Pp. 75-86 of the Proceedings

A Java Reference Model of Transacted Memory for Smart Cards

Erik Poll
University of Nijmegen, the Netherlands

Pieter Hartel
University of Twente, the Netherlands

Eduard de Jong
Sun Microsystems, Inc., Santa Clara, USA

Abstract

1 Introduction

In a previous paper [6] we introduced Transacted Memory as an efficient means to implement atomic updates of arbitrarily sized information on smart cards. Smart cards need such a facility, as a transaction can be aborted by a card tear, i.e. by pulling the smart card out of the Card Acceptance Device (CAD), at any moment. A patent application has been filed for this Transacted Memory [5]. Its design allows a much smaller implementation overhead than the transaction mechanism in the current Java Card API¹, which does not even provide generational, logging, or multiple concurrent transactions.

In our earlier paper we provided a succinct abstract Z specification [13] of the system, a first Z refinement that takes into account the peculiarities of EEPROM memory (i.e. byte read versus block write), a second Z refinement that deals with card tear, and, finally, an (inefficient) C implementation. (The inefficiency is due to the use of many simple for-loops that search the memory; we are working on a VHDL specification of a hardware module that will replace the for-loops by efficient parallel searches but this is beyond the scope of the present paper.) The C implementation has been coded in such a way that it also serves as a SPIN [8] model.

From our earlier work we concluded that a formal connection between specification and implementation would have been highly desirable, yet such a connection cannot be obtained using Z and C. While a formal connection can be established using SPIN, we believe the readability leaves much to be desired, as specification and implementation tend to be intertwined in a SPIN model.

In the present paper we adopt an integrated approach to specification and implementation that solves the problems of readability and the lack of a formal connection between specification and implementation. We use the Java/JML [9] modelling method and tools, which means we write formal specifications by annotating the Java code with invariants, preconditions, and postconditions, using the specification language JML (see www.jmlspecs.org). These formal specifications can then be compiled into runtime-checks [4], providing a convenient way of checking specifications against code. The Java/JML modelling method and the runtime assertion checker ensure a strong, formal connection between Java implementation and JML specification.

In the present work we apply Java/JML to what we hope will become a component of a future version of the Java Card technology. JML has already been used to specify the entire Java Card API [11,12], and other tools than the runtime assertion checker have already been used to verify JML specifications of Java Card applets [3,1].

The contributions of the present paper are:

• Several bugs have been detected and repaired in the implementation of the Transacted Memory.

• We make the pre- and postconditions of the memory operations explicit in the JML specifications. The readability of these specifications is better because the reader does not have to trawl through the entire Z specification to discover the pre- and postconditions. The connection between specification and implementation is formal, and has been checked using the runtime assertion checker.

• The previous C implementation cum SPIN model relied on implicit methods of modelling the recovery from card tears. In the Java/JML model we use exception handling as an explicit, clearer method for modelling recovery. This allows us to test the behaviour of the Java implementation in the presence of (simulated) card tears, and to use JML to precisely specify the conditions that should hold after a card tear.

• We contribute a reference model of the Transacted Memory system to SUN's collection, instead of just a reference implementation. The difference is in the presence of the formal JML specification.

In Section 2 we review briefly how Transacted Memory works. Section 3 describes the Java implementation of the system, Section 4 discusses the JML specification for this Java implementation. The last section concludes.

Figure 1: The process

2 The Transacted Memory

Figure 1 describes the relationship between the various specifications and implementations of the Transacted Memory system. The Java/JML reference model, which is the subject of this paper, was derived by hand from the closely corresponding C implementation cum SPIN model for the Java part, and from the final refinement of the Z specification for the JML part. While Java and C are similar in many ways, there are some important differences, discussed in Section 3 below. Here we concentrate on how Transacted Memory works, giving excerpts of the abstract Z specification to make the present paper self contained; the details are in [6,2].

Transacted Memory is designed around two notions: tags and information sequences. A Tag is merely a unique address, i.e. an identifier of a particular information sequence. An information sequence is a sequence of Info's, where Info is the unit of data stored and retrieved. A sequence of Info's would be used to store a collection of object instances that are logically part of a transaction.

