+
+function timepoints(ap::LifeCertain, ins::Annuity, ::Due)
+    end_time = omega(ins.life)
     timestep = 1 / ins.frequency
-    collect(ins.start_time:timestep:end_time)
+    return ins.start_time:timestep:end_time
 end
 
-function timepoints(ins::Annuity,payable::Immediate)
-    if isnothing(ins.n)
-        end_time = omega(ins.life)
-    else
-        end_time = ins.n + ins.start_time
-    end
+function timepoints(ap::LifeAnnuity, ins::Annuity, ::Due)
+    # same timepoints as LifeCertain
+    end_time = omega(ins.life)
     timestep = 1 / ins.frequency
-    end_time = max(ins.start_time + timestep,end_time) # return at least one timepoint to avoid returning empty array
-    collect((ins.start_time + timestep):timestep:end_time)
+    return ins.start_time:timestep:end_time
+end
+
+function timepoints(ap::TermCertain, ins::Annuity, ::Due)
+    end_time = ap.term + ins.start_time - 1 / ins.frequency
+    timestep = 1 / ins.frequency
+    return ins.start_time:timestep:end_time
+end
+
+function timepoints(ap::TermAnnuity, ins::Annuity, ::Due)
+    # same timepoints as 
+    end_time = ap.term + ins.start_time - 1 / ins.frequency
+    timestep = 1 / ins.frequency
+    return ins.start_time:timestep:end_time
+end
+
+function timepoints(ap::LifeCertain, ins::Annuity, ::Immediate)
+    end_time = omega(ins.life)
+    timestep = 1 / ins.frequency
+    end_time = max(ins.start_time + timestep, end_time) # return at least one timepoint to avoid returning empty array
+    return (ins.start_time+timestep):timestep:end_time
+end
+
+function timepoints(ap::LifeAnnuity, ins::Annuity, ::Immediate)
+    # same timepoints as LifeCertain
+    end_time = omega(ins.life)
+    timestep = 1 / ins.frequency
+    end_time = max(ins.start_time + timestep, end_time) # return at least one timepoint to avoid returning empty array
+    return (ins.start_time+timestep):timestep:end_time
+end
+
+function timepoints(ap::TermCertain, ins::Annuity, ::Immediate)
+    end_time = ap.term + ins.start_time
+    timestep = 1 / ins.frequency
+    end_time = max(ins.start_time + timestep, end_time) # return at least one timepoint to avoid returning empty array
+    return (ins.start_time+timestep):timestep:end_time
+end
+
+function timepoints(ap::TermAnnuity, ins::Annuity, ::Immediate)
+    # same timepoints as 
+    end_time = ap.term + ins.start_time
+    timestep = 1 / ins.frequency
+    end_time = max(ins.start_time + timestep, end_time) # return at least one timepoint to avoid returning empty array
+    return (ins.start_time+timestep):timestep:end_time
 end
 
 """
@@ -520,8 +614,12 @@ end
 
 The actuarial present value of the given insurance.
 """
-function ActuaryUtilities.present_value(ins)
-    return present_value(ins.int,cashflows(ins),timepoints(ins))
+function ActuaryUtilities.present_value(ins::T) where {T<:Insurance}
+    cfs = cashflows(ins)
+    times = timepoints(ins)
+    yield = ins.int
+    pv = present_value(yield, cfs, times)
+    return pv
 end
 
 """
@@ -532,18 +630,21 @@ The net premium for a whole life insurance (without second argument) or a term l
 
 The net premium is based on 1 unit of insurance with the death benfit payable at the end of the year and assuming annual net premiums.
 """
-premium_net(lc::LifeContingency) = A(lc) / ä(lc)
-premium_net(lc::LifeContingency,to_time) = A(lc,to_time) / ä(lc,to_time)
+function premium_net(lc::LifeContingency)
+    return A(lc) / ä(lc)
+end
+
+premium_net(lc::LifeContingency, to_time) = A(lc, to_time) / ä(lc, to_time)
 
 """
      reserve_premium_net(lc::LifeContingency,time)
 
 The net premium reserve at the end of year `time`.
 """
-function  reserve_premium_net(lc::LifeContingency, time)
-    PVFB = A(lc) - A(lc,n=time)
-    PVFP = premium_net(lc) * (ä(lc) - ä(lc,n=time))
-    return (PVFB - PVFP) / APV(lc,time)
+function reserve_premium_net(lc::LifeContingency, time)
+    PVFB = A(lc) - A(lc, time)
+    PVFP = premium_net(lc) * (ä(lc) - ä(lc, time))
+    return (PVFB - PVFP) / APV(lc, time)
 end
 
 """
@@ -551,8 +652,8 @@ end
 
 The **actuarial present value** which is the survival times the discount factor for the life contingency.
 """
-function APV(lc::LifeContingency,to_time)
-    return survival(lc,to_time) * discount(lc.int,to_time)
+function APV(lc::LifeContingency, to_time)
+    return survival(lc, to_time) * discount(lc.int, to_time)
 end
 
 """
@@ -561,58 +662,58 @@ end
 
 Return the probablity of death for the given LifeContingency. 
 """
-mt.decrement(lc::LifeContingency,from_time,to_time) = 1 - survival(lc.life,from_time,to_time)
+mt.decrement(lc::LifeContingency, from_time, to_time) = 1 - survival(lc.life, from_time, to_time)
 
 
 """
     survival(lc::LifeContingency,from_time,to_time)
     survival(lc::LifeContingency,to_time)
 
-Return the probablity of survival for the given LifeContingency. 
+Return the probability of survival for the given LifeContingency. 
 """
-mt.survival(lc::LifeContingency,to_time) = survival(lc.life, 0, to_time)
-mt.survival(lc::LifeContingency,from_time,to_time) = survival(lc.life, from_time, to_time)
+mt.survival(lc::LifeContingency, to_time) = survival(lc.life, 0, to_time)
+mt.survival(lc::LifeContingency, from_time, to_time) = survival(lc.life, from_time, to_time)
 
-mt.survival(l::SingleLife,to_time) = survival(l,0,to_time)
-mt.survival(l::SingleLife,from_time,to_time) =survival(l.mort,l.issue_age + from_time,l.issue_age + to_time, l.fractional_assump)
+mt.survival(l::SingleLife, to_time) = survival(l, 0, to_time)
+mt.survival(l::SingleLife, from_time, to_time) = survival(l.mortality, l.issue_age + from_time, l.issue_age + to_time, l.fractional_assump)
 
 """
-    surival(life)
+    survival(life)
 
 Return a survival vector for the given life.
 """
-function mt.survival(l::Life) 
-    ω =   omega(l)
-    return [survival(l,t) for t in 0:ω]
+function mt.survival(l::L) where {L<:Life}
+    ω = omega(l)
+    return Iterators.map(t -> survival(l, t), 0:ω)
 end
 
-mt.survival(l::JointLife,to_time) = survival(l::JointLife,0,to_time)
-function mt.survival(l::JointLife,from_time,to_time) 
-    return survival(l.contingency,l.joint_assumption,l::JointLife,from_time,to_time)
+mt.survival(l::JointLife, to_time) = survival(l::JointLife, 0, to_time)
+function mt.survival(l::JointLife, from_time, to_time)
+    return survival(l.contingency, l.joint_assumption, l::JointLife, from_time, to_time)
 end
 
