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CHECKSUM: tracking changes and measuring contributions in cooperative systems modeling

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Abstract

Models are often used to represent various types of systems. This is especially true for software systems, where cooperating teams create models using a modeling language (e.g., UML). In cooperative modeling scenarios, it is useful to identify contributions and changes performed by individuals and teams. This paper presents a technique called CHECKSUM, which monitors the cooperative work done on models and maintains an immutable changelog. CHECKSUM uses its changelog to measure contributions based on points, time, and quality, and to enable the auditing of a model’s change-history. This paper also presents GEneric Meta-Model (GEMM). The latter unifies the underlying representation of different types of models that follow varying visualization patterns including box and line, container, and interleaving. GEMM enables CHECKSUM to support an extensible variety of model types. We developed a prototype tool that realizes CHECKSUM’s concepts and integrates it into two existing modeling tools. We conducted two studies to evaluate CHECKSUM from two perspectives: technical and user. The studies yielded positive results concerning various qualities including integrability into existing tools, effectiveness, efficiency, usability, and usefulness.

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  1. Department of Computer Science, Notre Dame University-Louaize, Zouk Mosbeh, Lebanon

    Pierre A. Akiki & Hoda W. Maalouf

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  1. Pierre A. Akiki
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Appendix A: CHECKSUM’s storage mechanism

Appendix A: CHECKSUM’s storage mechanism

CHECKSUM is not mainly related to blockchain technologies, but it uses a blockchain-based mechanism for storing its data. Hence, this appendix offers a brief overview of blockchains and presents CHECHSUM’s storage mechanism.

1.1 Background on blockchain technologies

Blockchain is an infrastructural technology that relies on a distributed ledger, immutable storage, and consensus algorithms. These three technologies decentralize data storage and change the way people collaborate by improving the trustworthiness and integrity of transactions. A common example application for blockchain is the Bitcoin Protocol [52]. Although cryptocurrencies such as Bitcoin are possibly the most common example application of blockchain, there are other important applications such as insurance claim processing and supply chain management. Some platforms support the definition and management of blockchain-based systems using different programming languages. Examples of these platforms include: Ethereum [114], BigChainDB [115], Neo [116], Ripple [117], and Stratis [118]. Version control systems (refer to Sect. 2.3) are a form of blockchain in the sense of having an immutable ledger that keeps a history of changes. However, blockchains use a decentralized approach rather than a centralized one. For example, Nizamuddin et al. [56] presented a decentralized document version control system that is based on Ethereum.

As several researchers noted, blockchains can play an important role in interaction design [27]. One interesting and useful area of application is related to capturing each individual’s contributions to a creative process [31].

1.2 CHECKSUM’s storage mechanism

We based CHECKSUM’s storage mechanism on blockchain to provide immutability and to improve integrity and trust. This mechanism’s concepts and model-management process are presented in Figs. 

Fig. 39
figure 39

Concepts of CHECKSUM’s blockchain-based storage mechanism

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39 and

Fig. 40
figure 40

a Multi-node peer to peer communication and b model management process

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40 respectively.

1.2.1 Concepts

We designed a blockchain-based persistence layer for CHECKSUM’s prototype. This design supports the use of different types of DBMSs for local storage. This way it is possible to run various queries efficiently using common query languages, which is more difficult to do with traditional blockchain platforms. Researchers have extended existing blockchain platforms to make queries more efficient with approaches such as EtherQL [43] and VQL [63]. When such solutions become more time-tested, it is possible to consider using one of them with an existing blockchain platform in a future version of CHECKSUM.

There are three main concepts in our design, namely Blockchain, Block, and BlockEntry (transaction); these concepts are common in blockchain applications. Every Project has multiple Blockchains; each one stores a different part of the data. Typically, each Blockchain is composed of multiple Blocks that are in turn composed of multiple BlockEntries. The latter represent the data that are stored on a Blockchain.

