Forward search without candidates at specific model size

I'm currently working on the search_terms argument (fixing bugs and improving documentation). While doing so, I realized that there can be model sizes for which the forward search doesn't have any candidate models, for example:

options(mc.cores = parallel::detectCores(logical = FALSE))
data("df_gaussian", package = "projpred")
df_gaussian <- df_gaussian[1:41, ]
dat <- data.frame(y = df_gaussian$y, df_gaussian$x)
library(rstanarm)
rfit <- stan_glm(y ~ X1 + X2 + X3 + X4 + X5,
                 data = dat,
                 seed = 1140350788)
library(projpred)
vs <- varsel(rfit,
             nclusters = 3,
             nclusters_pred = 5,
             method = "forward",
             search_terms = c("X1 + X2"),
             seed = 46782345)

(tested with projpred 2.1.1). If you inspect the output of that varsel() call, you'll see that X1 + X2 is regarded as the solution term at model size 1:

print(vs)

gives

Family: gaussian 
Link function: identity 

Formula: y ~ X1 + X2 + X3 + X4 + X5
Observations: 41
Search method: forward, maximum number of terms 1
Number of clusters used for selection: 3
Number of clusters used for prediction: 5
Suggested Projection Size: NA

Selection Summary:
 size solution_terms   elpd  se  diff diff.se
    0           <NA> -101.6 2.9 -17.4     3.4
    1        X1 + X2  -93.9 2.8  -9.7     2.3

and plot(vs) behaves accordingly. Now my question (especially to @AlejandroCatalina) is whether this is intended or whether X1 + X2 should be regarded as the solution term at model size 2 because it consists of the 2 terms X1 and X2. The latter would probably require some larger changes because all functions downstream of search_forward() would have to be adapted to deal with "empty model sizes".

Start with the reproducible R example in the issue and inspect search_forward(), then trace how varsel() and plot(vs) consume its model sizes. First determine whether a grouped search term belongs at its term count or at the next model size. Done means the chosen behavior is consistent in the selection summary and plot, including sizes with no candidate models.