-function mt.survival(ins::LastSurvivor,assump::JointAssumption,l::JointLife,from_time,to_time)
+function mt.survival(ins::LastSurvivor, assump::JointAssumption, l::JointLife, from_time, to_time)
     to_time == 0 && return 1.0
-    
-    l1,l2 = l.lives
-    ₜpₓ = survival(l1.mort,l1.issue_age + from_time,l1.issue_age + to_time,l1.fractional_assump)
-    ₜpᵧ = survival(l2.mort,l2.issue_age + from_time,l2.issue_age + to_time,l2.fractional_assump)
+
+    l1, l2 = l.lives
+    ₜpₓ = survival(l1.mortality, l1.issue_age + from_time, l1.issue_age + to_time, l1.fractional_assump)
+    ₜpᵧ = survival(l2.mortality, l2.issue_age + from_time, l2.issue_age + to_time, l2.fractional_assump)
     return ₜpₓ + ₜpᵧ - ₜpₓ * ₜpᵧ
 end
 
-Yields.discount(lc::LifeContingency,t) = discount(lc.int,t)
-Yields.discount(lc::LifeContingency,t1,t2) = discount(lc.int,t1,t2)
+Yields.discount(lc::LifeContingency, t) = discount(lc.int, t)
+Yields.discount(lc::LifeContingency, t1, t2) = discount(lc.int, t1, t2)
 
-# function compostion with kwargs. 
-# https://stackoverflow.com/questions/64740010/how-to-alias-composite-function-with-keyword-arguments
-⋄(f, g) = (x...; kw...)->f(g(x...; kw...))
 
 # unexported aliases
 const V = reserve_premium_net
 const v = Yields.discount
-const A = present_value ⋄ Insurance
-const a = present_value ⋄ AnnuityImmediate
-const ä = present_value ⋄ AnnuityDue
+# A(args) = present_value(Insurance(args))
+# a(args, kwargs) = present_value(AnnuityImmediate(args...; kwargs...))
+# ä(args) = present_value(AnnuityDue(args))
+const A = present_value ∘ Insurance
+const a = present_value ∘ AnnuityImmediate
+const ä = present_value ∘ AnnuityDue
 const P = premium_net
 const ω = omega
 
diff --git a/src/scratchpad.jl b/src/scratchpad.jl
deleted file mode 100644
index f8b72a1..0000000
--- a/src/scratchpad.jl
+++ /dev/null
@@ -1,96 +0,0 @@
-using LifeContingencies
-using MortalityTables
-using Dates
-using DataFrames
-
-mort_table_name = "2012 IAM Period Table – Male, ANB"
-improv_table = "Projection Scale G2 – Male, ANB"
-iss_date = Date(2017,09,01)
-val_date = Date(2017,12,31)
-issue_age = 65
-annual_income = 12000
-deferral_period = 0
-benefit_period = 120
-interest_rate = 0.04
-
-# Not used because table name provides 
-# sex = :M
-# projection_scale = :G2
-# age_rule = :ANB
-
-
-mort = MortalityTables.table(mort_table_name)
-imp = MortalityTables.table(improv_table)
-
-table_end = omega(mort)
-
-# the projection scale table only goes to age 105, wheras we want  through age 120
-function imp_rate(table,age)
-    if age > lastindex(table)
-        return 0.0
-    else
-        return table[age]
-    end
-end
-
-SRA = map(0:(table_end - issue_age)) do time
-    
-    att_age = issue_age + time
-    
-    if time > 1 
-        imp_factor = prod(map(age -> 1 - imp_rate(imp,age),issue_age:(att_age-1)))
-    else
-        imp_factor = 1.0
-    end
-    
-    # returned values for each time
-    
-    (
-        att_age = att_age,
-        t=time,
-        q=mort[att_age],
-        imp_factor = imp_factor,
-        q_imp = mort[att_age] * imp_factor,
-        
-    )
-end
-
-### A type to handle life contingent maths via the LifeContingencies package
-ins = LifeContingency(
-    SingleLife(
-        mort = UltimateMortality([x.q_imp for x in SRA],start_age = issue_age), # mort is indexed by attained age, not starting at 1
-        issue_age = issue_age
-    ),
-    InterestRate(interest_rate)
-)
-
-
-ä(ins,55) * annual_income
-sum(LifeContingencies.APV.(ins,1:55) * 12000)
-
-
-
-ℓ₁ = [43302,42854,42081,41351,40050]
-ℓ₂ = [47260,47040,46755,46500,46227]
-
-ps₁ =  ℓ₁ ./ ℓ₁[1]
-qs₁ = [1 - ps₁[t] / ps₁[t - 1] for t in 2:5 ] 
-
-ps₂ =  ℓ₂ ./ ℓ₂[1]
-qs₂ = [1 - ps₂[t] / ps₂[t - 1] for t in 2:5 ] 
-
-m1 = UltimateMortality(qs₁, start_age=65)
-m2 = UltimateMortality(qs₂, start_age=60)
-
-
-l1 = SingleLife(mort = m1, issue_age = 65)
-l2 = SingleLife(mort = m2, issue_age = 60)
-
-jl = JointLife(lives=(l1, l2), contingency = LastSurvivor(), joint_assumption=Frasier())
-
-
-
-ins = LifeContingency(jl,InterestRate(0.05))
-ins_l1 = LifeContingency(jl.lives[1],InterestRate(0.05))
-ins_l2 = LifeContingency(jl.lives[2],InterestRate(0.05))
-# problem 9.1.f
\ No newline at end of file
diff --git a/test/AMLCR.jl b/test/AMLCR.jl
index 31366b6..57f4cb6 100644
--- a/test/AMLCR.jl
+++ b/test/AMLCR.jl
@@ -3,40 +3,40 @@
 
     # §5.7 payment frequency and certain (Tables 5.1 and 5.2)
     function f(age)
-        life = SingleLife(mort = AMLCR_std, issue_age = age)
+        life = SingleLife(mortality = AMLCR_std, issue_age = age)
         int = Yields.Constant(0.05)
         lc = [
-            AnnuityImmediate(life,int)
-            AnnuityImmediate(life,int,frequency=4)
-            AnnuityDue(life,int)
-            AnnuityDue(life,int,frequency=4)
-            AnnuityImmediate(life,int,n=10)
-            AnnuityImmediate(life,int,n=10,frequency=4)
-            AnnuityDue(life,int,n=10,frequency=4)
+            AnnuityImmediate(life, int)
+            AnnuityImmediate(life, int, frequency = 4)
+            AnnuityDue(life, int)
+            AnnuityDue(life, int, frequency = 4)
+            AnnuityImmediate(life, int, 10)
+            AnnuityImmediate(life, int, 10, frequency = 4)
+            AnnuityDue(life, int, 10, frequency = 4)
         ]
-        
+
         return present_value.(lc)
     end
 