Consensus algorithms are used to protect the integrity of the data stored on a blockchain, by preventing users from tampering with it and spamming the blockchain with a large number of blocks. Our implementation uses Proof of Work, which is the original consensus algorithm used by Bitcoin. The “Mine” function on Block computes the Block’s hash, based on a “difficulty” value. This function keeps on calling “CreateHash” until it gets a hash that starts with a number of zeros pertaining to a given proof-of-work difficulty. Increasing the difficulty makes it harder to generate new Blocks since it will take longer to find a hash that starts with a higher number of zeros. To get new hashes during the trials without changing the data, a nonce value is used and assigned a new random number after every attempt to get the desired hash.

The ChangeTrackingBlockchain stores tracked changes that are represented as ChangeTrackingOperations. It is possible to reconstruct Models out of their ChangeTrackingOperations. However, not all changes are necessarily tracked (refer to ChangeTrackingRules in Sect. 4), and the reconstruction can be time-consuming. Hence, Models (including diagrams, elements, etc.) are stored separately on the ModelBlockchain.

Users check-in and check-out models as they would do with source control systems. Each Model’s status (checked-in or checked-out) is stored on the ModelStatusBlockchain. The ConfigurationBlockchain saves Configurations that are related to access control, change tracking, and contribution measurement. These Configurations include the following concepts: BlockOperation, BlockOperationReason, ChangeTrackingRules, TimePeriodUnit Duration, OperationTypes, QualityRatingTypes, and RatingReasons.

To enable the persistence of the blockchain data using a DBMS, we defined repositories that provide functions for storing and querying this data. The IBlockchainRepository is the high-level interface that defines the common functions for the other repositories. These functions create, update, and retrieve Blockchain data. A delete function is not included since Blockchains provide immutability by acting like a ledger that logs all transactions. The IBlockchainRepository refers to an IBlockchainUnitOfWork whose concrete implementation works with Blockchains that need to be created or updated. The ChangeTracking, Model, ModelStatus, and Configuration repositories define methods for retrieving data from within the Blockchains. The class diagram presented in Fig. 39 shows a summary of these methods. If we choose to change the implementation to use a blockchain platform, we just need to define an alternative BlockchainContext that interacts with the selected platform rather than a DBMS.

1.3 Model management process

CHECKSUM’s data is shared among users across a peer-to-peer (P2P) network with multiple nodes, where each node represents a user’s device (Fig. 40a). We used WebSockets to enable communication among peers. The nodes act as both clients and servers and engage in full-duplex communication to exchange data and update their local blockchains.

The steps that show the process of managing models with CHECKSUM are presented in Fig. 40b. When a user opens a model design tool, the latter requests updates from peers on the network and updates the local data in all blockchains.

The new models that a user creates are saved in a local database. The changes performed on a model are tracked and also saved locally. When a user is done working and checks-in a model, the latest version of the model is added to the local model blockchain and the model’s new status (checked-in) is added to the local model status blockchain. Then, all the updates that include the model, its status, and the tracked changes are broadcasted to all the other nodes on the network.

When a user checks-out a model, the model’s new status (checked-out) is registered on the model status blockchain, and it is broadcasted to all other nodes on the network. The process of creating and modifying Configurations is similar. Therefore, we did not repeat it in a separate figure.

When transferring data among peers, some nodes are likely not available. This could be due to computer crashes or users being offline. A message broker, RabbitMQ [119], could be used to alleviate this problem. The message broker holds messages in a queue, and a retry mechanism reprocesses the messages in case of failures. This ensures that nodes receive messages from their peers when they come back online. This allows nodes to identify the true status (checked-in or checked-out) of a model, to work on up-to-date model content, and to observe the most recent changes and contributions.

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Akiki, P.A., Maalouf, H.W. CHECKSUM: tracking changes and measuring contributions in cooperative systems modeling. Softw Syst Model 20, 1079–1122 (2021). https://doi.org/10.1007/s10270-020-00840-3

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