The abstract Z specification (below) makes no specific assumptions about either component:

The existence of a finite set of available tags is assumed (tags), as well as limits on the size of the memory (msize). There may be several generations of the information associated with a tag, and there is a maximum number of generations that may be associated with any tag (maxgen):

The abstract Z specification represents the memory system as two partial functions assoc and size and a set committed, as shown below. We have omitted the constraints on the partial functions and the set:

The assoc function associates a tag with a sequence of sequences of information. The first sequence of information represents the current information associated with a tag. Any further information sequences give older generations of this information, in order of increasing age.

The size function gives the length of the information sequences associated with a tag. The committed set records those tags for which the current state of the transacted data has been committed.

Operations are provided to write a new generation, and to read the current or older generations. All generations associated with a tag have the same size, although this could be generalised.

The transaction processing capability of the memory is supported by a commit operation, which makes the most recently written information the current generation. The oldest generation is automatically purged should the number of generations for a tag exceed a preset maximum. It should be noted that the support for recording multiple generations, which can be useful for logging, essentially comes for free, i.e. without any additional implementation cost.

As an example, the abstract Z specification of the operation ACommit is shown below. The operation commits the current generation of information associated with a tag. The tag must have an associated information sequence, which is flagged as committed.

The Transacted Memory must be used in such a way that a sequence of operations either completes normally, or that a sequence is interrupted at an arbitrary moment by a card tear. A recovery operation Tidy is provided to return the Transacted memory to a known state. The idea is that each time the card is inserted in the CAD, the recovery operation is automatically started.

Transacted Memory thus provides undoability (by being able to revert to a previous generation) and persistence (by using EEPROM technology). These are precisely the ingredients necessary to support transactions [10].

To provide this functionality, Transacted Memory maintains a certain amount of bookkeeping information. In its most abstract form, the bookkeeping information records three items:

• The length of the information sequence that is associated with a tag.

• The different generations of information associated with each tag. It is possible that there is no information associated with a tag.

• Which tags are currently committed.

The details of the Z specification may be found in a technical report [2]; here we focus on the API of the Transacted Memory, taken from our previous paper [6] and shown in Figure 2, because this is where the pre- and postconditions of the Java/JML specification provide the major contribution to readability and rigour.

3 A Java implementation of Transacted Memory

The Java implementation was obtained by manually transliterating the C code to Java code. This is not difficult as the languages are close, and for a program of this size (1200 lines) the effort involved is small. We have been careful in transliterating the C code, and we are confident that our Java implementation closely mimics the C implementation. There are two essential differences between the Java implementation and the C implementation, as explained below.

Static Type Checking

The C implementation contains several macros to define ``types'' for the different kinds of numeric values (bytes) that are used, such as generations, locations, page numbers, tags, versions, etc.:

#define Gen  byte  /* 0 .. maxgen  */
#define Loc  byte  /* 0 .. msize-1 */
#define PageNo  byte
#define Tag  byte  /* 0 .. tsize-1 */
#define Ver  byte  /* 0 .. 2 */
#define Inf  byte  /* 0 .. isize-1 */
#define Seq  byte  /* 0 .. ssize   */

In the Java implementation we have chosen to use different classes for these different kinds of values. This is inefficient since we make what is just a simple byte into an object. The inefficiency is not a primary concern here; we believe it to be more important for a reference model to be as clear and concise as possible². Modelling bytes by classes has the advantage of providing type-safety, as for instance `generations' and `tags' are no longer assignment-compatible. Interestingly, this increased type safety immediately revealed a bug in the C code (and SPIN model): in one place a `version number' was used in a place where a `page number' was expected. This bug seems to have been a simple typo in the C code. This bug was not discovered in the model checking using SPIN, nor in testing of the C implementation, because the test harness for the Transacted Memory used there was fairly restricted.

The discovery of this bug illustrates the value of a statically enforced type system. Especially for code like that of the Transacted Memory, which is littered with different `kinds' of bytes, it is easy to confuse a byte representing a page number with a byte representing a `version'. It is a pity that C and Java do not have type-safe enumeration types, and that JML does not improve the level of expressiveness of the Java/JML combination in this respect.