     # atol only to two decimals b/c AMLCR uses rounded rates?
-    @test all(isapprox.(f(20), [18.966, 19.338, 19.966, 19.588, 7.711, 7.855, 7.952],atol=.01))
-    @test all(isapprox.(f(80), [ 7.548,  7.917,  8.548,  8.167, 6.128, 6.373, 6.539],atol=.01))
+    @test all(isapprox.(f(20), [18.966, 19.338, 19.966, 19.588, 7.711, 7.855, 7.952], atol = 0.01))
+    @test all(isapprox.(f(80), [7.548, 7.917, 8.548, 8.167, 6.128, 6.373, 6.539], atol = 0.01))
 
-    life = SingleLife(mort = AMLCR_std, issue_age = 20)
+    life = SingleLife(mortality = AMLCR_std, issue_age = 20)
     int = Yields.Constant(0.05)
 
     # property tests
 
-    @test present_value(AnnuityDue(life,int)) > present_value(AnnuityDue(life,int,start_time=5))
+    @test present_value(AnnuityDue(life, int)) > present_value(AnnuityDue(life, int, start_time = 5))
+
+    @test present_value(AnnuityDue(life, int, 5, certain = 5, start_time = 5)) == sum([1 for t = 5:9] .* [1 / 1.05^t for t = 5:9])
 
-    @test present_value(AnnuityDue(life,int,n=5,certain=5,start_time=5)) == sum([1 for t in 5:9] .* [1/1.05 ^t for t in 5:9])
-    
     # relation on pg 124
     @test issorted(present_value.([
-        AnnuityImmediate(life,int)
-        AnnuityImmediate(life,int,frequency=4) 
-        AnnuityDue(life,int,frequency=4)
-        AnnuityDue(life,int) 
+        AnnuityImmediate(life, int)
+        AnnuityImmediate(life, int, frequency = 4)
+        AnnuityDue(life, int, frequency = 4)
+        AnnuityDue(life, int)
     ]))
 
 end#
\ No newline at end of file
diff --git a/test/joint_life.jl b/test/joint_life.jl
index b133ad5..724a931 100644
--- a/test/joint_life.jl
+++ b/test/joint_life.jl
@@ -1,72 +1,72 @@
 @testset "Joint Life" begin
 
-        
+
     @testset "Joint Last Survivor unknown status" begin
-        
+
         @testset "ALMCR §9.4" begin
-            ℓ₁ = [43302,42854,42081,41351,40050]
-            ℓ₂ = [47260,47040,46755,46500,46227]
+            ℓ₁ = [43302, 42854, 42081, 41351, 40050]
+            ℓ₂ = [47260, 47040, 46755, 46500, 46227]
+
+            ps₁ = ℓ₁ ./ ℓ₁[1]
+            qs₁ = [1 - ps₁[t] / ps₁[t-1] for t = 2:5]
 
-            ps₁ =  ℓ₁ ./ ℓ₁[1]
-            qs₁ = [1 - ps₁[t] / ps₁[t - 1] for t in 2:5 ] 
+            ps₂ = ℓ₂ ./ ℓ₂[1]
+            qs₂ = [1 - ps₂[t] / ps₂[t-1] for t = 2:5]
 
-            ps₂ =  ℓ₂ ./ ℓ₂[1]
-            qs₂ = [1 - ps₂[t] / ps₂[t - 1] for t in 2:5 ] 
-            
-            m1 = UltimateMortality(qs₁, start_age=65)
-            m2 = UltimateMortality(qs₂, start_age=60)
+            m1 = UltimateMortality(qs₁, start_age = 65)
+            m2 = UltimateMortality(qs₂, start_age = 60)
 
             @test decrement(m1, 65, 66) == 1 - ℓ₁[2] / ℓ₁[1]
             @test decrement(m2, 60, 61) == 1 - ℓ₂[2] / ℓ₂[1]
 
-            l1 = SingleLife(mort = m1, issue_age = 65)
-            l2 = SingleLife(mort = m2, issue_age = 60)
-
-            jl = JointLife(lives=(l1, l2), contingency = LastSurvivor(), joint_assumption=Frasier())
-            
-            @test isapprox( survival(jl, 2) , 0.9997, atol = 1e-4)
-            
-            
-            ins = LifeContingency(jl,Yields.Constant(0.05))
-            ins_l1 = LifeContingency(jl.lives[1],Yields.Constant(0.05))
-            ins_l2 = LifeContingency(jl.lives[2],Yields.Constant(0.05))
+            l1 = SingleLife(mortality = m1, issue_age = 65)
+            l2 = SingleLife(mortality = m2, issue_age = 60)
+
+            jl = JointLife(lives = (l1, l2), contingency = LastSurvivor(), joint_assumption = Frasier())
+
+            @test isapprox(survival(jl, 2), 0.9997, atol = 1e-4)
+
+
+            ins = LifeContingency(jl, Yields.Constant(0.05))
+            ins_l1 = LifeContingency(jl.lives[1], Yields.Constant(0.05))
+            ins_l2 = LifeContingency(jl.lives[2], Yields.Constant(0.05))
             # problem 9.1.f
-            @test isapprox( present_value(AnnuityDue(ins,n=5)), 4.5437, atol = 1e-4)
+            @test isapprox(present_value(AnnuityDue(ins, 5)), 4.5437, atol = 1e-4)
 
-            @test isapprox( present_value(AnnuityDue(ins)), 4.5437, atol = 1e-4)
+            @test isapprox(present_value(AnnuityDue(ins)), 4.5437, atol = 1e-4)
         end
-    
+
         @testset "CIA tables" begin
             m1 = MortalityTables.table("1986-92 CIA – Male Smoker, ANB")
             m2 = MortalityTables.table("1986-92 CIA – Female Nonsmoker, ANB")
-            l1 = SingleLife(mort = m1.ultimate, issue_age = 40)
-            l2 = SingleLife(mort = m2.ultimate, issue_age = 37)
+            l1 = SingleLife(mortality = m1.ultimate, issue_age = 40)
+            l2 = SingleLife(mortality = m2.ultimate, issue_age = 37)
+
+            jl = JointLife(lives = (l1, l2), contingency = LastSurvivor(), joint_assumption = Frasier())
 
-            jl = JointLife(lives=(l1, l2), contingency=LastSurvivor(), joint_assumption=Frasier())
-            
             @testset "independent lives" begin
-                for time in 1:40
-                    tpx = survival(l1,time)
-                    tpy = survival(l2,time)
+                for time = 1:40
+                    tpx = survival(l1, time)
+                    tpy = survival(l2, time)
 
                     @test survival(jl, time) == tpx + tpy - tpx * tpy
                 end
             end
-        
-            q_annual = [0.00000141120,0.00000478349,0.00000921100,0.00001508953,0.00002255325,0.00003179413,0.00004327035,0.00005782855,0.00007524178,0.00009695039,0.00012370408,0.00015606419,0.00019612090,0.00024529620,0.00030502659,0.00037768543,0.00046587280,0.00057325907,0.00070238876,0.00085952824,0.00104786439,0.00127420204,0.00154640464,0.00187374100,0.00226186101,0.00272457482,0.00327193743,0.00391984214,0.00468084563,0.00557778027,0.00662135901,0.00783684326,0.00924475551,0.01086696400,0.01272977389,0.01485150445,0.01727277853,0.02000566587,0.02308982834,0.02654184882,0.03039819991,0.03469299691,0.03944737905,0.04469931521,0.05048294677,0.05683522818,0.06379854263,0.07142629169,0.07976664920,0.08888579420,0.09884411368,0.10971505011,0.12159455247,0.13456410066,0.14873755448,0.16421406941,0.18111392905,0.19954137714,0.21962070363,0.24144744481,0.26515968560,0.29099967654,0.31901974549,0.35111309929,0.39733960046,0.47004540325,0.58255000000,0.74852030000,1.00000000000]
-            q_cumulative = [0.00000141120,0.00000619469,0.00001540563,0.00003049492,0.00005304748,0.00008483992,0.00012810660,0.00018592774,0.00026115553,0.00035808060,0.00048174038,0.00063772939,0.00083372522,0.00107881691,0.00138351443,0.00176067732,0.00222572986,0.00279771301,0.00349813669,0.00435465818,0.00539795948,0.00666528343,0.00820138084,0.01005975458,0.01229886182,0.01498992747,0.01821281880,0.02206126957,0.02663884979,0.03206804441,0.03847706939,0.04601237389,0.05483175625,0.06510286552,0.07700389465,0.09071177542,0.10641770955,0.12429441828,0.14451430984,0.16722048170,0.19253547997,0.22054884408,0.25129614928,0.28476269870,0.32086998531,0.35946849466,0.40033347120,0.44316542761,0.48758225561,0.53312891378,0.57927637250,0.62543608637,0.67098101782,0.71525516126,0.75760741222,0.79741168545,0.83410325108,0.86720651682,0.89637071504,0.92139174110,0.94223548231,0.95904493828,0.97211041164,0.98190281145,0.98909354112,0.99422007198,0.99758716905,0.99939322200,1.00000000000]
+
+            q_annual = [0.00000141120, 0.00000478349, 0.00000921100, 0.00001508953, 0.00002255325, 0.00003179413, 0.00004327035, 0.00005782855, 0.00007524178, 0.00009695039, 0.00012370408, 0.00015606419, 0.00019612090, 0.00024529620, 0.00030502659, 0.00037768543, 0.00046587280, 0.00057325907, 0.00070238876, 0.00085952824, 0.00104786439, 0.00127420204, 0.00154640464, 0.00187374100, 0.00226186101, 0.00272457482, 0.00327193743, 0.00391984214, 0.00468084563, 0.00557778027, 0.00662135901, 0.00783684326, 0.00924475551, 0.01086696400, 0.01272977389, 0.01485150445, 0.01727277853, 0.02000566587, 0.02308982834, 0.02654184882, 0.03039819991, 0.03469299691, 0.03944737905, 0.04469931521, 0.05048294677, 0.05683522818, 0.06379854263, 0.07142629169, 0.07976664920, 0.08888579420, 0.09884411368, 0.10971505011, 0.12159455247, 0.13456410066, 0.14873755448, 0.16421406941, 0.18111392905, 0.19954137714, 0.21962070363, 0.24144744481, 0.26515968560, 0.29099967654, 0.31901974549, 0.35111309929, 0.39733960046, 0.47004540325, 0.58255000000, 0.74852030000, 1.00000000000]
+            q_cumulative = [0.00000141120, 0.00000619469, 0.00001540563, 0.00003049492, 0.00005304748, 0.00008483992, 0.00012810660, 0.00018592774, 0.00026115553, 0.00035808060, 0.00048174038, 0.00063772939, 0.00083372522, 0.00107881691, 0.00138351443, 0.00176067732, 0.00222572986, 0.00279771301, 0.00349813669, 0.00435465818, 0.00539795948, 0.00666528343, 0.00820138084, 0.01005975458, 0.01229886182, 0.01498992747, 0.01821281880, 0.02206126957, 0.02663884979, 0.03206804441, 0.03847706939, 0.04601237389, 0.05483175625, 0.06510286552, 0.07700389465, 0.09071177542, 0.10641770955, 0.12429441828, 0.14451430984, 0.16722048170, 0.19253547997, 0.22054884408, 0.25129614928, 0.28476269870, 0.32086998531, 0.35946849466, 0.40033347120, 0.44316542761, 0.48758225561, 0.53312891378, 0.57927637250, 0.62543608637, 0.67098101782, 0.71525516126, 0.75760741222, 0.79741168545, 0.83410325108, 0.86720651682, 0.89637071504, 0.92139174110, 0.94223548231, 0.95904493828, 0.97211041164, 0.98190281145, 0.98909354112, 0.99422007198, 0.99758716905, 0.99939322200, 1.00000000000]
             @testset "precalced vectors" begin
-                for time in 1:40
-                    @test isapprox(decrement(jl,time), q_cumulative[time], atol = 1e-6)
+                for time = 1:40
+                    @test isapprox(decrement(jl, time), q_cumulative[time], atol = 1e-6)
                 end
 
-                for time in 1:40
-                    q′ =  1 - survival(jl, time) / survival(jl, time-1)
+                for time = 1:40
+                    q′ = 1 - survival(jl, time) / survival(jl, time - 1)
 
                     @test isapprox(q′, q_annual[time], atol = 1e-6)
                 end
 
-                for time in 1:40
+                for time = 1:40
                     @test isapprox(survival(jl, time), 1 - q_cumulative[time], atol = 1e-6)
                 end
             end
diff --git a/test/simple_mort.jl b/test/simple_mort.jl
index 408a1b6..e1e4b4f 100644
--- a/test/simple_mort.jl
+++ b/test/simple_mort.jl
@@ -1,139 +1,139 @@
 @testset "basic building blocks" begin
-    mt = UltimateMortality([0.5,0.5])
+    mt = UltimateMortality([0.5, 0.5])
 
     # whole life insurance
     ins = Insurance(
-            SingleLife(mort = mt,issue_age = 0),
-            Yields.Constant(0.05)
-    ) 
-
-    @test all(survival(SingleLife(mort = mt,issue_age = 0)) .== [1.0, 0.5,0.25])
-
-    @test timepoints(ins) == [1.0,2.0]
-    @test survival(ins) == [1.0,0.5]
-    @test discount(ins) == [1.0 / 1.05, 1 / 1.05^2]
-    @test benefit(ins) == [1.0,1.0]
-    @test probability(ins) == [0.5,0.25]
-    @test cashflows(ins) == [0.5,0.25]
-    @test cashflows(ins) == benefit(ins) .* probability(ins)
-    @test present_value(ins)  ≈ 0.5 / 1.05 + 0.5 * 0.5 / 1.05 ^ 2
-    @test present_value(ins) ≈ LifeContingencies.A(ins.life,ins.int)
+        SingleLife(mortality = mt, issue_age = 0),
+        Yields.Constant(0.05)
+    )
+
+    @test all(survival(SingleLife(mortality = mt, issue_age = 0)) .== [1.0, 0.5, 0.25])
+
+    @test [timepoints(ins)...] == [1.0, 2.0]
+    @test [survival(ins)...] == [1.0, 0.5]
+    @test [discount(ins)...] == [1.0 / 1.05, 1 / 1.05^2]
+    @test benefit(ins) == 1.0
+    @test [probability(ins)...] == [0.5, 0.25]
+    @test [cashflows(ins)...] == [0.5, 0.25]
+    @test [cashflows(ins)...] == benefit(ins) .* probability(ins)
+    @test present_value(ins) ≈ 0.5 / 1.05 + 0.5 * 0.5 / 1.05^2
+    @test present_value(ins) ≈ LifeContingencies.A(ins.life, ins.int)
 