Modelling card tear

The second, and more important, aspect in which the Java implementation essentially differs from the C implementation is that we use Java's exception mechanism to model card tears. We introduce a special exception class CardTearException, and a card tear is simulated by throwing this exception. This is useful, because it allows us

1. to test the behaviour of the program when card tears occur; in the Java method that models atomic writes to EEPROM we can easily simulate random card tears by randomly choosing to throw a CardTearException or not, before or after the atomic write to EEPROM.
2. to specify in JML the properties that should hold after a card tear occurs; this will be discussed in Section 4.

In a later stage we will also introduce Java exceptions to signal that there is insufficient free transacted memory to carry out an operation, as discussed at the end of Section 4.

4 JML specifications for the Java implementation

The Java Modeling Language (JML) [9] is a behavioural interface specification language tailored to Java. JML is developed primarily by Gary T. Leavens at Iowa State University. Java programs can be specified using JML by annotating them with invariants, pre- and postconditions, and other kinds of assertions. JML combines features of Eiffel (or `Design by Contract') and model-based approaches, such as Larch/LSL and VDM.

JML annotations are written as a special kind of Java comments. This means they are ignored by normal Java compilers, but can be used by special tools for JML. The tools we have used on our JML-annotated code are the JML type-checker and the JML runtime assertion compiler [4]. Both these tools can be downloaded from www.jmlspecs.org. The runtime assertion compiler turns annotations into runtime checks, so that any violation of an annotation at runtime produces an error.

To create the JML specifications for the Java implementation, elements of the Z specifications and of the informal comments given in the C code were converted into pre- and postconditions, class invariants, and loop invariants. The JML specifications we have written are partial in the sense that they do not give a complete specification of Transacted Memory. Still, the specifications do express the main properties that should hold for the Transacted Memory, and have proven to be sufficiently detailed to find bugs, as we will discuss later.

Figure 2 gives an example of a JML specification, namely the specification of the method DWriteUncommitted. The JML specification is written between the annotation markers /*@ and @*/.

Figure 2: JML specification of DWriteUncommitted

The first three lines of the JML specification, starting with requires, give the precondition of the method. Here the precondition is that the tag should be in use, the information sequence i should be of the right length, and the tag should not be committed. When doing runtime assertion checking, any invocation of DWriteUncommitted which violates these preconditions will produce an error message³.

The next two lines, starting with ensures, give the postcondition of the method. The first of these lines says that if we read back the value for tag using DRead we get the value i we just assigned to it, the second says that the tag is still not committed. When doing runtime assertion checking, any invocation of DWriteUncommitted which does not establish these postconditions will produce an error message.

Finally, the last lines of the JML specification, starting with signals, give the exceptional postcondition. Whereas ensures clauses specify the `normal' postconditions, i.e. properties that should hold after normal termination of a method invocation, signals clauses specify properties that should hold at the end of a method invocation if an exception is thrown. The first signals clause here says that if a CardTearException is thrown then the tag remains uncommitted. The second signals clause says that if a CardTearException is thrown, then either

 DRead(tag).equals(i)

 DRead(tag).equals(\old( DRead(tag)))

Note that the information sequence i may consist of several bytes, and that a single DWriteUncommitted operation may require several writes to EEPROM. EEPROM is typically written block by block, where the block size depends on the particular EEPROM. So the second signals clause states the atomicity of the DWriteUncommitted operation!

When doing runtime assertion checking, any invocation of DWriteUncommitted which throws a CardTearException and which does not establish the exceptional postconditions will produce an error message. Throwing an exception that is not a CardTearException will also produce an error message, as there are no signals clauses allowing other exceptions to be thrown.

Everything the runtime assertion checker does could be programmed by hand, as tests in the code - the C implementation has a number of these tests scattered through the code -, but note that for something like the second signals clause above this is far from trivial! It would involve catching and re-throwing exceptions at the end of the method, as well as somehow recording the `old' value that DRead(tag) has in the pre-state. The JML runtime assertion tool compiles all this into the code automatically, which is useful, as it means we can concentrate on the essentials.

The other three write-operations - DWriteFirst, DWriteCommittedAddGen, and DWriteCommittedMaxGen - have specifications very similar to the one discussed above. The only difference is in their preconditions.

The specification of DWriteUncommitted above is still incomplete. For example, it does not specify that the older generations of the tag are left unchanged. Still, specifications like this turn out to be detailed enough to give useful feedback when checking them at runtime. As discussed below, several problems with the implementation came to light when performing runtime assertion checks.