     # basic life contingency tests
-    @test survival(LifeContingency(ins),0,1) ≈ 0.5
-    @test survival(LifeContingency(ins),0,2) ≈ 0.25
-    @test discount(LifeContingency(ins),0,1) ≈ 1/1.05
-    @test discount(LifeContingency(ins),0,2) ≈ 1/1.05^2
+    @test survival(LifeContingency(ins), 0, 1) ≈ 0.5
+    @test survival(LifeContingency(ins), 0, 2) ≈ 0.25
+    @test discount(LifeContingency(ins), 0, 1) ≈ 1 / 1.05
+    @test discount(LifeContingency(ins), 0, 2) ≈ 1 / 1.05^2
 
     # term life insurance
     ins = Insurance(
-            SingleLife(mort = mt,issue_age = 0),
-            Yields.Constant(0.05),
-            n=1
-    ) 
-
-    @test survival(ins) == [1.0]
-    @test discount(ins) == [1.0 / 1.05]
-    @test benefit(ins) == [1.0]
-    @test probability(ins) == [0.5]
-    @test cashflows(ins) == [0.5]
-    @test cashflows(ins) == benefit(ins) .* probability(ins)
-    @test timepoints(ins) == [1.0]
-    @test present_value(ins)  ≈ 0.5 / 1.05
-    
+        SingleLife(mortality = mt, issue_age = 0),
+        Yields.Constant(0.05),
+        1
+    )
+
+    @test [survival(ins)...] == [1.0]
+    @test [discount(ins)...] == [1.0 / 1.05]
+    @test benefit(ins) == 1.0
+    @test [probability(ins)...] == [0.5]
+    @test [cashflows(ins)...] == [0.5]
+    @test [cashflows(ins)...] == benefit(ins) .* probability(ins)
+    @test [timepoints(ins)...] == [1.0]
+    @test present_value(ins) ≈ 0.5 / 1.05
+
     # annuity due
     ins = AnnuityDue(
-            SingleLife(mort = mt,issue_age = 0),
-            Yields.Constant(0.05)
-    ) 
-
-    @test survival(ins) == [1.0,0.5,.25]
-    @test discount(ins) == [1.0, 1 / 1.05^1, 1 / 1.05^2]
-    @test benefit(ins) == [1.0,1.0,1.0]
-    @test timepoints(ins) == [0.0,1.0,2.0]  
-    @test probability(ins) == [1.,0.5,0.25]
-    @test cashflows(ins) == [1.0,0.5,0.25]
-    @test cashflows(ins) == benefit(ins) .* probability(ins)
-    @test present_value(ins)  ≈ 1 + 1 * .5 / 1.05 +  1 * .25 / 1.05 ^2
+        SingleLife(mortality = mt, issue_age = 0),
+        Yields.Constant(0.05)
+    )
+
+    @test [survival(ins)...] == [1.0, 0.5, 0.25]
+    @test [discount(ins)...] == [1.0, 1 / 1.05^1, 1 / 1.05^2]
+    @test benefit(ins) == 1.0
+    @test [timepoints(ins)...] == [0.0, 1.0, 2.0]
+    @test [probability(ins)...] == [1.0, 0.5, 0.25]
+    @test [cashflows(ins)...] == [1.0, 0.5, 0.25]
+    @test [cashflows(ins)...] == benefit(ins) .* probability(ins)
+    @test present_value(ins) ≈ 1 + 1 * 0.5 / 1.05 + 1 * 0.25 / 1.05^2
 
     ins = AnnuityDue(
-        SingleLife(mort = mt,issue_age = 0),
+        SingleLife(mortality = mt, issue_age = 0),
         Yields.Constant(0.05),
-        n = 2
-) 
-    @test present_value(ins)  ≈ 1 + 1 * .5 / 1.05
+        2
+    )
+    @test present_value(ins) ≈ 1 + 1 * 0.5 / 1.05
 
     ins = AnnuityImmediate(
-        SingleLife(mort = mt,issue_age = 0),
+        SingleLife(mortality = mt, issue_age = 0),
         Yields.Constant(0.05),
-        n = 1
-    ) 
+        1
+    )
 
-    @test present_value(ins)  ≈ 1 * .5 * 1 / 1.05
+    @test present_value(ins) ≈ 1 * 0.5 * 1 / 1.05
 
     ins = AnnuityDue(
-        SingleLife(mort = mt,issue_age = 0),
+        SingleLife(mortality = mt, issue_age = 0),
         Yields.Constant(0.05),
-        n = 1,
-        start_time=1
-    ) 
+        1,
+        start_time = 1
+    )
 
-    @test timepoints(ins)  == [1.0]
-    @test probability(ins)  == [0.5]
-    @test present_value(ins)  ≈ 1 * .5 * 1 / 1.05
+    @test timepoints(ins) == [1.0]
+    @test [probability(ins)...] == [0.5]
+    @test present_value(ins) ≈ 1 * 0.5 * 1 / 1.05
 
 end
 
 @testset "one  year" begin
     ins = LifeContingency(
         SingleLife(
-            mort = UltimateMortality([0.5]),
+            mortality = UltimateMortality([0.5]),
             issue_age = 0
         ),
         Yields.Constant(0.05)
     )
 
-    @test survival(ins,1) ≈ 0.5
-    @test survival(ins,0) ≈ 1.0
-    @test survival(ins.life,0,0.5) ≈ 1 - 0.5 * 0.5
-    @test survival(ins,0.5) ≈ 1 - 0.5 * 0.5
+    @test survival(ins, 1) ≈ 0.5
+    @test survival(ins, 0) ≈ 1.0
+    @test survival(ins.life, 0, 0.5) ≈ 1 - 0.5 * 0.5
+    @test survival(ins, 0.5) ≈ 1 - 0.5 * 0.5
 
     @test omega(ins) ≈ 1
-    @test present_value(AnnuityDue(ins)) ≈ 1 + 1 * .5 / 1.05
-    @test present_value(AnnuityDue(ins,n=1)) ≈ 1
-    @test present_value(AnnuityDue(ins,n=0)) == 0
-    @test present_value(AnnuityImmediate(ins,n=1)) ≈ 1 * .5 / 1.05
-    @test present_value(AnnuityImmediate(ins,n=0)) == 0
+    @test present_value(AnnuityDue(ins)) ≈ 1 + 1 * 0.5 / 1.05
+    @test present_value(AnnuityDue(ins, 1)) ≈ 1
+    @test present_value(AnnuityDue(ins, 0)) == 0
+    @test present_value(AnnuityImmediate(ins, 1)) ≈ 1 * 0.5 / 1.05
+    @test present_value(AnnuityImmediate(ins, 0)) == 0
 
     @test present_value(Insurance(ins)) ≈ 0.5 / 1.05
-    @test present_value(Insurance(ins,n=1)) ≈ 0.5 / 1.05
-    @test present_value(Insurance(ins,n=0)) ≈ 0
+    @test present_value(Insurance(ins, 1)) ≈ 0.5 / 1.05
+    @test present_value(Insurance(ins, 0)) ≈ 0
 
 
     ins_jl = LifeContingency(
-        JointLife((ins.life,ins.life),LastSurvivor(),Frasier()),
+        JointLife((ins.life, ins.life), LastSurvivor(), Frasier()),
         Yields.Constant(0.05)
     )
 
     @test omega(ins_jl) ≈ 1
-    @test present_value(AnnuityDue(ins_jl)) ≈ 1 + 1 * .75 / 1.05
-    @test present_value(AnnuityDue(ins_jl,n=1)) ≈ 1
-    @test present_value(AnnuityImmediate(ins_jl,n=1)) ≈ 1 * .75 / 1.05
-    @test present_value(AnnuityDue(ins_jl,n=2)) ≈ 1 + 1 * .75 / 1.05
-    @test present_value(AnnuityDue(ins_jl,n=2;certain=2)) ≈ 1 + 1 / 1.05 
-    @test present_value(AnnuityDue(ins_jl,n=0)) == 0
-
-    @test survival(ins_jl,1) ≈ .5 + .5 - .5 * .5
-    @test all(survival(JointLife((ins.life,ins.life),LastSurvivor(),Frasier())) .== [1.,.75])
-    @test present_value(Insurance(ins_jl)) ≈ .25 / 1.05
-    @test present_value(Insurance(ins_jl,n=1)) ≈ 0.25 / 1.05
-    @test present_value(Insurance(ins_jl,n=0)) ≈ 0
+    @test present_value(AnnuityDue(ins_jl)) ≈ 1 + 1 * 0.75 / 1.05
+    @test present_value(AnnuityDue(ins_jl, 1)) ≈ 1
+    @test present_value(AnnuityImmediate(ins_jl, 1)) ≈ 1 * 0.75 / 1.05
+    @test present_value(AnnuityDue(ins_jl, 2)) ≈ 1 + 1 * 0.75 / 1.05
+    @test present_value(AnnuityDue(ins_jl, 2; certain = 2)) ≈ 1 + 1 / 1.05
+    @test present_value(AnnuityDue(ins_jl, 0)) == 0
+
+    @test survival(ins_jl, 1) ≈ 0.5 + 0.5 - 0.5 * 0.5
+    @test all(survival(JointLife((ins.life, ins.life), LastSurvivor(), Frasier())) .== [1.0, 0.75])
+    @test present_value(Insurance(ins_jl)) ≈ 0.25 / 1.05
+    @test present_value(Insurance(ins_jl, 1)) ≈ 0.25 / 1.05
+    @test present_value(Insurance(ins_jl, 0)) ≈ 0
 end
 
 @testset "two year no discount" begin
     ins = LifeContingency(
         SingleLife(
-            mort = UltimateMortality([0.0,0.0]),
+            mortality = UltimateMortality([0.0, 0.0]),
             issue_age = 0
         ),
         Yields.Constant(0.00)
@@ -141,111 +141,111 @@ end
 
     @test omega(ins) ≈ 2
     @test present_value(AnnuityDue(ins)) ≈ 3
-    @test present_value(AnnuityDue(ins;start_time=1)) ≈ 2
-    @test present_value(AnnuityDue(ins,n=1)) ≈ 1 
-    @test present_value(AnnuityDue(ins,n=2)) ≈ 2
-    @test_throws BoundsError present_value(AnnuityDue(ins,n=2;start_time=2))
-    @test present_value(AnnuityDue(ins,n=3)) ≈ 3
-    @test present_value(AnnuityDue(ins,n=0)) == 0
-    @test present_value(AnnuityImmediate(ins,n=0)) == 0
-    @test present_value(AnnuityImmediate(ins,n=1)) ≈ 1
-    @test present_value(AnnuityImmediate(ins,n=1;start_time=1)) ≈ 1
-    @test_throws BoundsError  present_value(AnnuityImmediate(ins;start_time=2))
-    @test present_value(AnnuityImmediate(ins,n=2)) ≈ 2
+    @test present_value(AnnuityDue(ins; start_time = 1)) ≈ 2
+    @test present_value(AnnuityDue(ins, 1)) ≈ 1
+    @test present_value(AnnuityDue(ins, 2)) ≈ 2
+    @test_throws BoundsError present_value(AnnuityDue(ins, 2; start_time = 2))
+    @test present_value(AnnuityDue(ins, 3)) ≈ 3
+    @test present_value(AnnuityDue(ins, 0)) == 0
+    @test present_value(AnnuityImmediate(ins, 0)) == 0
+    @test present_value(AnnuityImmediate(ins, 1)) ≈ 1
+    @test present_value(AnnuityImmediate(ins, 1; start_time = 1)) ≈ 1
+    @test_throws BoundsError present_value(AnnuityImmediate(ins; start_time = 2))
+    @test present_value(AnnuityImmediate(ins, 2)) ≈ 2
     @test present_value(AnnuityImmediate(ins)) ≈ 2
-    @test present_value(AnnuityImmediate(ins;certain=0)) ≈ 2
-    @test present_value(AnnuityImmediate(ins;certain=2)) ≈ 2
+    @test present_value(AnnuityImmediate(ins; certain = 0)) ≈ 2
+    @test present_value(AnnuityImmediate(ins; certain = 2)) ≈ 2
 
     @test present_value(Insurance(ins)) ≈ 0
-    @test present_value(Insurance(ins,n=1)) ≈ 0
-    @test present_value(Insurance(ins,n=0)) ≈ 0
+    @test present_value(Insurance(ins, 1)) ≈ 0
+    @test present_value(Insurance(ins, 0)) ≈ 0
 
     ins_jl = LifeContingency(
         JointLife(
-            lives = (ins.life,ins.life),
+            lives = (ins.life, ins.life),
             contingency = LastSurvivor(),
             joint_assumption = Frasier()),
         Yields.Constant(0.00)
     )
 
-    @test survival(ins_jl,0) ≈ 1.0
-    @test survival(ins_jl,1) ≈ 1
-    @test survival(ins_jl,2) ≈ 1
+    @test survival(ins_jl, 0) ≈ 1.0
+    @test survival(ins_jl, 1) ≈ 1
+    @test survival(ins_jl, 2) ≈ 1
 
 end
 
 @testset "two year with interest" begin
     ins = LifeContingency(
         SingleLife(
-            mort = UltimateMortality([0.5,0.5]),
+            mortality = UltimateMortality([0.5, 0.5]),
             issue_age = 0
         ),
         Yields.Constant(0.05)
     )
 