Bug 1 - Uncommitting new generations

Performing tests of the Transacted Memory the runtime assertion checker immediately reported that DWriteCommittedAddGen and DWriteCommittedMaxGen do not establish their postconditions; more specifically, they fail to establish

 ensures !ddata[tag.value].committed;

Note that even in the Java/JML model we could have forgotten this postcondition, and then we would not have discovered the problem either. However, by systematically writing specifications for all the operations we believe one is less likely to forget something like this.

Bug 2 - Inadvertent commit

After Bug 1 was repaired, a second bug was discovered by runtime assertion checking. We also repaired the SPIN model and re-ran the model checker on that, and found the same error there.

The operations DWriteCommittedAddGen and DWriteCommittedMaxGen start a new, uncommitted, generation, but a card tear at a certain point in their execution may inadvertently commit the new generation written. Both DWriteCommittedAddGen and DWriteCommittedMaxGen first write the data for the new generation. This may take several atomic writes, but the last of these implicitly records that the whole write has been successful (in effect, making the whole writing of the data atomic). Then the commit flag is cleared - also atomically, but separate from the last write for the data. If a card tear occurs immediately after the data is written, but before the commit flag is cleared, the tag will appear committed to the recovery process, whereas in reality it should be uncommitted. The recovery process was not designed to detect this, and indeed a warning to this effect appears in the original Z specification [2, page 34].

The solution which we have implemented is to use not a boolean commit flag, but a three-valued flag, so that a DWriteCommittedAddGen or DWriteCommittedMaxGen interrupted at the precise point above can be detected during recovery. (An alternative solution would be to store the last of the data and the commit flag together in the same EEPROM block, as opposed to storing them in separate areas, so that writing the last of the data and the clearing the commit flag becomes one atomic operation.)

Optimisations and Improvements in the Algorithm

In addition to finding the bugs above, the systematic analysis of the code required to write the JML specifications also had the benefit of suggesting several optimisations and improvements to the code.

Efficiency Improvements

The method DGeneration(Tag tag) discovers the generation indices associated with a tag, and then returns the indices of the oldest and newest generation, as well as the number of generations. To better understand the implementation of this method, it was annotated with JML assert clauses. An assert clause can occur anywhere in a method body, and specifies a property that should hold at this point in the program. When doing runtime assertion checking, any violation of an assert clause will produce an error message.

Annotating the implementation of DGeneration(Tag tag) with assert clauses, we discovered that one for-loop could be removed, as the value it computed could already be computed directly from values already known.

Also, a redundant modulo operation % (i.e. one where the first argument will always be smaller than the modulus) was discovered in the implementation of DGeneration.

Interface Improvements

The four operations for writing to the Transacted Memory are:

• DWriteFirst
• DWriteUncommitted
• DWriteCommittedAddGen
• DWriteCommittedMaxGen

An unsatisfactory feature of the Transacted Memory as originally implemented in C is that if there is insufficient space to perform a write operation, it may be carried out only partially, resulting in an inconsistent state, without any warning. The informal specification of DWriteFirst in Table 2 does indeed say that its effect is undefined if insufficient space is available. The same can happen in the other write operations, although their informal specifications do not say this.

Our initial JML specifications for the write methods, e.g. the one in Figure 2, did not allow for this, and the runtime assertion checker warned about violations of them.

We improved the Java implementation so that a OutOfTransactedMemoryException is thrown in case insufficient space is available to perform a write operation. The JML specifications were adapted accordingly. For example, in the specification for DWriteUncommitted in Figure 2 we added

 signals 
  (OutOfTransactedMemoryException) 
      DRead(tag).equals(is) && 
      ! ddata[tag.value].committed;

Similarly, the operation DNewTag was adapted to throw an OutOfTagsException when no additional tag is available, rather than producing an undefined result in this case.

4.1 Future Work with these JML specs

Figure 3: JML specification of ACommit

We also translated the abstract Z specification given in [6] to Java/JML. This was not difficult, given that JML comes with a package org.jmlspecs.models that provides Java implementations of all the standard mathematical concepts used in the Z specification. For example, Figure 3 gives the JML translation of the Z specification of the operation ACommit shown in Section 2.