     @test omega(ins) ≈ 2
-    @test present_value(AnnuityDue(ins)) ≈ 1 + 1 * .5 * 1 / 1.05 +  1 * .25 / 1.05 ^2
-    @test present_value(AnnuityDue(ins,n=1)) ≈ 1 
-    @test present_value(AnnuityDue(ins,n=2)) ≈ 1 + 1 * .5 * 1 / 1.05
-    @test present_value(AnnuityDue(ins,n=3)) ≈ 1 + 1 * .5 * 1 / 1.05 +  1 * .25 / 1.05 ^2
-    @test present_value(AnnuityDue(ins,n=0)) ≈ 0
-    @test present_value(AnnuityImmediate(ins,n=0)) ≈ 0
-    @test present_value(AnnuityImmediate(ins,n=1)) ≈ 1 * .5 * 1 / 1.05
-
-    @test present_value(Insurance(ins)) ≈ 0.5 / 1.05 + 0.5 * 0.5 / 1.05 ^ 2
-    @test present_value(Insurance(ins,n=1)) ≈ 0.5 / 1.05
-    @test present_value(Insurance(ins,n=0)) ≈ 0
+    @test present_value(AnnuityDue(ins)) ≈ 1 + 1 * 0.5 * 1 / 1.05 + 1 * 0.25 / 1.05^2
+    @test present_value(AnnuityDue(ins, 1)) ≈ 1
+    @test present_value(AnnuityDue(ins, 2)) ≈ 1 + 1 * 0.5 * 1 / 1.05
+    @test present_value(AnnuityDue(ins, 3)) ≈ 1 + 1 * 0.5 * 1 / 1.05 + 1 * 0.25 / 1.05^2
+    @test present_value(AnnuityDue(ins, 0)) ≈ 0
+    @test present_value(AnnuityImmediate(ins, 0)) ≈ 0
+    @test present_value(AnnuityImmediate(ins, 1)) ≈ 1 * 0.5 * 1 / 1.05
+
+    @test present_value(Insurance(ins)) ≈ 0.5 / 1.05 + 0.5 * 0.5 / 1.05^2
+    @test present_value(Insurance(ins, 1)) ≈ 0.5 / 1.05
+    @test present_value(Insurance(ins, 0)) ≈ 0
 
     ins_jl = LifeContingency(
         JointLife(
-            lives = (ins.life,ins.life),
+            lives = (ins.life, ins.life),
             contingency = LastSurvivor(),
             joint_assumption = Frasier()),
         Yields.Constant(0.05)
     )
 
-    @test survival(ins_jl,0) ≈ 1.0
-    @test survival(ins_jl,1) ≈ .5 + .5 - .5 * .5
-    @test survival(ins_jl,2) ≈ (.25 + .25 - .25 * .25)
+    @test survival(ins_jl, 0) ≈ 1.0
+    @test survival(ins_jl, 1) ≈ 0.5 + 0.5 - 0.5 * 0.5
+    @test survival(ins_jl, 2) ≈ (0.25 + 0.25 - 0.25 * 0.25)
 
 end
 
 @testset "two years" begin
     ins = LifeContingency(
         SingleLife(
-            mort = UltimateMortality([0.5,0.5]),
+            mortality = UltimateMortality([0.5, 0.5]),
             issue_age = 0
         ),
         Yields.Constant(0.05)
     )
 
     @test omega(ins) ≈ 2
-    @test present_value(AnnuityDue(ins,n=1)) ≈ 1
-    @test present_value(AnnuityDue(ins,n=2)) ≈ 1 + 1 * .5 * 1 / 1.05 
-    @test present_value(AnnuityDue(ins,n=3)) ≈ 1 + 1 * .5 * 1 / 1.05 + 1 * .25 * 1 / 1.05 ^ 2
-    @test present_value(AnnuityDue(ins,n=0)) == 0
-    @test present_value(AnnuityImmediate(ins,n=0)) == 0
-    @test present_value(AnnuityImmediate(ins,n=1)) ≈ 1 * .5 * 1 / 1.05 
+    @test present_value(AnnuityDue(ins, 1)) ≈ 1
+    @test present_value(AnnuityDue(ins, 2)) ≈ 1 + 1 * 0.5 * 1 / 1.05
+    @test present_value(AnnuityDue(ins, 3)) ≈ 1 + 1 * 0.5 * 1 / 1.05 + 1 * 0.25 * 1 / 1.05^2
+    @test present_value(AnnuityDue(ins, 0)) == 0
+    @test present_value(AnnuityImmediate(ins, 0)) == 0
+    @test present_value(AnnuityImmediate(ins, 1)) ≈ 1 * 0.5 * 1 / 1.05
 
-    @test present_value(Insurance(ins)) ≈ 0.5 / 1.05 + 0.5 * 0.5 / 1.05 ^ 2
-    @test present_value(Insurance(ins,n=1)) ≈ 0.5 / 1.05
-    @test present_value(Insurance(ins,n=0)) ≈ 0
+    @test present_value(Insurance(ins)) ≈ 0.5 / 1.05 + 0.5 * 0.5 / 1.05^2
+    @test present_value(Insurance(ins, 1)) ≈ 0.5 / 1.05
+    @test present_value(Insurance(ins, 0)) ≈ 0
 
     ins_jl = LifeContingency(
         JointLife(
-            lives = (ins.life,ins.life),
+            lives = (ins.life, ins.life),
             contingency = LastSurvivor(),
             joint_assumption = Frasier()),
         Yields.Constant(0.05)
     )
 
     @test omega(ins_jl) ≈ 2
-    @test present_value(AnnuityDue(ins_jl,n=1)) ≈ 1
-    @test present_value(AnnuityDue(ins_jl,n=2)) ≈ 1 + 1 * .75 /1.05
-    @test present_value(AnnuityDue(ins_jl,n=3)) ≈ 1 + 1 * .75 /1.05 + 1 * survival(ins_jl,2) / 1.05 ^ 2
-    @test present_value(AnnuityDue(ins_jl,n=0)) == 0
-    @test present_value(AnnuityImmediate(ins_jl,n=0)) == 0
-    @test present_value(AnnuityImmediate(ins_jl,n=1)) ≈ 1 * .75 /1.05
+    @test present_value(AnnuityDue(ins_jl, 1)) ≈ 1
+    @test present_value(AnnuityDue(ins_jl, 2)) ≈ 1 + 1 * 0.75 / 1.05
+    @test present_value(AnnuityDue(ins_jl, 3)) ≈ 1 + 1 * 0.75 / 1.05 + 1 * survival(ins_jl, 2) / 1.05^2
+    @test present_value(AnnuityDue(ins_jl, 0)) == 0
+    @test present_value(AnnuityImmediate(ins_jl, 0)) == 0
+    @test present_value(AnnuityImmediate(ins_jl, 1)) ≈ 1 * 0.75 / 1.05
 
 end
 
@@ -254,7 +254,7 @@ t = UltimateMortality(maleMort)
 
 @testset "demo mortality" begin
     i = Yields.Constant(0.05)
-    ins = LifeContingency(SingleLife(mort = t, issue_age = 0), i)
+    ins = LifeContingency(SingleLife(mortality = t, issue_age = 0), i)
 
     @test l(ins, 0) ≈ 1.0
     @test l(ins, 1) ≈ 0.993010000000000
@@ -276,21 +276,21 @@ t = UltimateMortality(maleMort)
     @test M(ins, 1) ≈ 0.0355801393752753
     @test M(ins, 2) ≈ 0.0351775312392208
 
-    @test present_value(Insurance(ins   )) ≈ 0.04223728223
-    @test present_value(Insurance(ins, n=0)) ≈ 0.0
-    @test present_value(Insurance(ins, n=1)) ≈ 0.0066571428571429
-    @test present_value(AnnuityDue(ins, n=0)) ≈ 0.0
-    @test present_value(AnnuityDue(ins, n=1)) ≈ 1.0 
-    @test present_value(AnnuityDue(ins, n=2)) ≈ 1.0 + survival(ins,1) / 1.05
-    @test present_value(AnnuityImmediate(ins, n=0)) ≈ 0.0
-    @test present_value(AnnuityImmediate(ins, n=1)) ≈ survival(ins,1) / 1.05
+    @test present_value(Insurance(ins)) ≈ 0.04223728223
+    @test present_value(Insurance(ins, 0)) ≈ 0.0
+    @test present_value(Insurance(ins, 1)) ≈ 0.0066571428571429
+    @test present_value(AnnuityDue(ins, 0)) ≈ 0.0
+    @test present_value(AnnuityDue(ins, 1)) ≈ 1.0
+    @test present_value(AnnuityDue(ins, 2)) ≈ 1.0 + survival(ins, 1) / 1.05
+    @test present_value(AnnuityImmediate(ins, 0)) ≈ 0.0
+    @test present_value(AnnuityImmediate(ins, 1)) ≈ survival(ins, 1) / 1.05
 
-    @test present_value(Insurance(ins, n=30)) ≈ 0.0137761089686975
+    @test present_value(Insurance(ins, 30)) ≈ 0.0137761089686975
 
     @test N(ins, 26) ≈ 5.156762988852310
     @test D(ins, 26) ≈ 0.275358702015970
-    @test present_value(AnnuityDue(ins, n=26)) ≈ 14.9562540842669
+    @test present_value(AnnuityDue(ins, 26)) ≈ 14.9562540842669
 
 
 
-end 
\ No newline at end of file
+end
\ No newline at end of file
diff --git a/test/single_life.jl b/test/single_life.jl
index b1eeb4e..9aae269 100644
--- a/test/single_life.jl
+++ b/test/single_life.jl
@@ -2,7 +2,7 @@
     @testset "issue age 116" begin
         t = MortalityTables.table("2001 VBT Residual Standard Select and Ultimate - Male Nonsmoker, ANB")
         i = Yields.Constant(0.05)
-        lc = LifeContingency(SingleLife(mort = t.ultimate, issue_age = 116), i)
+        lc = LifeContingency(SingleLife(mortality = t.ultimate, issue_age = 116), i)
 
 
         @test l(lc, 0) ≈ 1.0
@@ -27,13 +27,13 @@
 
         @test present_value(Insurance(lc)) ≈ 0.9418373716628330
         @test present_value(AnnuityDue(lc)) ≈ 1.2214151950805000
-        
+
         qs = t.ultimate[116:118]
-        @test present_value(Insurance(lc, n=3)) ≈ sum(qs .* [1;cumprod(1 .- qs[1:2])] .* [1.05 ^ -t for t in 1:3])
-        @test present_value(AnnuityDue(lc, n=3)) ≈ sum([1;cumprod(1 .- qs[1:2])] .* [1.05 ^ -t for t in 0:2])
-        
-        @test LifeContingencies.V(lc,1) == reserve_premium_net(lc,1)
-        @test LifeContingencies.v(lc,1) == Yields.discount(lc,1)
+        @test present_value(Insurance(lc, 3)) ≈ sum(qs .* [1; cumprod(1 .- qs[1:2])] .* [1.05^-t for t = 1:3])
+        @test present_value(AnnuityDue(lc, 3)) ≈ sum([1; cumprod(1 .- qs[1:2])] .* [1.05^-t for t = 0:2])
+
+        @test LifeContingencies.V(lc, 1) == reserve_premium_net(lc, 1)
+        @test LifeContingencies.v(lc, 1) == Yields.discount(lc, 1)
         @test LifeContingencies.A(lc) == present_value(Insurance(lc))
         @test LifeContingencies.ä(lc) == present_value(AnnuityDue(lc))
         @test LifeContingencies.a(lc) == present_value(AnnuityImmediate(lc))
@@ -44,12 +44,12 @@
     @testset "issue age 30" begin
         t = MortalityTables.table("2001 VBT Residual Standard Select and Ultimate - Male Nonsmoker, ANB")
         i = Yields.Constant(0.05)
-        life = SingleLife(mort = t.select[30], issue_age = 30)
+        life = SingleLife(mortality = t.select[30], issue_age = 30)
         ins = LifeContingency(life, i)
 
-        @test life.issue_age == SingleLife(mort = t.select[30]).issue_age
+        @test life.issue_age == SingleLife(mortality = t.select[30]).issue_age
         @test life.issue_age == SingleLife(t.select[30]).issue_age
-        @test life.issue_age == SingleLife(t.select,issue_age= 30).issue_age
+        @test life.issue_age == SingleLife(t.select, issue_age = 30).issue_age
 
 
         @test l(ins, 0) ≈ 1.0
@@ -81,10 +81,10 @@
         @test reserve_premium_net(ins, 2) ≈ 0.0119711961204193
 
         qs = t.select[30][30:55]
-        @test present_value(Insurance(ins, n=26)) ≈ sum(qs .* [1;cumprod(1 .- qs[1:25])] .* [1.05 ^ -t for t in 1:26])
-        @test present_value(AnnuityDue(ins, n=26)) ≈ sum([1;cumprod(1 .- qs[1:25])] .* [1.05 ^ -t for t in 0:25])
+        @test present_value(Insurance(ins, 26)) ≈ sum(qs .* [1; cumprod(1 .- qs[1:25])] .* [1.05^-t for t = 1:26])
+        @test present_value(AnnuityDue(ins, 26)) ≈ sum([1; cumprod(1 .- qs[1:25])] .* [1.05^-t for t = 0:25])
 
-        @test premium_net(ins, 26) ≈ LifeContingencies.A(ins, 26) /  LifeContingencies.ä(ins, 26) 
+        @test premium_net(ins, 26) ≈ LifeContingencies.A(ins, 26) / LifeContingencies.ä(ins, 26)
 
     end
 end
\ No newline at end of file
diff --git a/wip_benchmark.jl b/wip_benchmark.jl
new file mode 100644
index 0000000..706ad62
--- /dev/null
+++ b/wip_benchmark.jl
@@ -0,0 +1,22 @@
+using LifeContingencies
+using MortalityTables
+using Yields
+import LifeContingencies: V, ä     # pull the shortform notation into scope
+using BenchmarkTools
+
+# load mortality rates from MortalityTables.jl
+vbt2001 = MortalityTables.table("2001 VBT Residual Standard Select and Ultimate - Male Nonsmoker, ANB")
+
+issue_age = 30
+life = SingleLife(                 # The life underlying the risk
+    mort = vbt2001.select[issue_age],    # -- Mortality rates
+)
+
+yield = Yields.Constant(0.05)      # Using a flat 5% interest rate
+
+lc = LifeContingency(life, yield)  # LifeContingency joins the risk with interest
+
+@benchmark LifeContingencies.N(lc, 10)
+
+ins = Insurance(lc)
+premium_net(lc)