One obvious difference is that the Z specification looks prettier, as in Java/JML we do not have conventional mathematical notation, such as or .

A more important difference is that the JML/Java specification can be turned into an executable one, namely

 public void ACommit(Tag t)
 { committed = committed.insert(t);
 }

5 Conclusions

The work described in this paper, i.e.

• developing a Java implementation based on a C implementation, and
• developing JML specifications based on a Z specification, and
• checking the Java implementation against the JML specification using runtime assertion checking,

It is disappointing that the careful development of the system as reported in our previous paper [6] - starting from a formal abstract Z specification that was refined to an C/SPIN implementation, which was model-checked - did leave these bugs in the final implementation.

In all fairness, we must admit that the original testing scenario for the C/SPIN implementation with the model-checker SPIN was too restricted. Conventional testing of the C implementation would have discovered many of the bugs that we found, but probably with more effort. Runtime assertion checking of JML specifications makes it easier to locate bugs than conventional testing. Indeed, no complicated testing scenarios were needed to find any of the bugs discussed.

Some problems and possible improvements were found before we even tried runtime assertion checking, but were spotted when trying to come up with good specifications in the first place. Annotating Java code with JML specifications provides a systematic way of performing a thorough code review, which can help to discover bugs and may point to possible optimisations or improvements. By contrast, testing of the code may find the bugs, but will probably not suggest optimisations or improvements.

There is a fairly standard recipe for annotating Java code with JML. Typically, one starts by giving pre- and postconditions for each method; these can be based on existing informal specifications, on our informal understanding of the program, and - somewhat exceptionally here - on the formal Z specifications. For each method implementation one then informally checks that any method invocations it contains do not violate their preconditions; this may require further strengthening of its precondition, or the introduction of loop invariants. Then one compares the different pre- and postconditions that have been written. Commonalities between pre- and postconditions may suggest class invariants. Differences between them may point out possible omissions; e.g if the precondition of DWriteUncommitted (Tag tag) requires a tag to be uncommitted, then its postcondition should probably state whether this tag remains uncommitted or not, and possibly other methods that have a tag as argument should be specified with similar conditions. Finally, any violations of assertions found during runtime assertion checking in test scenarios may of course lead to improvements in the JML specifications.

For the system we considered, a vital advantage of using Java over using C is that we can conveniently model card tears using Java's exception mechanism. A disadvantage of using Java instead of C is that C is probably closer to a realistic implementation in actual hardware.

Using Java and JML, rather than C and Z, for implementation and specification, has had several advantages.

Firstly, it becomes possible to check the relation between implementation and specification: runtime assertion checking tells us where Java implementation and JML specification disagree. This may of course just as well be a mistake in the Java implementation as a mistake in the JML specification.

Secondly, Java implementation and JML specification are close together, in the same file. The usefulness of this is illustrated by the fact that the Z specification actually discusses the possibility of bug 2, but in a footnote on page 34 of [2], something one is not likely to notice or remember when working on the C implementation.

Finally, the JML specifications are a lot easier to understand than the Z specifications, except for experts in Z. JML mainly uses Java notions and notations, and it has been the overriding design principle in the design of JML that specifications should be easy to understand by any Java programmer. Indeed, a point we would like to stress is that formal methods need not involve notations and tools that only specialists can use. Our formal model is a Java program, that can be understood by anyone familiar with Java, as can the formal specifications for it written in JML. In this respect, it is interesting to note the contrast with Z and SPIN - or indeed UML! Developing the kind of JML specifications we discussed in this paper and using the runtime assertion checker should not pose any problem for competent Java programmers.

6 Acknowledgments

The work by Erik Poll is financially supported by the IST Programme of the European Union, as part of ``VerifiCard'' project (IST-2000-26328).

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... API¹

Java and all Java-based trademarks and logos are trademarks or registered trademarks of Sun Microsystems, Inc. in the U.S. or other countries, and are used under license.

... possible²

Also, the Java Card technology offers the possibility to optimize API components, such as the transacted memory API, in the offcard converter.

... message³

Actually, JML is so expressive that some JML assertions are not decidable, e.g. assertions using the keyword forall to quantify over an infinite domain; these (parts of) JML assertions are not compiled into runtime checks.